Session J00: Poster Session I (2pm-5pm CST)

Fabricating a Twisted Bilayer WSe2 Device

The distinct properties of the quantum confinement effects in two-dimensional materials from that of bulk three-dimensional materials have led to enormous research attention in 2D materials. Since 2D materials are uniform and have a fixed and thin thickness, confinement effects are observed. Due to this, combining different 2D crystals held by van der Waals forces can be made into one vertical stack known as the Vander Waals heterostructure. Stacking one monolayer over another has opened up new paths to band engineering. Fabricating a twisted bilayer transition metal dichalcogenides (TMDs) device is the foundation of this experiment. Two-dimensional transition metal dichalcogenides (TMDs) moire systems, specifically twisted bilayer tungsten diselenide (tWSe2) exhibit exceptional tunability bandstructure properties enabling the exploration of more quantum effects. Recent experiments in graphene-based heterostructures using tuning parameters such as twist angle, pressure, and layer stacking have proven superconductivity. Although these parameters have also been investigated in moireTMD systems, applying pressure to prove superconductivity and other phenomena has rarely been studied. In this project, we fabricated a twisted bilayer tungsten diselenide (tWSe2) and used it in an ongoing project that deals with correlations under pressure.   

Exploring the Potential of Flexible Piezoelectric Materials for Energy Harvesting Applications

Energy harvesting has become a rapidly expanding field of research driven by the growing demand for clean and renewable energy sources. Piezoelectric materials have shown great potential in harnessing energy from wasted mechanical energy. They possess the remarkable ability to convert mechanical energy into electrical energy which makes them highly suitable for energy harvesting applications. Consequently, they have emerged as attractive alternatives to traditional rechargeable batteries, particularly for powering low-energy devices like wearable technology and wireless communication systems. Despite this, harnessing the full potential of piezoelectric materials for energy harvesting requires certain challenges and obstacles to be addressed. Hence, this comprehensive study explores the capabilities of piezoelectric materials in energy harvesting applications and proposes novel approaches to enhance their performance. Specifically, the study examines currently available piezoelectric elements in the market, explores different self-powered energy harvesting circuits, and investigates the development of flexible piezoelectric cells, such as barium titanate (BaTiO3), to improve durability, conformability and energy harvesting properties. In addition, the study delves into advancements toward achieving high-efficiency energy generation.   

Phase Analysis of Charge Density Waves in Kagome Superconductors Using Scanning Tunneling Microscopy

Charge density waves (CDWs) can be analyzed using Scanning Tunneling Microscope (STM) images. In this study, we demonstrate an approach to investigate CDWs by registering STM images of the same sample at different bias voltages, followed by an Inverse Fourier Transform and line cuts of the resulting images. This process allowed us to create a waterfall plot, revealing the phase shift in the charge density wave. The phase shift provided crucial insights into positioning the Charge Density Wave gap relative to the Fermi Level. Our investigation focused on a sample of crystal CsV3Sb5, and we discovered that the pi phase shift occurs between unexpected sample biases of -280 meV and -240 me instead of at the expected 0 meV.   

Limits of coupled learning for multifunctional allosteric responses in physical flow networks

Traditional methods of designing functional materials often involve extensive trial and error or a deep understanding of material properties. Physical coupled learning offers a promising alternative as a local method for training networks to accomplish tasks and perform computations in response to external stimuli. Utilizing the framework of coupled learning, this work expands on how the scaling of networks can affect the training of successful linear allosteric responses. Through simulations of 2D flow networks we show how the error of responses decreases with the size of the network and increases with the number of tasks to be trained. We also analyze how geometry and connectivity of sources (inputs) and targets (outputs) can impair learning, making a task achievable or not. Comparison with global gradient descent reveals similar results, indicating that network properties — rather than the learning method — may dictate limitations of multifunctionality in physical systems.   

Impact of the Mechanical Processing of Nanocellulose on the Characteristics of Nanocellulose Derived Solids

Nanocellulose fibers were formed by ultrasonic mechanical processing of a mixture of powdered microcrystalline cellulose and distilled water which results in a water-based suspension. We found that the feature sizes of the resultant nanocellulose particles depended strongly on processing parameters like ultrasonic power, processing time, and the concentration of cellulose in the suspension. We found a dimensional crossover in the nanocellulose features with highly viscous suspensions forming 2D sheets rather than 1D fibers. We also found there were significant differences between batch and flow-through processing, with flow-through resulting in a higher percentage of the microcrystalline cellulose broken down into nanocellulose. Suspensions were air-dried to form hardened solids and freeze dried to form aerogels. We found that the void concentration in the aerogels closely aligned with the water concentration in the original suspension. Aerogels composed of 1D fibers were significantly stronger than those formed of 2D sheets. Larger air-dried solids were able to be formed with smaller nanocellulose particles without cracking. These results enable us to determine optimal processing parameters to create nanocellulose with desired feature size in the most efficient manner possible.   

"Corona" Wind and Its Relationship to Voltage and Electrode Size in Alternating Current Electrospinning

Electric fields generated by high voltage alternating currents (AC) result in the propagation of electrohydrodynamic "corona" winds in the surrounding gas. This phenomenon is essential for the AC electrospinning process where this voltage is applied to an electrode containing a liquid polymer layer. Electrified liquid jets are generated from this layer to form nanofibers upon the evaporation of the polymer solvent. The propagation of nanofibers primarily depends on the corona wind phenomenon. Consequently, documentation and analysis of the is imperative for the understanding and commercialization of AC electrospinning. This investigation utilizes "dry" experiments without electrospinning precursors to isolate the corona wind parameters to the electrode. Measurements are taken at vertical distances commonly used in the AC electrospinning process. The variance in corona wind velocity distributions due to the shape of the electrodes and applied voltage are discussed.   

ATR-FTIR Investigation of Plastics Treated by Atmospheric Pressure Plasma

The growth of plastic waste in modern society is unsustainable and there are large scale environmental and human health consequences. Chemical upcycling of plastic wastes is an emerging strategy to combat this environmental problem. Using innovative techniques such as plasma decomposition plastics can be broken into value-added chemicals, ex. CO, C2H2, used in chemical synthesis . Plasma decomposition of plastics through pyrolysis and hydrogenolysis, produces monomers and oligomers allowing for the formulation of new high quality compounds. Three different plastics polymers, Polypropylene (PP), Polyethylene Terephthalate (PET), and Low Density Polyethylene (LDPE), were exposed to Ar plasma at atmospheric pressure with additions of H2 and N2. After treatment, the remaining solid materials were analyzed via Fourier Transform Infrared spectroscopy (FTIR) with an ATR accessory. The treated PET showed little measurable changes after plasma exposure, but PP showed increased oxides. Additionally, the PP and LDPE treated in the Ar/H2 mixture showed the break up into smaller chains than when treated with Ar alone. The addition of N2 resulted in LDPE, there is evidence of oxides and nitrates with the presence of nitrogen gas. The presence of short fragments in the LDPE and PP with the addition of H2 gas provides evidence for hydrogenolysis as a decomposition process in plasma treatment of plastics.
Acknowledgement:
The work of Dorothy Doughty was supported by the Student Undergraduate Laboratory Internship and SS was supported by the Princeton Collaborative Research Facility, supported by the US Department of Energy, contract no. DE-AC02-09CH11466.   

Effect of proton irradiation on the properties of YBCO thin-film superconductors

We studied the effect of 600 keV proton irradiation on the properties of YBCO thin film superconductors. A 500 nm thick YBCO-1237 sample was subjected to a series of proton irradiations with a total fluence of 7.2 x 10¹⁶ p/cm². Upon irradiations, the superconducting critical temperature (T_c) was drastically decreased from 90 K towards zero Kelvin, and the normal state resistivity increased accordingly. The rate of T_c reduction to resistivity increase will be used to discuss the relation between impurity and superconducting gap.   

Effects of Hydrogen Molecule Absorption on the Raman Scattering in Few-layer Graphene

Hydrogen storage is vital for the future of clean energy, given its environmentally friendly water byproduct, non-toxic nature, and absence of pollution. While many studies have been dedicated to enhancing efficiency in graphene oxides, intrinsic graphene remains an intriguing storage platform awaiting further exploration. In this work, we investigate the effects of hydrogen pressure, number of layers and defect density of graphene on hydrogen storage efficiency. We prepared graphene thin layers using the "scotch tape" method and then exposed them to molecular hydrogen gas, monitoring the absorption via Raman spectroscopy. We find that the G peaks for graphene layers with different thicknesses shift to a lower wavenumber with time upon hydrogen introduction. Notably, monolayer graphene exhibits the most significant red shift in the G peak. Conversely, the 2D peak remains largely unaffected, exhibiting unobvious time-dependent variations. Furthermore, our defect analysis under varying hydrogen pressures accentuates the distinction between pristine and defected graphene. Our findings underscore that specific Raman modes offer a promising avenue for determining hydrogen storage efficiency in 2D materials.   

Dependence of cellulose nanocrystals on feedstock cellulose feature size

We have explored the potential for high efficiency production of nanocellulose crystals from purified cellulose stock. Production efficiency is problematic for incorporating nanocrystalline cellulose an economical fashion, Here, we use standard acid hydrolysis to cleave the cellulose molecules and form nanocrystalline structure, but vary the starting cellulose input. Using mechanical processing via ultrasonic agitation, we can first reduce the size of the purified cellulose into nanoscale form. By varying process parameters and the ratio of cellulose to water during sonication, we can achieve both 1D and 2D features, as well as tune feature size between 10 nm diameter to the micron scale. By examining the time, energy output, and machine wear, we can determine how to improve production efficiency and explore different processing pathways to potentially utilize nanocrystalline cellulose in commercial applications.   

Ground State Stability for the spin-1/2 ferromagnetic Heisenberg spin ring

For the quantum Heisenberg spin-j model on a bipartite, balanced graph, the ground state of the antiferromagnet is a spin singlet by the Lieb-Mattis theorem, "Ordering of energy levels." Moreover, the minimum energy in the spin S sector E(S) is monotonically increasing as S moves from 0 to j|V|. The Lieb-Mattis theorem also implies that for the ferromagnet the absolute ground state is E₀^FM(S_max). However, their theorem does not necessarily imply that E(j|V|) is monotonically decreasing as a function of S for the ferromagnet, as one might expect. We use the tool of first-order perturbative linear spin wave theory, and show that in that context E(0) < E(1). This is modelled on the Lieb-Schultz-Mattis theorem about gapless spin systems. This tool is applicable for sufficiently large systems, such as long spin rings, in the presence of a spectral gap. For spin j = 1/2, all this was already proved by Sutherland, using the Bethe ansatz. But we present numerical evidence for spin rings for j > 1/2, as well.   

Rare Earth Metal Erbium Under High Pressures and Low Temperatures

The rare earth metal erbium has gained the attention of physicists for its unique characteristics of nearly zero thermal expansion at low temperatures and large magnetic dipole moment, making this material an excellent candidate for permanent magnets at low temperatures. Erbium metal was studied under high pressures up to 65 GPa and low temperatures down to 20 K in a diamond anvil cell by X-ray diffraction (XRD) at HPCAT, Advanced Photon Source, Argonne National Laboratory. Pressure was monitored during the experiment through a combination of ruby fluorescence and the measured volume of a copper pressure marker at high pressures and low temperatures. The XRD data was analyzed with GSAS-II to identify lattice parameters for both copper and erbium. The erbium sample data was analyzed at pressures of 1, 20, 40, 50, and 65 GPa and temperatures between 295 K and 20 K for each pressure point. The analysis of thermal expansion data for the hexagonal close packed (hcp) phase and the double hexagonal close packed (dhcp) phase of erbium confirm the nearly zero thermal expansion characteristics of this material to the lowest temperature of 20 K. The x-ray diffraction data is complemented by the neutron diffraction study of magnetic ordering at the SNAP beamline at the Spallation Neutron Source, Oak Ridge National Laboratory.   

Effect of Environmental Humidity and Temperature on the Variations in Physiochemical Properties of Monolayer Graphene in Sliding Electrical Contact Interface

We study the physiochemical properties of supported single-layer graphene (SLG) rubbed with an electrically-biased conductive AFM (cAFM) probe under various environmental humidity and temperature. During the experiment, the relative humidity is changed from 0% to 80% while the temperature is controlled between 10°C and 80°C to regulate the capillary condensation of nanoscale water meniscus formed around the cAFM probe-SLG contact zone. The effective work function (WF), structural, and chemical properties of rubbed SLG are respectively investigated by Kelvin probe force microscopy, Raman spectroscopy, and X-ray photoelectron spectroscopy. When a positive voltage is applied to the probe, tunneling triboelectric (TTE) effect occurs, which modulates the electrical properties, i.e., the effective work function (WF) of SLG. On the other hand, when a negative bias is applied, water molecules in the nanoscale water meniscus will be electrolyzed, leading to local oxidation of SLG. Together with TTE, chemical functionalization of SLG surface also results in variations in the effective WF and chemical properties of SLG that depends on the sliding velocity of cAFM probe, humidity, and temperature. Our findings offer valuable insights into the design of novel graphene-based nano-devices that involve sliding electrical contact interface, especially those designed for operation across a wide range of ambient humidity and temperature conditions.   

Dendritic Growth of Ammonium Nitrate Crystals

Dendritic crystal growth is an important example of nonequilibrium pattern formation that involves both nonlinear dynamics and noise-driven effects. It is commonly observed in the growth of metal alloys, but can also be observed in the solidification of some transparent organic and inorganic compounds. In particular, the growth of ammonium nitrate dendrites are of interest because ammonium nitrate is essential for creating fertilizers. The resulting large-scale structures exhibit growth facilitated by chemical or thermal diffusion and are sensitively dependent on relatively small effects, such as surface tension, and also on small anisotropies in those quantities. In this work, we present results for phase II ammonium nitrate dendrites grown from supersaturated aqueous solution.  This new system has been studied previously by van Driel et al.[1].  Specifically, we present new measurements of the tip radius ρ, growth speed v, and sidebranch spacing λ, along with initial estimates of the stability constant σ*=2d₀D/vρ², where D is the chemical diffusion constant and d₀ is the capillary length. We also discuss the large-scale structure of the dendritic patterns, and make qualitative comparisons between ammonium nitrate dendrites and crystals of other chemistries that demonstrate dendritic growth.

[1] Van Driel, C.A., Van der Heijden, A.E.D.M, Van Rosmalen, G.M., "Growth of Ammonium-Nitrate Phase-I and Phase-II Dendrites." J. Cryst. Growth 128 (1993) 229–233.  https://doi.org/10.1016/0022-0248(93)90324-P   

Micromagnetic Simulation of Meander-Like Sensing Elements

Magnetic sensors find applications in accelerometers, magnetometers, biomagnetism, magnetic compasses, traffic control, non-destructive analysis, and virus and cancer cell detection. The most sensible technique for detecting magnetic fields is the Superconducting Quantum Interference Device (SQUID), which uses cryogenic liquid, requires large facilities and has a high-cost operation. In this context, magnetic sensors based on the Giant Magnetoimpedance (GMI) effect can be a low-cost alternative, once they are compact, present tunable sensibility, fast response, and operate at room temperature. In this work, we simulate meander-like thin film magnetic sensing elements of Permalloy (Ni₈₀Fe₂₀) for working based on GMI. To understand how parameters such as composition, film thickness, meander's number of turns, and total length of the sensing element affect the sensitivity of the sensor, we simulate hysteresis curves and spatial distribution of the magnetic moments using the well-established micromagnetic simulator Object Oriented Micromagnetic Framework (OOMMF). We also investigate the preferential anisotropies axes along with the element sensor works more effectively and determine a set of parameters that maximizes the sensor's sensitivity to proceed with fabrication processes.   

Fundamental Analysis of Carbon Spheres Synthesized via Sucrose-Derived Hydrothermal Carbonization

Carbon spheres are a promising material than can be used in various applications, including energy storage, drug delivery systems, and reinforcement in composites. This study focuses on the preparation and characterization of carbon spheres produced via hydrothermal carbonization using sucrose as a sustainable and cost-effective carbon source. The precursor solution concentration is adjusted to tailorthe size of the microspheres, a crucial factor that impacts their properties. Next, the spheres are subjected to thermal annealing at 600 °C in an inert atmosphere to eliminate functional groups and increase the carbon content. The thermal transformations occurring in the preparation of reduced carbon spheres (rCS) are investigated through thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) across a broad temperature range from 25 to 800°C. Additional characterization techniques, like scanning electron microscopy (SEM), fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD), provide in-depth insights into their morphology, composition, surface chemistry, and structural complexities. The results confirm the successful reduction of functional groups and structural changes during thermal annealing. Further investigation into the impact of precursor concentration and annealing temperature on the properties of rCS will be presented.   

Thermal and structural properties of 3D printed silk fibroin

Silk fibroin, the protein in cocoon fibers of the Bombyx mori silkworm, is used across many fields due to its tensile strength and flexibility [1]. Because it is biocompatible and biodegradable, it is the ideal material for many biomedical applications [1]. We study the use of 3D printing to create printed parts of silk fibroin. The process involves extraction of fibroin from cocoon fibers, enrichment to obtain a printable solution, printing into a coagulation bath, and characterization of the secondary structures of the resulting parts. We focus on the salt-water coagulation bath, which crystallizes printed parts through the formation of beta pleated sheets [1]. Two factors must be considered during the coagulation process. First, silk fibroin takes up bound water during the printing process, which lowers its glass transition temperature (T_g), making it weaker [2]. Second, the presence of beta sheet crystals strengthens the material and increases T_g [3]. We examine the relationship between bound water content and degree of crystallinity, and the salinity of the coagulation bath. Building more resilient and stronger silk leads to better 3D printed parts, beneficial in biomedical applications.

References

[1] Mu, X. et al., Advanced Healthcare Materials, 19(5), e1900191 (2020).

[2] Hu, X. et al., Thermochimica Acta, 461(1-2), 137 (2006).

[3] Hu, X. et al., Macromolecules, 39(18), 6161 (2006).   

Title: Nanomaterials Patterning Involving Undergraduates at Illinois State University

The use of nanomaterials for the fabrication of different optical, magnetic, chemical, biomedical, and microelectronics devices has received tremendous attention because of lower power consumption, faster response, and higher performance. Patterns of these nanomaterials with a tunable structure, size, and composition are critical for achieving the precision necessary to make these emerging devices. In our experimental physics laboratory at Illinois State University, we use self-assembled patterned block copolymers (BCPs) as templates in a process called sequential infiltration synthesis (SIS) to fabricate nanopatterns by selectively infiltrating inorganic material inside the polymer. During our study, we have explored different BCPs as templates for SIS, including poly(styrene-b-methylmethacrylate) (PS-b-PMMA) and polystyrene-block-poly(α-caprolactone) (PS-b-PCL). In our lab, using these nanostructures of BCP as guiding patterns, we fabricate nanopatterns of various inorganic materials such as aluminum oxide (Al2O3), silicon dioxide (SiO2), and aluminum nitrides (AlN). We characterize these nanopatterned structures using scanning electron microscope (SEM), Energy-dispersive X-ray spectroscopy (EDX), and Fourier Transform infrared spectroscopy (FTIR). In our presentation, we will discuss the fabrication process of nanomaterials using BCP and SIS and will show the structural and physical properties of the fabricated nanostructures.   

Low Temperature Growth of Superconducting Thin Films for Quantum Computation

The field of superconducting quantum computing uses superconducting circuit elements to store information in qubits. These devices are fabricated using high quality thin film superconductors. Poor quality superconductors lead to a decrease in the critical temperature of the superconductor, making it difficult to use qubit systems. In this work, we explore methods of low temperature (<10 K) molecular beam epitaxy (MBE) growth to increase the critical temperatures of superconducting tantalum (Ta) and niobium (Nb) thin films on sapphire substrates. We compare the critical temperature, T_C, of thin films grown at low temperature (LT) to room temperature (RT). We found that LT MBE growth does result in higher critical temperatures compared to RT growth, most significantly for Ta thin films. Using atomic force microscopy imaging for structural analysis, we saw that LT growth produced smoother Ta films, whereas it produced rougher Nb films. Though we did not see a consistent structural difference between LT and RT growth, the increase in T_C as a result of LT growth was significant in both Ta and Nb.   

Crushing Emulsions: A tensiometer study of different diameter ferromagnetic emulsions

Generating emulsions with microfluidics has become a popular topic in science over the last decade. While most of these emulsions are thermodynamically unstable, recent developments have succeeded in making stable emulsions with hard-shells using nanoparticles. This study focuses on measuring the tension required to crush these hard-shelled emulsions as a function of their diameter. At the time of this writing, we are also exploring how these destructive properties manifest in both double and single emulsions as a function of their size.    

Investigating Economic Methods to Synthesize Wood Biochar for Supercapacitor Electrodes

We investigated economic methods for producing bur oak biochar to replace fossil fuel-derived activated carbons as electrode materials for supercapacitors. Three synthesis methods were evaluated by their operating temperatures, mass yield, setup cost, ease of use, and their performance in supercapacitor electrodes: a top-lit updraft gasifier, distillation of wood, and a biochar kiln. The resultant biochars were fashioned into electrodes of coin-type supercapacitors and tested for their specific capacitance, cycling stability, and electrical conductivity. The gasifier demonstrated the best electrode material, with a median specific capacitance of 70.14 F/g, cycling stability of 97.37% after 250 cycles, and an internal resistance drop of 5.58 Ω (all tested at a 0.5 mA charging current). This is close to commercially available carbons (83.55 F/g, 98.99%, 9.3 Ω), and outperforms the kiln (40.79 F/g, 123.03%, 23.98 Ω) and distillation methods (20.57 F/g, 97.72%, 11.22 Ω). The gasifier also possessed high operating temperatures (>550℃), low setup costs (~$50), a mass yield of 18.84%, and user-friendly operation. Future work will optimize composition of the gasifier biochar, explore different wood species, and search for more sustainable chemical activation agents.   

Dual Detection of Kerker Anapoles in Dielectric Microspheres

It has been hypothesized that in the case of Mie scattering, the emergence of pure electric or magnetic scattering regimes at Kerker conditions under dipolar excitation can give rise to zero total scattering efficiency at the optical regime, known as Kerker anapole. To detect this, we illuminated spherical titanium dioxide (TiO­­₂) with an average size of ~ 1.1 microns using tightly focused Gaussian beams (TFGBs) that mimic the scattering properties of dipolar fields. We measured the scattering spectra of the single particles in both the forward and backward directions and found that there are several dips associated with the 1^st and 2^nd Kerker conditions. Moreover, the scattering minima of the backscattered spectra nearly coincide with the scattering minima of the forward scattering spectra under illumination TFGBs, which is a signature of Kerker anapole.   The detection of optical anapole can potentially overcome the limitations of current optical devices in terms of non-efficient coupling and directionality of light.   

Ionic liquid gate tunable diodes based on MoSe2/doped Si hetero-junctions

We present our results on the fabrication and electrical characterization of CVD grown monolayer MoSe₂/doped Si heterojunction diodes at room temperature. Ionic liquid (IL) gating of monolayer MoSe₂ when connected in a field-effect transistor configuration shows that the charge transport is ambipolar. This motivated us to test the operation of MoSe₂/doped Si diodes fabricated separately using p- and n-doped Si substrates in the presence of an IL. By applying a gate voltage to the IL we were able to tune the diode parameters (i.e. rectification ratio, turn-on voltage and ideality parameter). Notable differences in the current-voltage (I-V) curves were observed depending on the type of doped Si that was used. Varying the gate voltage resulted in the diode exhibiting non-linear rectifying characteristics in the first and third quadrant of the I-V plot for the MoSe₂/p-Si diode, while the MoSe₂/n-Si diode exhibited non-linear rectifying behavior only in the third quadrant of the I-V plot. Electrostatic current control at low voltages enhances the diode’s functionality, making it useful in other applications besides rectification.   

Poster: The Development of ZnO, Ultraviolet, All-Optical Switches

The pursuit of high-speed communication has driven the development of new optoelectronic components, such as all-optical, surface-normal, switches constructed of semiconductor thin-film heterostructures. ZnO is a promising material for switches that operate in the ultraviolet (UV) region. It has a bandgap of ~3.4 eV and is less toxic than other materials with similar bandgaps, such as GaN. The structures we are studying are composed of alternating layers of polycrystalline ZnO and Zn_0.9Mg_0.1O, where the ZnO serves as the active semiconductor layer. In these experiments, we measure the absorption changes as a function of the energy, polarization, repetition rate, and time delay of the control and signal pulses. Our experiments indicate that the switching action is produced when the conduction-band electrons and valence-band holes excited by the control separate due to a built-in electric field in the ZnO layers. The resulting space-charge field screens the built-in field, blue shifting the band edge by reducing the excitonic red shift associated with the quantum-confined Stark effect.  In our presentation, we will discuss how the carrier dynamics impact the switch’s speed.   

Combination of Gold Nanotriangle Arrays with MoSe2 Monolayers for Plasmon-Exciton Coupling

This study explores the synthesis and properties of hybrid plasmonic/2-dimensional semiconductor nanostructures by combining gold nanotriangle (NT) arrays with mechanically exfoliated MoSe₂ monolayers on a sapphire substrate. The MoSe₂ monolayers exhibit an exciton emission at 786 nm at room temperature. Using nanosphere lithography with polystyrene beads, an array of gold NTs is thermally deposited on top of these transition metal dichalcogenide (TMDC) monolayers. Characterization through Atomic Force Microscopy (AFM) and Scanning Electron Microscopy (SEM) determines the shape and height of the gold NTs. Transmission measurements are employed to investigate the shift of the plasmon resonance of the gold NT arrays as a function of the NT height and of the exciton transition in the combined MoSe₂ monolayer/gold NT samples. The experiments are accompanied by COMSOL simulations. This work paves the way for applications of plasmon-coupled TMDC nanostructures.   

Optical Properties of Hafnium Doped Gallium Oxide Thin Films

Gallium Oxide (Ga₂0₃), an ultra-wide-bandgap semiconductor, is a promising material for high power electronic devices and solar blind detectors [1,2]. However intrinsic Ga₂0₃ exhibits too large of a resistivity for device applications. To overcome this challenge, Hafnium (Hf) can be introduced as a n-type dopant, however current work has only focused on single crystal Hf: Ga₂0₃ [3,4]. 

In this work we present the optical properties of Hf: Ga₂0₃ thin films fabricated by RF reactive sputter deposition. Initial results show Hf incorporation increases the index of refraction of the material while minimally altering the band gap. 

Citations 

Developing gating devices for scanning tunneling microscope (STM)

Using a gating device compatible with scanning tunneling microscope (STM), we adjust the doping in our molecular-beam epitaxy (MBE) films through a back gate, and observe the change in local density of states with STM. To develop the gating device, we measure the dielectric breakdown of hBN-SiO₂ and Al₂O₃-SiO_2, and transfer high-quality graphene on the devices. The films are then grown on the devices with MBE and studied with STM. We show how the STM compatible gate-tunable devices are developed, how the materials are grown on the devices, and STM spectrums on gated materials.   

Molecular Dynamics Simulation of Photovoltaic Exciton Dissociation

The dynamics of exciton particles in photovoltaic systems plays a key role in determining the electrical efficiency of such systems. Excitons consist of electron-hole pairs that generate electric currents through dissociation, and a quantitative understanding of exciton dynamics is relevant to the design of efficient photovoltaics. This rate of dissociation is known to depend on the degree of orbital energy disorder prevailing over the molecular lattice of the photovoltaic, and this dependence has previously been investigated using kinetic Monte Carlo techniques that employ pre-assigned lattice site transition rate constants and static lattice sites.

In this study, we simulate this dissociation process using accelerated molecular dynamics (MD), which accommodates lattice vibrations and allows lattice site transitions based on particle dynamics. Treating the electron and hole as separate particles, we investigate the time-averaged separation between these particles over the course of multiple trial simulations and calculate their fractional dissociation yield. The energetic disorder of the lattice is varied and the corresponding fractional dissociation yield of the exciton is determined and compared with experimental results.   

Topological Magnons in the Bi-layer Honeycomb Ferromagnet

Over the last couple of years, magnetic systems have also been shown to host topological excitations. We explore the particular case of ferromagnet bi-layer honeycomb lattice which, when considering nearest- and next nearest-neighbor exchange interactions, Dzyaloshinskii-Moriya interaction, and easy-axis anisotropy, allows for topological magnons to arise [1]. We extend the Hamiltonian of Ref. [1] via the inclusion of extra interlayer interactions, in addition to various layers stack, i.e. A-B stacking or A-A stacking. We show this Hamiltonian hosts topological magnons that are controllable via the interlayer interactions. Most importantly, these new interactions provide a novel way to tailor and engineer different topological magnon frequency dispersion. Finally, we also calculate the magnon thermal Hall conductivity as a function of temperature and magnetic field.

[1] H. Kim and S. K. Kim, Phys. Rev. B 106, 104430 (2022)   

Crystalline and Magnetic Properties of Cr2MnAl

In recent years, Heusler alloys have attracted much attention in the scientific community because of their potential for application in the field of spintronics. This is due to their uncommon properties, such as half-metallicity and spin-gapless semiconductivity. We have synthesized one predicted half-metallic alloy, Cr₂MnAl, using methods of stoichiometric engineering, arc melting, and annealing at high temperatures. The as-prepared Cr₂MnAl alloy shows a cubic crystal structure with the A2 type disorder. The magnetic hysteresis curve recorded at 100°C from the as-prepared sample shows a small saturation magnetization of about 0.2 emu/g. We will also include the effect of doping Co, Fe, V, Ti in the Cr site followed by high temperature annealing in this presentation. Additionally, the results from our first principal calculations will also be presented.   

Small Satellite Applications: Insights from High-Altitude Balloon Experiments with Chip Scale Atomic Clocks

The proliferation of Low Earth Orbit (LEO) space applications for small satellites (smallsats) is rapidly expanding, encompassing a wide array of commercial, scientific, and defense payloads. These applications demand precision timing solutions with a focus on minimizing Size, Weight, and Power (SWaP) requirements. Our research focuses on the behavior of Chip Scale Atomic Clocks (CSACs) during High-Altitude Balloon (HAB) flights. This study involves launching CSACs in HAB payloads to measure time dilation errors at the nanosecond level, comparing the result to a ground based CSAC reference. The primary goal is to explore the Gravitational Time Dilation predicted by Einstein's Theory of General Relativity and develop a robust model for accurate time dilation measurement using data from HAB launches. We anticipate that the linear slope derived from these launches will enable time calculations within a 5-nanosecond margin of error. Once this model is established, it can be applied to location prediction software, serving as a reliable alternative to satellite-based navigation. Ultimately, our research aims to provide an alternative, GPS-quality navigation, and timing information signal to users in regions where global navigation satellite systems (GNSS) may be unavailable.   

Laser Ablation for Efficient Space Debris Removal

Space debris poses an escalating threat to safe and sustainable use of space. To tackle this problem, several strategies are being explored, including spacecraft design enhancements, mission program revisions, space traffic management, and active space debris removal. A promising approach for debris removal involves laser ablation, which employs laser-induced plasma techniques to adjust debris trajectories, facilitating safe re-entry into Earth's atmosphere for termination of debris or sending debris to graveyard orbits. This presentation will explore the use of nanosecond pulsed laser ablation (with fluence around 100 kJ/m^2 and a 6 ns pulse duration) to develop efficient methods for space debris removal. Furthermore, femtosecond pulsed laser ablation (with a 100 fs pulse duration) will be investigated for its unique directional plasma plume, enhancing control in debris removal. This research will address key challenges, including real-time tracking and targeting, and showcase the potential of ground-based laser targeting in space for debris removal.   

Integrated machine learning and laser spectral analysis of penny composition across the 20th century

Using Laser-Induced Breakdown Spectroscopy (LIBS) as an analytical tool coupled with a Nd:YAG 1064 laser, the presence of metals in circulated (1934-1958 & 2005-2014) and uncirculated mint-condition pennies (1970-2009) can be determined. When analyzing metal composition, excited metal atoms and ions (e.g. Cu) in LIBS spectra can be identified. Using Machine Learning (ML) algorithms, a set of atomic emission peaks were compiled to identify specific metals in sample pennies. Discrepancies between the metal content in empirical data and the theoretical values reported by the US Mint may indicate socioeconomic conditions of various historical eras. Integrating LIBS and ML, this research project recruits high school students for hands-on learning at the intersection of physics, chemistry, data science, history, and socioeconomics.     

Investigating the use of Chip Scale Atomic Clocks to account for Gravitational Time Dilation effects in diverse environments and their implementation in Small-Scale systems.

The objective of this research project is to explore the theoretical principles of gravitational time dilation as described by Einstein's Theory of General Relativity. The Theory of General Relativity stipulates that time advances slower when in the presence of stronger gravitational fields. This time dilation is minute and is often hard to detect and quantify as it requires precisely synchronized clocks and a period of measurement that allows for time drift to accumulate. By experimentally investigating the principles of gravitational time dilation as described by Einstein's Theory of General Relativity, and by gathering data from both satellite-based and ground-based Chip Scale Atomic Clocks (CSACs); this research aims to develop a reliable model based on gravitational potential and environmental influences that accurately accounts for gravitational time dilation in diverse scenarios. This research focuses on advancing the modeling and predictions of gravitational time dilation, a fundamental concept in General Relativity, through the application of CSACs and the integration of environmental data collection. This research field has the potential to significantly advance applications of timekeeping for ventures such as navigation and communication.   

Exploring Electronic Resonance Enhancement in 3-color Two-Beam Coherent Raman Scattering

We report a new application and extension of our formerly developed and characterized instrumentation and spectral processing methods of two-beam 3-color broadband coherent Raman methodology [1]. The procedure was applied for molecular vibrational measurements over the low-frequency spectral domain. It was recognized that the method could be used to measure high-quality phonon spectra of crystals, but the effects of electronic enhancement have not been investigated. We now present new low-frequency vibrational spectra of, e.g., beta-carotene measured under electronic resonance conditions. We developed the necessary signal-processing method for the observed spectra because altered lineshapes and polarization were detected. 

[1] L. Ujj, Contribution to the development of low frequency terahertz coherent Raman micro-spectroscopy and microscopy, Spectrochim. Acta - Part A Mol. Biomol.Spectrosc. (2018), https://doi.org/10.1016/j.saa.2018.03.033.   

Impact of Dopamine Agonist on Locomotion Pattern of Daphnia Magna

Daphnia Magna, a small freshwater planktonic crustacean, plays a crucial role in various ecological, toxicological, and pharmacological studies. They propel themselves through water using powerstroke motion, by periodically beating their antennae. Despite their significance, the description of Daphnia motion has primarily been qualitative or vaguely quantitative. Our study aims to offer a detailed granular-level analysis of Daphnia locomotion. We observed their free-swimming motion in a quasi-2D chamber as well as the motion of their antenna in a tethered state. The extracted positional, temporal, and orientation data using a deep learning software - SLEAP, helped us categorize different gaits of daphnia magna. To further study the impact of these gaits on the dynamics, speed, and efficiency of swimming, we treated these organisms with a dopamine receptor agonist. This drug is known to decrease the average swimming speed of the daphnids, however, the exact physical mechanism by which that happens remains unclear.  Our study aims to identify the features of the swimming gait that lead to the emergence of distinct mobility patterns that decrease their overall speed.   

Sparse identification of bacterial transcriptional regulation

In bacteria, the relationship between a gene's regulatory structure and its expression is well-understood for specific gene circuits. However, a comprehensive, genome-scale view of this relationship is lacking. A recent collaborative project from our lab used bacterial single-cell RNA sequencing (scRNA-seq) and single molecule fluorescence in situ hybridization (smFISH) to measure the genome-wide cell cycle pattern of Escherichia coli (E. coli) transcription (PMID: 37034646). While the transcriptional activities of many genes align with a null model where transcription rates simply mirror gene dosage (PMID: 26669443), some genes exhibit variations, such as shifts in timing or amplitude of expression. As a follow-up, we aim to use machine learning-aided methods to construct ordinary differential equation (ODE) models of transcription rates, which reveal regulatory mechanisms beyond the null model. After evaluating various algorithms, we have focused on the sparse identification of nonlinear dynamics (SINDy) algorithm (PMID: 27035946) because of its superior computational efficiency. We tested SINDy with simulated mRNA number data from ODE models that represent known mechanisms, such as transcriptional activation and repression, thus validating SINDy's capability to recognize basic biological patterns. Our current effort is to apply SINDy to genome-wide E. coli transcription data from our lab’s collaborative project. We will compare SINDy-inferred models with existing databases such as EcoCyc and RegulonDB to ascertain consistency with documented regulatory mechanisms and evaluate their predictive power for unidentified mechanisms. Our attempt will serve as a starting point for learning more complicated transcriptional regulation models using data-driven methods.   

Mathematical Modeling of C. elegans’ Thermotaxis

C. elegans is a free-living worm inhabiting temperate environments across the Earth. They contain various features that are imperative in human biology, including temperature sensing. This work aims to improve understanding of the underlying mechanisms of these temperature responses. We incorporate temperature features into a set of differential equations to create a mathematical representation of C. elegans AFD neurons. The animal uses its memory of the cultivation temperature to perform migration behavior in temperature gradients. Our computational results show how a phenomenological mathematical model can replicate the calcium dynamics of a real AFD neuron during temperature experiments. Using color maps in Arrhenius-based parameter space, we study how our model neuron responds to temperature variations. The findings suggest that intracellular activity observed in response to such changes may be caused by oscillating inputs to CNG ion channels in the dendrite. This proposes a methodology for predicting the calcium response of AFD neurons in C. elegans in different temperatures by utilizing a dynamical mechanism and without requiring physiological details.   

Decoding Destabilization: Investigating the Mechanisms by Which Disruption of the RAD51:RAD51 Interface Affects RAD51 Nucleoprotein Filament Integrity and Function

Homologous recombination is a DNA repair technique in which nucleoprotein RAD51 facilitates strand exchange between the broken double-stranded DNA and a homologous strand. RAD51, with assistance from mediators, forms nucleoprotein filaments on single-stranded DNA overhangs produced after a double-stranded break. Mutations in the RAD51 interface can have negative effects on the stability of the nucleoprotein filament. Using FRET and mass photometry this study examines the effect of mutations on essential RAD51 functions   

A stochastic three-state model on a Cayley tree and its potential applications to nanomedicine

We present a three-state cooperative sequential adsorption and evaporation model on a Cayley tree with constant and variable attachment and detachment rates and discuss its possible applications for drug encapsulation of two types of nanoparticles on tree-like synthetic polymers called dendrimers. The geometry of a dendrimer is described mathematically as a Cayley tree. We present analytical and Monte Carlo simulation results and calculate a variety of quantities such as time-dependent particle densities and time-dependent probabilities of certain particle configurations relevant to dendrimer dynamics.   

Biophysics Comes to Highschool: Developing a Low-Cost Method for Measuring the Force of a Laser Tweezer Trap

Optical tweezers are a Nobel Prize winning technology with interdisciplinary applications including studies in the structure of DNA and molecular biology. We are developing a low-cost optical tweezing apparatus in order to study biomolecules, including the forces required to break damaged and undamaged DNA. Our long term goal is to utilize optical tweezing in order to trap large biomolecules for spectral analysis using Laser-Induced Breakdown Spectroscopy (LIBS). This project is a part of the PLAIDX collaboration, a group focused on giving high school students and underserved undergraduate students access to original biophysics research. By successfully implementing a cost-effective and reliable Quadrant Photo-Diode (QPD) in a HeNe optical tweezing system, we establish an innovative approach for high school-level biophysics research. This hands-on experience introduces students to advanced scientific concepts and the process of scientific collaboration.   

Single Photon Vision: A Quantum Optics Lens on the Human Eye.

Can we see a single photon? Rod photoreceptor cells are known to respond to this infinitesimal stimulus but whether it persists through neural circuits to elicit conscious perception is a question yet unanswered. While previous studies have been firmly rooted in the classical realm and plagued by observer bias, we harness a true heralded single-photon source to probe the visual system. The heralded photon is generated with Type II spontaneous parametric down-conversion (SPDC) at 505 nm, the peak wavelength of the rod’s spectral sensitivity, and is channeled toward a trained observer in our two-alternative forced-choice experimental design. This procedure minimizes false positive results in both observer and detector by arbitrarily choosing the direction of emanation and including trials without a photon entirely. The subject answers where they ‘saw’ the photon each time and statistically significant correct identification of the photon’s location suggests single-photon sensitivity in the observer. If we can consciously perceive one photon, cascading questions ask the precise location of wavefunction-collapse in the visual system, potentially tackled by sending superposition states of light to the eye, and the possibility of human observers acting in novel tests of nonlocality, reconciling quantum mechanics and human perception.   

The Mechanics of Invading Tumor Spheroids in Aligned Extra Cellular Matrix

Breast cancer is the second most prevalent cancer, and some associated genetic risks involve the nature of the fiber structure of the surrounding breast tissue. Solid tumors are known to remodel the alignment and mechanics of their local extracellular matrix (ECM). Tumor cells use local radially aligned fibers as highways to aid in more efficient invasion, while tangential fibers act as a barrier inhibiting invasion. During the invasion process, the tumor and invading cells strongly interact with the ECM, causing realignment of the fibers. By using spheroids embedded in type 1 collagen gels with varying alignments, we can explore how some genetic traits are better at fighting breast cancer than others. In our research, we find that both the invasion profiles and morphodynamics of the spheroids are highly dependent on the alignment of the ECM.   

Measuring the Localized Physical Properties of A. nidulans Using Atomic Force Microscopy

Mycelial Materials, materials composed of fungi, have been produced with a variety of mechanical properties allowing them to be tailored for specific applications. One clear advantage of these materials is their biodegradability and potential to reduce environmental impacts. The properties of the bulk mycelial material depend significantly on the properties of the individual fungal hyphae. In this work, the localized physical properties measurements of Aspergillus nidulans using Atomic Force Microscopy techniques were measured. Elastic Modulus and adhesion properties were correlated with fungal hyphae topography on a control strain and compared with those of genetically modified mutant strains. The application of this data to optimizing the properties of bulk materials will be discussed.   

Effects of DNA-Wrapped Single Walled Carbon Nanotubes on Cell Viability and Proliferation, In Immortalized and Native Murine Cells

Neurodegenerative diseases result in the gradual and progressive loss of neural cells, affecting millions of people worldwide. In the brain, the process by which new neurons form is called neurogenesis. To harness the potential of neural stem cells in influencing cellular behavior and differentiation, a deeper understanding of the external factors that modulate their proliferation is needed. The goal of this research is to study the interaction between single-walled carbon nanotubes (SWCNTs) in two different biological test beds: C17.2 cells, which are a murine neural progenitor cell line, and cells of the dentate gyrus of living murine organotypic brain slices. Using these two test beds, we conduct controlled experiments evaluating the effects of escalating doses of SWCNTs on cell viability and proliferation, as well as on SWCNT deposition using single-cell analysis. These experiments establish a comprehensive dose-response relationship, providing the threshold at which SWCNTs begin to exert detrimental effects in both immortalized and native cells.   

Atomic Force Microscopy Studies of Cancer Cells

The Atomic Force Microscope (AFM) is a powerful technique to measure both topographical images and physical properties of materials. This instrument has proven to be valuable in many areas of biophysics research. In particular, the AFM has provided useful information on many properties of human cells. In this study, topography data from the AFM is correlated with optical, fluorescence, and magnetic microscopy data to characterize healthy and cancerous cells. This information could lead to novel methods of treating cancer cells.   

Influence of Static Magnetic Field Orientation on HT22 Neural Cell Behavior

Magnetotherapy has the capacity to become a valuable tool in the biomedical field due to its minimally invasive therapeutic potential. Nevertheless, there are numerous unresolved questions surrounding the effects of static magnetic fields on neural structure and growth. In our study, we investigate the effects of manipulating the orientation of a 1mT static magnetic field on HT22 neural cells. Our research endeavors to evaluate the influence of factors such as the duration and orientation of the magnetic field on proliferation, viability, and structure of the cells. By delving into these interactions, we strive to provide insights that contribute to a more comprehensive understanding of magnetotherapy's potential role in the field of neural biology.   

Poster: Modeling Open Quantum Systems Using QuTiP

To study the nonidealities we need to consider the open quantum system which is widely modeled with the Lindblad Master Equation. However, solving these equations may pose problems due to the increased complexity of the system dynamics. This solution can be found using a Python library known as QuTiP which has been built as a computationally viable tool that numerically solves the dynamics of both closed and open quantum systems. For example, the Jaynes-Cummings model is a description of how light interacts with matter within an optical cavity. Using QuTiP we have modeled the amplitude decay of the system due to different nonidealities (i.e., spontaneous emission and cavity leakage). We then compared our model against experimental trends and noticed a significant match to observed amplitude decay loss.   

Quantum-Dot-Based Single-Photon Detection with Solid-Immersion-Lens Integration

Quantum-dot, optically gated, field-effect transistors (QDOGFETs) have been shown to exhibit photon-number-resolving capabilities and are promising devices for future quantum networks; however, with their mm-sized active areas, it has proven difficult to efficiently couple light into them. Here, we demonstrate how a high-index, cubic zirconia, solid-immersion lens (SIL) can be used to improve the free-space coupling of light into QDOGFET single-photon detectors. Wewill show how SIL-integration can be used to reduce the loss associated with photons missing the active area of the QDOGFET and how it can be used to direct the photons to the quantum dots that exhibit the largest and most uniform responses. While the former improves the overall detection efficiency of the system, the latter ensures that the detector is operating with its optimal sensitivity and photon-number resolution. Our presentation will include the results of measurements where statistical analysis of the detected photons is employed to evaluate the performance of SIL-capped detectors and to produce the response maps that we use to identify the optical seed point of photons.   

Plasma-Enhanced Atomic Layer Deposition of Superconducting TiN films

To reduce dependency on error correction in quantum computation, this study aims to investigate the decoherence that originates from the impurities within the superconducting qubit material itself, specifically Titanium Nitride (TiN). Since TiN is attractive for its long coherence times and plasma-enhanced atomic layer deposition (PEALD) provides incomparable homogeneity and thickness control, optimizing PEALD TiN film fabrication for higher superconducting transition temperature Tc, lower impurity concentration, and increased crystallinity is crucial to making replicable and reliable qubits. This begins with tuning the fabrication parameters, such as titanium precursor pulse time and post deposition cooling time, across varying film thicknesses, then placing those films inside a cooled dilution fridge and recording their Tc and other electrical properties. In this work, we present our experimental study of PEALD TiN film where the parameters mentioned above were analyzed for increased film quality. We also show the measurement results of testing TiN films of various thicknesses in the dilution fridge and their corresponding Tc values. Furthermore, we recorded how the effects of the fabrication parameter variations manifested in different characterization tools across different film thicknesses, from spectroscopic ellipsometry (Woollam) to X-ray diffraction analysis (XRD).   

Characterization of Nanoscale Superconducting Quantum Interference Devices in a Top-Loading Cryogen-Free 4 K Refrigerator

The imaging of magnetic structure at the nanoscale is a prominent need across many scientific disciplines. Superconducting quantum interference devices (SQUIDs) offer a minimally invasive and highly direct measurement of magnetic properties as compared with other methods of detection; however, conventional, lithographically-produced SQUIDs are not well suited for imaging magnetic structure at the nanoscale. The SQUID on tip (SOT) is a type of nanoSQUID that addresses this issue. The small size of SOTs and their close proximity to the sample yields high local magnetic sensitivity with nanoscale spatial resolution. Using custom-designed inserts for a top-loading cryogen-free 4 K refrigerator, this project characterizes SOTs for use in such a scanning SQUID microscope platform. The insert design features a two-stage configuration comprising an SOT and a SQUID series array amplifier with auxiliary instrumentation such as thermometry. Moreover, the insert uses a regulated amount of helium as a thermal exchange gas. Additionally, the insert incorporates a 0.5 Tesla magnet, with careful consideration given to the associated heat load. The project also examines strategies to minimize vibrational and electrical interference arising from the refrigerator pulse-tube cryocooler.   

Parametric Energy Transfer Between Microwave Resonators

The project is motivated by an experiment on superconducting resonators with voltage-controlled frequency and nonlinearity. Devices utilizing this technology allow for dynamic tunability in superconducting quantum circuits. By improving the energy transfer between these resonators, the efficiency of the circuits can increase. In this work, the exchange of energy was studied in a simulation of two parametrically driven oscillators described in terms of the experimental circuit's parameters. An improved transfer of energy was achieved through the adjustment of various circuit parameters and the introduction of a modification to the driving frequency. The optimal modification was chosen for various resonators' frequencies, coupling strengths, and amplitudes of parametric modulation. These results are predicted to improve the efficiency of the device used in the experiment with superconducting resonators.   

A Quantum Computing Algorithm for an Ising Model in One and Two Dimensions

We present a quantum computing algorithm designed to model and analyze the Ising model in one and two dimensions in an external magnetic field. The goal of this project is to introduce students at the undergraduate level to the emerging field of quantum computing via a well-studied statistical physics model, the Ising model. We compare the standard Metropolis algorithm to the quantum algorithm implemented in Qiskit and address the advantages of quantum computing in studying statistical physics models. We present results for the relevant quantities such as magnetization, susceptibility, and critical temperature of the system.   

A Hands-on Cryogenics Training Module for Quantum Engineering Students: Evaluating Superconductivity in Thin Film Materials

Superconducting materials play a pivotal role in the field of quantum information science and engineering by virtue of their unique ability to conduct electricity with zero resistance at extremely low temperatures. The critical temperature, at which a material enters the superconducting state, is a crucial parameter, often occurring at temperatures near millikelvin. In this study, we investigated various materials exhibiting superconducting properties in different cryogenic environments. Our initial examination focused on the analysis of the magnetic field generated by superconducting Yttrium barium copper oxide (YBCO) within a cooled bath at 77 K, utilizing an open-cycle liquid nitrogen cryocooler. Subsequently, we expanded our research to explore the superconducting properties of materials including Bismuth strontium calcium copper oxide (BSCCO) and niobium using closed-cycle Gifford-McMahon cryocoolers. The goal of this comprehensive study was to elucidate the advantages of these materials in the development of quantum devices. Additionally, our investigation incorporated both automation and hands-on training to gain practical experience in the realm of quantum devices. These efforts contribute to the ongoing work of leveraging superconducting materials and cryogenic environments to advance QISE education, thereby paving the way for the next generation of the quantum workforce.   

Raman Noise Measurement in Periodically Poled Lithium Niobate at Telecommunication Wavelengths

Frequency up-conversion is important for long-distance quantum communication where transmitted photons need to be at telecommunication wavelengths to minimize loss in optical fibers, but sources, memories and detectors may be optimized at other wavelengths. However, Raman noise can be problematic in frequency up-conversion processes since it introduces unwanted noise that can degrade the quality of the up-converted signal. Such Raman noise can reduce the signal-to-noise ratio (SNR), and cause efficiency loss in the up-converted signal. We measure the Raman noise spectrum in periodically poled lithium niobate (PPLN) using a pump at 1590, 1595, and 1600 nm. Anti-stokes Raman peaks were observed between 1553 nm and 1563 nm. The results show that a frequency conversion pump set at 1595 nm produces minimal Raman noise at a 1550 nm signal, so that a quantum signal at 1550 nm could be converted to 786 nm while achieving a high SNR.   

Enhanced Purification Protocol for Entangled Systems

Due to the unpredictable and delicate nature of quantum states, the quantum systems need processes to remove error and purify corrupted quantum bits. Purification protocols can reduce error and prevent corrupted states from multiplying in such systems.The primary errors come from corruption of the state whether through phase transitions or bit flips. By accounting for the various errors, different methods can be used to detect errors and increase the trustworthiness of a system. Two of these methods are used in tandem to create a purification protocol that can detect the majority of errors that can result in corruption of a system while minimizing the use of quantum resources.   

Accelerating Diffusion Models in Particle Physics

Our research investigates the optimization of sampling techniques applied to particle physics datasets, focusing on numerical methods and comprehensive data analysis. The unique challenges encompassed by particle physics data, such as continuous coordinates, stochastic dimensionality, and permutation invariance, distinguish it from stan- dard datasets. The prevalent deep generative models, mainly designed for image data, fall short for these datasets. Our approach centers on a novel neural network simulation called Fast Point Cloud Diffusion (FPCD). The core aim is to boost the efficiency and speed of diffusion models, assessed via minimized Wasserstein Distances between authentic and generated data distributions and reduced sampling time.  We propose a stochastic differential equation solver implementing Euler-Maruyama scheme with predictor-corrector method, resulting in an 8.4x acceleration in performance compared to the baseline ODE solver from the SciPy library. The research uses resources of National Energy Research Scientific Computing Center, , a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy".   

Investigating Correlations Between the Microstructures of Different Wood Species and their Performances as Supercapacitor Electrodes

Supercapacitors typically rely on activated carbon derived from nonrenewable sources, but biochar derived activated carbon serves as a renewable alternative. Future research demands more information about the performance of different biomasses as activated carbon. This study explores the performance of biochars derived from Boxelder, Buckthorn, Bur Oak, and Green Ash. Wood samples were pyrolyzed with a Top-Lit Updraft Gasifier before undergoing KOH chemical activation in a tube furnace. Activated carbon was then used as supercapacitor electrodes. The supercapacitors were tested and analyzed for their specific capacitance, cycling stability, and internal resistance. Bur Oak supercapacitors have achieved excellent results reaching a specific capacitance of 105.6 F/g, and a cycling stability of 98.59% over 250 cycles all at 0.5mA. Compared to supercapacitors made from commercially available activated carbon reaching a specific capacitance of 102.0 F/g, cycling stability of 94.17%, as well as qualitatively determining that wood biochar supercapacitors achieved a lower internal resistance, it is apparent that wood biochars can outperform commercial activated carbon. This study will assess the performance of biochars derived from the four wood species and provide insight into correlations between wood microstructures and their applications for supercapacitor electrodes.   

Thermomagnetic Oscillators with FeRh

The thermomagnetic properties of iron-rhodium (FeRh) make it a suitable candidate for neuromorphic computing. FeRh undergoes a phase transition between 300 K and 400 K from an antiferromagnetic state with high resistivity at low temperature to a ferromagnetic state with low resistivity at high temperature. This unique characteristic enables the potential for FeRh to serve as a resistivity auto-oscillator in the development of energy-efficient computational systems that mimic the brain’s computing power. With a constant applied current through FeRh in its antiferromagnetic phase, FeRh heats up due to its high resistivity transitioning to its ferromagnetic phase, where the low resistivity causes it to cool down again to its antiferromagnetic phase. This may lead to auto-oscillations between the two phases and resistivity states. Our objective is to reduce the transition region to enhance energy efficiency by requiring a smaller current. To investigate FeRh’s potential for such an oscillator, thin films with varying Fe and fixed Rh sputtering powers were grown using sputter deposition from a pure Fe and pure Rh target onto a pre-annealed MgO substrate followed by post-annealing. Film thickness and deposition rates were determined using X-ray reflectivity (XRR). The magnetic response of the films was analyzed using a Magnetic Property Measurement System (MPMS), while resistivity measurements were performed using a Physical Property Measurement System (PPMS) and a vector magnet equipped with a cryostat, allowing a wide temperature range down to 3 K and up to 400 K. Composition dependence was explored by adjusting individual gun power. Films grown with Fe gun power ranging from 24–30 W exhibited the phase transition in both magnetometry and resistivity measurements. Films with 27 W Fe and 10 W Rh powers displayed the most promising phase transition, characterized by its small transition temperature range. Ongoing efforts aim to shift the transition to lower temperatures, with the ultimate goal of achieving thermomagnetic auto-oscillations of FeRh under a constant applied current.

This work was supported by NSF through the Illinois MRSEC (DMR-1720633) and DOE as part of the Q-MEEN-C EFRC (DESC0019273).   

Multidisciplinary REU site at Cleveland State University: Synthesis, Assembly, and Characterization of Soft Matter

Cleveland State University’s NSF sponsored REU site on Synthesis, Assembly and Characterization of Soft Matter Systems is in the second 3-year period. Housed in the physics department but including faculty collaborating in Physics, Chemical & Biomedical Engineering, Math and collaborators at Case Western Reserve University the faculty and students collaboratively study the unique properties and applications of soft matter materials. The objective of our Soft Matter REU site is to involve undergraduate physics and engineering majors in meaningful interdisciplinary research projects within soft matter science and engineering. A primary focus of our site is to encourage students to continue in STEM fields as either graduate students or workforce members. CSU’s focus on Engaged Learning has cultivated a strong culture of support for undergraduate research, and REU participants benefit from this culture. Students receive one-on-one mentoring from experienced faculty and participate in a variety of professional development opportunities. The culture of collaborative multidisciplinary research at CSU would provide students with a unique perspective of working among peers and faculty from different academic disciplines. This poster will give an overview of the student research accomplishments and experiences from its first REU cycle as well as describe the projects and application process for the new funding cycle.   

Developing a Plotting Tool to Study the Higgs Boson Production mode ttHH with the ATLAS Detector at CERN

At CERN, analysis of particle statistics can be very repetitive and time consuming. It is important that analysis groups spend time making programs readable and easily reconfigurable. I developed a plotting tool in C++ using the ROOT plotting framework, in order to cut down on repetitive tasks for my analysis group within the ATLAS collaboration at CERN. With the use of a JSON parsing library in C++, we configure plots seperately from the plotting program, in a JSON configuration file. This allows for researchers to configure plot data and styles without the need to recompile our program. This research project helps minimize the time consuming element of plotting kinematic and multiplicity data so that physicists can spend more of their time doing the important statistical analysis of di-Higgs events.   

Employing Computational Fluid Dynamics in Undergraduate Research

Undergraduate research is an important pathway for students to experience investigating a problem in-depth and gain valuable insight into career prospects. Mechanical engineering undergraduates often solve design-driven problems but do not investigate research-driven problems. They also typically can take computational fluid dynamics (CFD) as an elective course towards the end of their bachelor’s degree which affords an opportunity to expose undergraduate mechanical engineering students to applied CFD research. Towards that end, a project was scaffolded to investigate the feasibility of using complex CFD tools for a simulation of a drop impacting a porous substrate. This system was recently analytically solved and allows for a comparison with numerical results. The principal lesson learned was that in order to facilitate undergraduate research in CFD, a carefully selected scope needs to be rigidly defined, otherwise there’s a risk of a convoluted research project not accessible to an undergraduate mechanical engineering student. This carefully structured research project is possible to complete if the student is motivated in learning numerical methods and an application of fluid mechanics. Lessons learned will be presented and future improvements discussed.   

Towards Non-equilibrium Field Theories

In our study, we emphasized that index theorems are written in terms of characteristic classes. These characteristic classes describe the topology of the model under consideration. Through an examination of supersymmetric/topological path integrals, we aimed to understand the emergence of these topological properties from a path integral framework. This, in turn, offers insights into the manifestation of topological quantities in non-equilibrium cases.

We began by calculating interactions between positive and negative branes on the Schwinger-Keldysh contour. Subsequently, we integrated the Keldysh rotation into these calculations and explored a new form of the Schwinger-Keldysh contour. Then we tried to solve the problem by investigating Witten's iε prescription. And, finally, we settled on approaching the problem by first solving problems in the index theorem and from supersymmetric worldline path integrals.    

A Comparison of Vendor and Mayo-Designed AIR Coil Arrays for Prostate MRI

Accelerated Prostate MRI is an effective way to diagnose and localize prostate cancer clinically. However, the quality of the image is highly dependent on the layout of RF coils used for signal reception. This work aims to evaluate the anterior blanket coil and in-table posterior coil arrays (vendor-provided, GE Healthcare) and new Mayo-developed coil arrays (Mayo arrays).  Both array combinations are based on AIR^TM coil technology ^[1].  The Mayo coil is based on high element overlap, allowed by the low mutual inductance of the elements.  We compared the arrays in terms of noise correlation and geometry factor (g-factor) using MR images of a humanoid pelvic phantom.  Under an IRB-approved protocol, we further evaluated these two quantitative factors as well as the visual quality in images of human subjects.  We found that the Mayo-designed AIR coil array provides improved performance versus the GE array.   

Multiphysics Simulation of Thermoelectric Material (Fe2V0.8W0.2Al)

Thermoelectric materials hold immense promise for sustainable energy generation by directly converting heat directly into electricity. Among these materials, the Heusler alloy Fe2V0.8W0.2Al stands out due to its exceptional thermoelectric properties. In this study, we employ Multiphysics simulations to delve into the intricate behavior of Fe2V0.8W0.2Al as a thermoelectric material.

COMSOL Multiphysics is comprehensive simulation software. It allows calculations of electrical and thermal profiles in different geometries with temperature dependent material properties. Our Multiphysics approach encompasses electrical, and thermal, accounting for the alloy’s complex crystal structure. We use COMSOL to find out the temperature distribution in Fe2V0.8W0.2Al sample. The Simulation results of other properties of Fe2V0.8W0.2Al will be presented.   

Data Analysis of Stellar Spectra Using Fourier Analysis and Wavelet Analysis

Analyzing the periodic and localized data of the light intensity of stars recorded by Kepler Space Telescope can tell us a lot about the physics within the stars. In order to study the periodic and localized features of the intensities, Fourier analysis and Wavelet analysis are used. Fourier analysis is used to analyze the periodic features of the light spectrum, and can decompose the signal into amplitude and frequency. Wavelet analysis is able to analyze both the periodic features and the localized features of these signals. Wavelet In this project we have studied the spectra of several stars and the results are presented here.    

Studying Quantum Kinetics With Neutrinos in the Early Universe

The evolution of particles in a dense system is influenced by two competing effects: quantum coherence which builds up quantum phase and the kinetic destruction of this phase through inelastic scattering. One example of this quantum kinetic behavior is the evolution of neutrino states in the hot and dense early universe. Neutrinos oscillate because, fundamentally, their interaction states are incompatible with their energy eigenstates. In the early universe, large distributions of neutrinos and anti-neutrinos non-linearly affect both the coherent and scattering-induced decoherent evolution of neutrino states. In this poster, we look to explore and characterize the properties of this quantum kinetic behavior.   

Neutron and Gamma Shielding Capabilities of Li and Na Borate Glasses

Glass is an increasingly popular candidate material for uses in radiation shielding in a variety of settings, including spacecraft design and medical environments. This study investigates the shielding properties of various glass samples produced in house at Coe College. The glasses were several sodium and lithium doped borate glasses with composition XNa2O-B2O3 and XLi2O-B2O3 (X = 0.2, 0.3, 0.4) as well as 0.6Na2O-SiO2 and 0.6LI2O-SiO2. GATE, a geant4 extension, was used to simulate photon energies from 10 keV to 20 MeV. Additionally, neutron simulations were run from 2 to 12 MeV. Unfortunately, simulation restrictions prevented accurate thermal neutron simulations from being run. In addition, mass attenuation coefficients (MAC), half value layer (HVL), tenth value layer (TVL), mean free path, and fast neutron removal cross section are reported.   

Development of Microprocessor Based Physics Lab System for Undergraduate and K-12 Education

The goal of this project is to utilize low-cost microprocessors as brains in educational lab setups. These brains (in our case a Wrover ESP32 chip) can be used to acquire data in a lab activity, and then communicate this data through Wi-Fi back to a host-device. We are developing a set of experiments so that the system can be used in a modular fashion with various i2c based devices. The system is open source so that individual users can also develop their own protocols if desired. The first step of this project was to create a prototype device using a six axis gyroscope/accelerometer. Motion information is read by the local microprocessor and transmitted to a host device. Locally, a small screen mounted on the microprocessor can be used to display information in real time, max/min data, or be set to display information in graphical format. In this setup, one can implement the device for use in experiments using carts, collisions, or even to monitor aerial experiments such as catapults or egg drops. We will test the system in various classroom environments to ascertain lerning effectiveness as compared to traditional lab setups. Hopefully, we can develop a set of modular labs that can be integrated into education systems at a low-cost to enable advanced labs to be fully accessible to all, even on a small budget.

Thanks,

Logan Ingraham   

Exploring Band Structure Effects in Transition Metal Oxides for Electrocatalytic Nitrite Reduction

The electrocatalytic reduction of nitrite (NO₂^–) to nitrogen gas (N₂) is of significant environmental and industrial importance. This study investigates the catalytic effectiveness of transition metal oxides, particularly spinels with diverse band structures in their oxygen 2p orbitals, as potential catalysts for nitrite reduction. Our research aims to establishing correlations between band center positions, thermodynamics, and kinetics in the nitrite reduction reaction by manipulating band structure of the oxygen 2p orbitals. Inspired by linear free energy scaling relationships, we explore how changes in the band center position of the oxygen 2p orbitals influence the strength of the nitrite-catalyst bond, thereby impacting thermodynamics and activation energy. Such insights have implications for the development of cost-effective and efficient electrocatalysts for denitrification. Guided by the affinity of transition metal centers for oxygen bonding and inspired by copper nitrite reductases, we investigate transition metal oxides as catalysts, providing a novel perspective on catalysis relevant to various element-oxygen bond reactions. In our investigation, we employ Density Functional Theory (DFT) calculations to establish the relationship between the binding energy and the band center positions in the oxygen 2p orbitals. This computational approach sheds light on how variations in the band structure of oxygen 2p orbitals can impact the catalytic performance of transition metal oxide catalysts. A comprehensive experimental approach involves synthesizing specific spinel catalysts (CoFe₂O₄, NiCo₂O₄, Mn₃O₄, LiMn₂O₄, and Co₃O₄) through advanced nanoparticle techniques, followed by rigorous characterization. Subsequent electrochemical testing assesses their efficiency in nitrite electroreduction. This research strives to unveil the intricate relationship between the properties of these spinel catalysts, particularly the band center position of the oxygen 2p orbitals, and their catalytic performance in nitrite reduction. This has implications for developing more cost-effective and efficient electrocatalysts for denitrification, supported by DFT calculations that highlight the connection between binding energy and the oxygen 2p band structure.   

Accuracy and Efficiency of Integration Methods for Modeling Reactions

The computational expense that comes with simulating complex astrophysical reacting flows is challenging. Reactions are stiff, and we typically model these systems using implicit integration methods. These methods require a Jacobian matrix, J = ∂f/∂y', to be calculated and stored at each time step, along with linear algebra operations, all of which are computationally expensive. This expense motivates exploring more economical explicit methods that do not store the Jacobian. The goal of this study is to investigate how accurate and efficient the explicit Runge-Kutta-Chebyshev (RKC) method is compared to the implicit VODE method applied to astrophysical reactive flows. These integrators are applied to simulate X-ray bursts arising from unstable thermonuclear burning of accreted fuel on the surface of neutron stars, and to the double detonation sub-Chandrasekhar model for Type Ia supernovae, occurring when a carbon-oxygen white dwarf accumulates sufficient helium to ignite at the surface. The code framework for these problems is contained within CASTRO and are ran at the NERSC Perlmutter supercomputer. The node hours used and the mass fractions of elements show the explicit RKC method outperforms the current implicit VODE method in this application. However, there is no noticeable difference when applied to detonations.   

Measurement of Proton's Energy Loss Through Thin Gold Film

The National Institute of Standards and Technology (NIST) aims to reduce the systematic uncertainties of the energy spectrum in the neutron's lifetime experiment, but the presence of any "dead" layer inside the detector affects the energy spectrum of low-energy ions. In order to take this factor into account, we conducted this experiment to determine energy loss spectra of proton beam within the Gold dead layer and compare this spectra with the Stopping Power (SP) of Gold from the NIST's database. To that end, we generated 50-200 keV energy proton beam in Gettysburg College's 200 keV Van de Graff proton accelerator and collected the proton counts received by the detector, containing Gold layer, for different corresponding energy channels using energy spectra measuring software. As a result, we had to evaporate gold onto different batches of circular glass slides, and Si detector within the Gold Evaporator chamber and determined the thickness of gold layers by utilizing UV-Vis Spectroscopy technology, and AFM Technology. Employing these data, we plotted SP of the Gold dead layer versus the kinetic energy of the proton beam using the thickness function of the Gold and differentiated this plot with the graph of SP of Gold collected from the NIST database.   

Adapting A Generalist, Automated ALFALFA Baryonic Tully-Fisher Relation for use with Green Bank Telescope Observational Data

The Baryonic Tully-Fisher Relation (BTFR, McGaugh et al. 2000) describes a proportional relationship between the total mass of a galaxy and its rotational velocity. Since 2021, the Undergraduate ALFALFA Team (UAT) has worked to derive a minimal scatter BTFR from neutral hydrogen (HI) observations of galaxies with known distances using automated determinations of redshift, rotational velocity, and HI mass.  Our observing project, GBT 22A-430, is providing spectra from 220 galaxies hosting supernovae widely distributed across the sky. Another group associated with the UAT has developed a Python-based method of constructing the BTFR to improve our understanding of galaxies in the ALFALFA survey (Haynes et al. 2018) presented in Ball et al. 2023.  A proper BTFR provides refined estimations of parameters such as mass, rotational velocity, and, indirectly, galaxy distance. This work has the additional potential to be adapted for use with other HI-rich galaxy samples in the local universe e.g., the Arecibo Pisces-Perseus Supercluster Survey (APPSS, O'Donoghue et al. 2019).  We aim to adapt Ball et al. 2023’s analysis methodology for use with the GBT 22A-430 sample, utilizing GBTIDL, a Green Bank proprietary IDL-based data reduction software, and UAT-developed, pyAPPSS, a Python-based data reduction script for use with APPSS galaxies. We investigate the resultant BTFR and its implications regarding sample galaxies’ characteristics.   

Nitinol Interatomic Potential Using Moment Tensor Potentials in Machine Learning

In this study we developed an interatomic potential for the metal compound Nitinol using moment tensor potentials (MTP) by employing machine learning. The traditional way of determining interatomic forces is through quantum mechanics, which often requires a high computing cost and time. MTP has been shown to efficiently generate interatomic potentials for a wide variety of metallic systems. Although a Deep Learning potential for Nitinol has already been reported, it often requires high GPU and processing costs. Using MTP would allow for an affordable alternative potential that closely resembles the efficacy of Deep Learning Neural Network potential. The results presented were found using MTP codes run on a local AI workstation at Missouri State University (MSU). By optimizing the hyperparameters, errors in the interatomic potential were reduced dramatically approaching over 90 percent accuracy. We also demonstrated the benefit in utilizing the active learning algorithm to further enhance its accuracy. The computational works were performed at NERSC at National Lawrence Berkeley Laboratory and MSU's AI workstation. The support from NASA-Missouri Space Grant Consortium is acknowledged.   

Development of Instructional Physics Simulations for Classical Mechanics

We have developed two new physics simulations with learning objectives to address the lack of accessible and satisfactory educational tools for students. Our design process involved researching pre-existing web-based physics simulations and identifying gaps in learning devices for specific physics concepts. Our simulations are coded in JavaScript using the THREE.js library tocreate a 3D interactive environment with orbit controls. The animated frames are optimized for mainstream desktop internet browsers, with future testing aimed at expanding usability to mobile devices. We are currently revising one of the simulations to include an accessible, simplified, and immersive user interface for new learners. The first simulation explores the conservation of angular momentum and how angular velocity changes with factors that vary the moment of inertia caused by internal forces. The second simulation embodies crucial orbital mechanics concepts, such as Kepler's Second Law, conservation of total angular momentum and mechanical energy, and impulsive orbital maneuvers. Our long-term goal is to determine the impact of the simulations on understanding and engagement with the targeted concepts in undergraduate classrooms.   

Noise Detection Using Generative Adversarial Networks with Applications to High Energy Physics

In this project, we investigate the application of Generative Adversarial Networks (GANs) in signal processing to detect noise within large datasets, with a specific focus on their application to data processing for the Compact Muon Solenoid (CMS) experiment at CERN. GANs are employed to generate realistic signal representations and effectively distinguish between noise and true signals. We explore various GAN variants and data preprocessing techniques to optimize noise detection. The research showcases GANs' potential to enhance data reliability in high-energy physics experiments like CMS, contributing to improved particle physics analysis and discovery potential.   

Comparisons of the Seismic Properties of the Sun During Solar Cycles 23, 24, 25

A notable decline in solar activity was observed during Solar Cycle 24, prompting an investigation into its seismic properties compared to Cycle 23. Utilizing 15 years of oscillation data from the Michelson Doppler Imager (MDI) and the Global Oscillations Network Group (GONG) , we analyzed the frequencies of solar oscillations and simultaneous changes in seven other solar activity indicators from Cycle 23. This analysis was extended to Cycle 24 and the initial phase of Cycle 25. Our findings revealed a significant reduction – up to 40% –  in the sensitivity of frequency changes to long term solar activity levels in Cycle 24 compared to Cycle 23. Preliminary data from Cycle 25 indicates a resurgence in solar activity, suggesting a peak strength surpassing that of Cycle 24. This study provides insights into the evolving nature of solar activity and its seismic properties, offering valuable data for future solar and space weather forecasting.   

Effects of crystalline structures on protein repellent property of ultrathin homopolymer thin films

Fouling is the undesirable accumulation of a material on a wide variety of objects and has now become a widespread global problem from land to ocean with both economic and environmental penalties. Recently, we reported protein repellent properties of ultrathin polymer films that are considered to be of structural origin and generalizable across amorphous homopolymer systems¹. In this talk, ultrathin semicrystalline homopolymer films (≥ 100 nm thick) composed of isotactic polypropylene, low-density polyethylene, and poly(lactic acid) were subject to protein adsorption test against two model plasma proteins: fluorescein labeled bovine serum albumin (BSA) and fibrinogen. The stock protein solutions were diluted in phosphate-buffered saline (PBS) at a resultant protein concentration of 1 mg/ml in PBS for BSA and 0.1 mg/ml in PBS for fibrinogen. The polymer films were incubated in the protein solution for 30 min at 25 °C, then extracted and rinsed with water and thereafter dried with a gentle oxygen/nitrogen gas stream. The absorption of the BSA and fibrinogen on the thin film was measured using a photon counting spectrofluorometer. We will discuss the effect of crystalline structures on protein repellent properties.

¹D. Salatto, Y. T. et al., Macromolecules, 2020, 53, 6547.   

Wind Energy and its Effect on Local Weather and Climate

The need for clean, safe energy production has led to an accelerated deployment of windfarms around the world, including the eastern coast of the United States. An obvious question to ask is whether wind farms have an effect on the local microscale, mesoscale, and/or synoptic weather systems. The synoptic weather scale (large scale, cyclonic scale) is a horizontal length scale of the order of one thousand kilometers. Weather systems with this scale include extratropical cyclones, high and low pressure systems, and hurricanes. The mesoscale include systems with a length scale of five kilometers to hundreds of kilometers. These systems include sea breezes, squall lines, and convective thunderstorms. Microscale weather systems or features have a length scale smaller than five kilometers. Microscale systems include smaller clouds and breezes. These systems and features control the mixing and dilution processes in the atmosphere. Although this scale may seem unimportant, microscale meteorology studies processes such as heat transfer and gas processes involving soil, vegetation, surface water and the atmosphere caused.

Two avenues of research were followed in this study. The first avenue used computer modeling techniques to study weather patterns prior to the construction and operation of the three wind farms and compared them to weather patterns after the wind farms began producing power. The computer model used is the Weather Research and Forecasting (WRF) Model, This model simulates the structure of the atmosphere using historical data or present-day data for the initial conditions. This model was chosen for two reasons. First, it has a list of excellent features: two dynamical cores, a data assimilation system, a software architecture supporting parallel computation, and nested grids. The second avanue of research was to evaluate the historical weather records for areas with existing wind farms.   

Exploring meteoritic fragments with microscopy and spectroscopy techniques

Carbonaceous chondritic meteorites are ancient materials from the earliest times of our Solar System, and thus, these objects can provide valuable information about how planets formed. These meteorites are composed of micro/millimeter-sized inclusions surrounded by a matrix of microparticles. The study of the physical properties (e.g., structure, composition and morphology) of these constituents can give evidence of the conditions (e.g., thermal, temporal and barometric) in which the materials found in the meteoritic samples developed in our Solar System. These physical properties can be studied using different experimental and analytical methods. In this work, we use microscopy and spectroscopy techniques, such as Raman spectroscopy, optical microscopy and atomic force microscopy, to study several properties of carbonaceous meteorites (e.g., mineralogical composition and topography at the micro and nanoscale). In particular, we analyze two meteoritic fragments: Northwest Africa (NWA) 7184 and Aguas Zarcas. We explore numerous regions of individual inclusions, surrounding matrix and inclusion-matrix interface. We correlate our results to look for clues about the origin of these extraterrestrial materials.   

Insect swarms and complexity

Insect swarms exhibit collective behaviors that emerge from the interactions between individual insects. In midges these interactions are thought to be governed by long-range acoustic signals from other insects in the swarm. A model developed by Gorbonos et al [1.] adds the long-range acoustic behavior into an equation of motion to describe midge swarm dynamics. This research compares the results of the previously described model to a random walk model with additional statistical weighting to mimic an insect's response to the acoustic signal. The results of this work may further our understanding of the role randomness plays in swarms and complexity.

[1.] Dan Gorbonos et al, New J. Phys. 2016, 18, 073042.   

The Use of Atomic Force Microscopy to study charging and charge transfer between micron sized particles and substrates.

The interaction of micron-sized charged particles with substates is of significant interest to many industrial fields such as the pharmaceutical, paint, photocopy, and electronics industries. Specifically, the charging process and charge transfer mechanisms are of immediate importance. In this study, the Atomic Force Microscope is used to measure the interaction force between micron-sized particles and substrates. Different charging mechanisms are used including tribocharging and polarization processes. Theoretical models are used to determine the charge distribution and charge transfer during contact.   

Structural and Electrical Properties of Calcium Manganese Oxide Thin Films

Calcium manganese oxide (CaMnO₃ abbreviated as CMO) is a metal oxide thin film belonging to the ABO₃ perovskite family of materials, where A is an alkaline earth metal, B is a transition metal, and O is oxygen. Electrical resistivity, a property of interest for applications of CMO in renewable energy technologies, can be controlled by introducing vacancies at the oxygen site of the crystal lattice, which are produced when the material is oxygen deficient. We will present recent results from our research on controlling oxygen deficiency in epitaxial thin films of CMO which are grown using pulsed laser deposition (PLD). Previous research has shown that for CMO films grown on (100) oriented LaAlO₃ (LAO) substrates, tensile strain present help stabilize oxygen deficiency. The resistivity of these films is strongly thickness dependent. Thinnest films, which are coherently strained films show resistivity which is orders of magnitude less than that of the fully oxygenated material. In addition to film thickness, film growth parameters such as oxygen pressure and laser fluence (energy density) used for the deposition also control oxygen stoichiometry, and thus the structural and electrical properties of the film. We will present our results on the dependence of structural and electrical properties of CMO films on the laser fluence and oxygen growth pressure.   

Proton-Emission Resonance Levels in 11B

A narrow near-threshold proton resonance in 11B was proposed near E_x=11.44 MeV to explain the branching ratio discrepancy of 11Be→10Be. The proton resonacne was thought to enhance the β-delayed proton emission in 11Be and leads to a larger than expected decay branch to 10Be. The reaction 7Li(α,p)10Be was performed using the FN accelerator at ISNAP in the University of Notre Dame to search for the resonance. A range of energies were tested with a focus on the hypothetical excitation value. After the conclusion of the experiment and analysis of the data, there seems to be no resonance level at the indicated value nor any other unknown resonance in the aforementioned energy range though there were unreported triton decays found at higher energies. A more thorough study of the α angular distribution or an approach that would detect a proton resonacne width only would be of benefit to this decay. Otherwise, the 11Be→10Be decay would require some form of exotic decay to explain it and with it comes the potential for new physics.   

On the Center of Mass of the Half n-Ball

This project explores how the center of mass (COM) of a half ball depends on its number of dimensions (n). A closed form solution is obtained for the COM, which confirms the known two and three dimensional cases. The solution is proven to converge.   

Control of polar phases of PVDF through electrospraying

Poly(vinylidene fluoride) (PVDF) is a thermoplastic fluoropolymer with wide applications in industry ranging from antifouling filtration membranes to lithium-ion battery cathodes.  However, films with thicknesses on the order of micro- to nano-meters form the beta (chain conformation TTTT) and gamma (chain conformation TTTGTTTG’) crystallographic phases [1]. Here,  we create thin mats of PVDF through an alternative method of processing, using solution electrospraying. We used the solvent N,N-dimethylacetamide (DMAc) to create electrospinning solutions with concentrations on a PVDF weight to DMAc volume basis ranging from 3% to 12%. The resultant films were analyzed with Fourier-Transform Infrared spectroscopy and wide-angle X-ray diffraction in order to observe and quantify the crystalline phases of the samples. The phases were identified using the methodology of Cai, et al. [2]. The specific ratios of crystallographic phases in the samples were found using Fourier Self Deconvolution of the FTIR absorbance spectra. [3]. We observed that solution concentration influenced the relative amounts of beta and gamma phases. A high ratio of electroactive gamma to beta phase (84/16) was found in the 12% weight-to-volume sample, and through this study we reinforce the link between thin films and existence of higher percentages of the electroactive crystalline phases in PVDF.  

References 

[1] Andrew J. Lovinger. Poly(Vinylidene Fluoride). Developments in Crystalline Polymers, Chapter 1. (Springer, Dordrecht, Netherlands, 1982, vol 33, pp. 196-273)

[2] Anuja S. Jayasekara, Peggy Cebe. Quantitative analysis of polar crystalline fractions in poly(vinylidene fluoride) electrospun fibers and electrosprayed films. Polymer (2023) 281, 2-7

[3] Xiomei Cai, Tingping Lei, Daoheng Sun, Liwei Lin. A Critical Analysis of the α, β and γ phases in poly(vinylidene fluoride) using FTIR. RSC Advances (2017) 7, 1-2   

Lightcurve Photometry of Suitable Astroids Using an Automated Observatory

The purpose of this presentation is to provide an overview of the research conducted by the previous group of cadet researchers at the West Point Observatory and to introduce new data on the targets slated for investigation during the current academic year. Specifically, we are focusing on three asteroids: 458732 2011 MD5 with a magnitude of 13.9, 6991 Chichibu with a magnitude of 14.6, and 8265 1986 RB5 with a magnitude of 14.9. 

Our primary objective at the West Point Observatory is to gather experimental data related to the light intensity of these asteroids, with a particular emphasis on those with unknown rotational periods. To achieve this, it is imperative to transform our observatory into an automated system with minimal human intervention. This automation comprises three essential tasks, each to be accomplished over time:

1. Develop a Reliable Autofocus System: We aim to identify a dependable and compatible autofocus method that can be seamlessly integrated with our existing equipment. This will enhance the precision of our observations.

2. Address Temperature-Induced Focal Length Effects: Recognizing the impact of temperature on the optical tube assembly (OTA) is crucial. We intend to measure and correct these effects to maintain image quality and accuracy.

3. Optimize Image Capture Workflow: Streamlining the process of capturing images is essential for facilitating the remote operation of the telescope, making it more accessible for future cadets. This optimization will involve using tools such as an attached temperature sensor, TheSkyX program, the observatory automation and imaging program N.I.N.A., as well as image processing software like MaxIM DL and Photoshop.

This research represents a significant expansion of the West Point Observatory's capabilities. It enables us to conduct 8-hour imaging sessions, a feat previously unattainable for our observatory. The integration of automation software and instrumentation will not only improve the efficiency of our observations but also enhance the observatory's potential for future research and cadet engagement.   

Elastomer Bistable Jumper for Soft Robotics

Multistability, characterized by the presence of multiple stable equilibrium states, has recently emerged as a versatile foundation for designing a broad spectrum of intelligent structures. These structures encompass shape-reconfigurable architectures, entirely elastic and recyclable metamaterials capable of storing energy, soft aquatic robots equipped with preprogrammed directional propulsion, and aerospace-grade deployable solar panels. Within the scope of our project, we concentrate on bistable spherical caps and delineate specific geometric configurations that give rise to an energy barrier surmountable upon impact, thereby creating opportunities for jumping behavior. Our methodology involves the fabrication of diverse shell variations, a comprehensive assessment of their nonlinear responses when subjected to indentation, and rigorous testing to validate their capability for jumping upon contact with a rigid surface.   

Assembling and testing an atomic force microscope to examine carbonaceous meteoritic fragments

Atomic force microscopy (AFM) is a technique that can be used to analyze several properties of a sample’s surface (e.g., optical, topographical, mechanical, chemical, magnetic and electrical properties) through non-destructive and accurate measurements with very high resolution at the nano- and micro-scales. In this work, we assemble and test an educational AFM system with different AFM tips and appropriate samples with the final goal of characterizing fragments of carbonaceous chondritic meteorites by examining their topography and mechanical properties, such as adhesion and hardness. These properties allow us to investigate what structures are on the surfaces of the samples and how they have stuck together. Our findings can provide novel valuable evidence about how planets formed in our Solar System since carbonaceous chondritic meteorites are relics that date back to the origin of the planets. In addition, from a pedagogical point of view, this study was conceived as an undergraduate research project to expose students, in particular physics majors, to all the stages of an experimental scientific work.      

Determining Efficiency of Direct Energy Converters through Simulation

Direct energy converters (DEC) for ions leaving magnetic confinement have been theorized for decades. We examine simulations of some proposed set ups, such as the "venetian blind" arrangement [1,2], to calculate the conversion efficiency for ions. The simulations are run via the Boris particle push algorithm, while the electric and magnetic field set ups are determined through Gmsh and Dolfinx. Efficiency is determined by the change in the kinetic energy once the ion collides with an ion collector. DEC methods for energy capture from fusion reactors theoretically allow for higher energy efficiency than standard heat cycle energy capture. DEC methods lend themselves to open field line configurations.   

Study of Higgs Boson Production in the ttHH mode at the Future HL-LHC with the ATLAS Detector at CERN

The Higgs field is one of the fundamental constituents of the Standard Model of Particle Physics. It plays a crucial role in giving mass to fundamental particles and is directly related to the electroweak symmetry breaking. Much effort has gone into studying Higgs pair production through two different production modes, gluon-gluon fusion and vector-boson fusion. However, a third production mode, top quark-antiquark production (ttHH) can serve as a valuable source of information for probing the limits of the Standard Model pertaining to the Higgs boson. With the much lower cross-section of ttHH production, higher luminosities and better statistics are required to detect ttHH production. The HL-LHC should provide both the upgraded detector technology and the higher luminosities required. Using Monte Carlo simulations, we generate ttHH samples, along with background samples, to simulate their detector response for future accelerator technologies.   

Luddism on Diffusion Networks.

We further develop and analyze the LISA (Luddite, Ignorant, Susceptible, Adopter) diffusion model via mean field theory and network simulation. We eliminate ignorant nodes from the stationary state, such that only 'Adopters' and 'Luddites' are left after some time. We analyze different sets of initial conditions, and their effects on the stationary state of the network. Namely, we investigate the possibility for luddism resulting from triadic connections, which are considered the basis of social networks. We also study the stationary states resulting from 2 and 3 densely connected sub-graphs with one 'seeding' subgraph and various proportions of bridging between subgraphs.   

Interactive Infrared Camera Photo Booth

Thermal imaging, rooted in the detection of infrared radiation, helps visualize the temperature of various objects. The “picture” created is a heat signature. This technology has many practical applications. In pursuit of enhancing understanding and engagement with the physics of thermal imaging, we have created an interactive infrared (IR) photo booth. This project is a scientific take on the conventional photo booth experience, integrating thermal imaging technology to serve entertaining educational purposes. We have used the FLIR Lepton 3.5 Thermal Imaging Camera, complemented by other FLIR products and Raspberry Pi software. In this interactive photo booth, participants are offered a unique opportunity to capture their own heat signatures, thereby gaining insights into the capabilities of a thermal camera. Serving as a bridge between the scientific community and the general population, users can achieve this by participating in various activities, such as using different background materials and moving around to create different thermal images that would not be noticeable in regular cameras. This photo booth can be a traveling exhibit, to local schools, science fairs, and conferences to provide learning experiences for scientists of any level.   

Gauging Non-invertible Symmetries

This work investigates the consequences of gauging non-invertible symmetries, which are symmetries that do not follow group-like compositions. We focus on specific examples, such as gauging a discrete subset of non-invertible O(2) electric symmetries and gauging the non-invertible O(2) magnetic 1-form symmetries (which leads to BF theory with gauged charge conjugation). Key findings include the definition for a charged operator to remain invariant under non-invertible symmetries, nontrivial mappings between symmetry operators as well as nontrivial fusion rules in the former example, and novel discoveries about BF theory. The poster presentation will also introduce generalized symmetry and the concept of gauging to provide context for our research.   

Light-driven transformations in entangled active matter

California blackworms (Lumbriculus variegatus) are freshwater aquatic worms that entangle with one another, forming aggregate structures commonly referred to as worm blobs. Biologically, the entangled state of worms helps them in the efficient execution of vital functions such as temperature maintenance, moisture control, oxygen regulation, and collective locomotion. From the active matter perspective, these tangled worm blobs represent a remarkable material that can autonomously self-assemble, shape-shift, and exhibit other emergent collective functions. Here, we investigate the response of these worm blobs to light exposure. It had been shown previously that blackworms are negatively phototactic in nature, i.e., they tend to move away from light. We leverage this behavior of worms to control their collective motion through a remotely applied stimulus. To this end, we study the dynamic response, shape transformation, and adaptive behavior of entangled living matter as the function of programmed light. Moreover, blackworms show the tendency to entangle with passive material present in their proximity, due to thigmotaxis. The interplay of these blackworms’ intrinsic behaviors can be harnessed to develop strategies aimed at light-guided material transportation and/or assembly through the utilization of entangled active matter.   

Ab initio excited state forces towards light-induced changes in methylammonium lead iodide (MAPI) perovskites

Perovskites are promising materials for use in solar cells, although their degradation limits their use on a large scale. Several works have studied its optical and vibrational properties but the understanding of the exciton-phonon effects is still limited. We study methylammonium lead iodide perovskite (MAPI) in its three phases (cubic, orthorhombic and tetragonal) using excited state (ES) forces from the GW/Bethe-Salpeter equation approach. These forces are the gradient of the ES potential energy surface and indicate the direction atoms tend to move due to light absorption and are useful for the understanding of the microscopic mechanism of exciton self-trapping. Our implementation combines results from the BerkeleyGW code and electron-phonon coefficients from Quantum ESPRESSO. The main advantage of our approach is that our calculations just demand one GW/BSE + DFPT calculation in contrast to finite differences that would demand 3N calculations. For the three phases, we observe strong exciton-phonon coupling with low-frequency modes, which may be related to the degradation of those materials. Our results agree with time-resolved optical experimental data of the tetragonal and orthorhombic phases of exciton coupling to coherent phonons (in particular, the distortion of the I-Pb-I angle). We also study the relaxation of the system on the ES potential energy surfaces and light-induced stress.   

Pneumatic Gaussian cells

In Nature, plants leaves or petals may develop into very complex shapes through differential growth. Such change of a surface into a well-defined 3D shape requires both distorting distance along the plane and bending curvature simultaneously. However, current mechanisms are usually limited to either bending or metric distortion with soft systems. Programming complete morphing in stiff structures are relevant for engineering applications remains a challenge.

 

Here, we present and rationalize a novel and versatile gaussian morphing approach inspired by pneumatic actuation in monocotyledon plant leaves (bulliform cells). Our method relies on two pieces of airtight fabric separated by a network of thin walls that define pneumatic Gaussian cells. Both in-plane contraction and angular deflection of the panels can be programmed simultaneously through the cross section of the walls and the width of the cell. In addition, the stiffness of the structure is proportional to the applied pressure, which paves the way for the development of large-scale objects. These surfaces with controlled stiffness and fast actuation are manufactured using consumer-grade materials and constitutes an important milestone towards large-scale shape-morphing robotics applications.

    

Topological band degeneracies from spin-space symmetries

Crystalline symmetries have always played a crucial role in the classification of solids, culminating in the 1651 magnetic space groups, which capture spatial symmetries as well as time reversal. Yet, once we need to describe an electron spin, the well-known extension to double groups introduces an easily overlooked assumption: Spin and spatial actions are tightly coupled and of the same order, e.g., a fourfold spatial rotation is only combined with a fourfold spin rotation. We find magnetic textures, for which such a description is generally insufficient, instead spin-space groups are needed [1,2].

To clarify the band topological implications of such spin-space symmetries in electronic systems, we discuss enforced nodal surfaces and how they evolve with spin-orbit coupling. Further, we identify emergent spin-symmetries of spin-orbit coupled nonmagnetic phases, which pin Weyl points even when time-reversal symmetry is broken.

[1] Brinkman, W. F., et al. (1966),

[2] Corticelli, A., et al. (2022)   

Deicing with in situ Electrolysis

Ice accretion is ubiquitous and destructive: from car windshields to powerlines, wind turbines to airplanes, ice-induced damages comprise a multibillion-dollar problem in the United States alone. Traditional deicing methods rely on mechanical scrubbing, heating, or chemical melting that are crude, inefficient, and even environmentally toxic. Here we propose a fundamentally different approach to the classical problem of deicing using in situ water electrolysis. We show with experiments how a progressing ice front can trap the electrolytically generated bubbles at the interface that subsequently act as stress concentrators to diminish the energy required to fracture ice. Our proposed mechanism constitutes a self-starting, self-limiting means to reduce ice adhesion– a feature hitherto non-existent.   

Vortex interactions in Water-walking insects

Microvelia are water walking insects of the order Gerromorpha, which locomote on both water and land. Unlike Gerridae’s rowing gait on water, these insects use an alternating tripod gait on both water and land.  Microvelia shed pairs of vortices during the power strokes of their middle legs and hind legs. In the case of microvelia, hind legs stir the vortices shed from the middle legs, enhancing their circulation. However, such energy recapture phenomenon is absent in water locomotion of other water walking insects. Here, we unveil the role of vortex interactions in Microvelia and other insects of the same order. Our observations are based on the data collected via high-speed imaging and particle imaging velocimetry (PIV) techniques. Furthermore, we also built a physical model to study vortex-structure interactions in Microvelia, where we studied the effect of the stroke frequency, the stroke duration, and the time difference between the middle and hind legs’ strokes on the vortex circulation. Our work on understanding the vortex interactions of water walking insects can be used as a guide to design the efficient microscale water walking robots.   

How to efficiently extract a filament from a topological tangle

Tangled balls of soft filaments are encountered ubiquitously, ranging from Cyanobacteria tangles to tangled computer cables inside a storage drawer. How does the entanglement between individual filaments affect their untangling behavior? We explore this question by considering the extraction of a single soft fiber from a tangled ball of similar fibers hanging in gravity. Our experiments reveal that vertically vibrating a single fiber from the hanging tangle at an optimal frequency can lead to its expedited extraction. We test this observation for various degrees of “tangledness” by changing the parameters of an in-house stochastic tangling setup. We try to further understand this behavior by taking a deterministically formed entangled system using a square mesh of soft fibers instead of the tangled ball. These experiments uncover the role played by the internal tangle topology and material properties of the fibers in the frequency response of fiber extraction. Our minimal experimental model along with numerical simulations can provide useful insights into understanding the relationship between entanglement and dynamical responses of a system.   

Ab-initio MD simulations of laser-induced pressure waves tuning nonthermal melting in silicon thin films

Intense ultrafast-laser pulses can induce tremendous structural changes in materials. In particular, at the surface the deposited energy can cause several modifications like ripple formation, droplets, holes, or super-hydrophilic behavior. Most of those effects are initiated by laser-induced nonthermal conditions and their ensuing ultrafast processes like nonthermal melting. But how does the free surface affect the microscopic pathways of those ultrafast phenomena, in particular nonthermal melting. Here, we performed ab-initio molecular dynamics simulations of laser-excited thin silicon films, starting from an electronic temperature around the bulk laser-melting threshold above which irreversible changes to the material are induced. Our findings indicate that the broken symmetry at the surface has a big influence on laser-induced ultrafast processes and therefore on the reconstruction effects. In more detail, we observe that an out-of-plane pressure wave is induced by the excitation, which reflects back and forth from the surfaces. For moderate levels of excitation, this causes a breathing mode perpendicular to the film/surface, whereas for higher levels of excitations transient melting below the surface takes place, which is healed by the incoming pressure wave.   

Summer Quantum Engineering Internship Program: An Intensive Training Program for Future Quantum Engineers

Quantum information science and engineering (QISE) has the potential to revolutionize the world of computing, sensing and communication in the years to come. Preparing a well-trained workforce to drive progress in QISE requires hands-on training experiences from the early years of college education. The Summer Quantum Engineering Internship Program (SQEIP) is an intensive training program that allows students to explore multiple facets of QISE through hands-on training modules. SQEIP is jointly organized by Clemson and Winston-Salem State University. The program is comprised of three modules: 1) vacuum technology, where we design, assemble, and test vacuum systems that achieve ultra-high vacuum conditions; 2) cryogenic technology, in which we assemble and test open- and closed-cycle cryocoolers for electrical characterization of various superconducting materials; 3) Lasers and packaging: for which we fabricate, package, and characterize active, semiconductor lasers devices in vacuum and under cryogenic conditions. Through experiential learning, we gained an understanding of the role and importance of vacuum systems, cryogenics, and laser in quantum engineering.   

Preparing a Diverse Quantum Workforce in Carolinas through Hands-on Education and Training Experiences

Quantum Information Science and Engineering (QISE) is an emerging field of technology with the potential to revolutionize the world of computation in the near future and push the frontiers of science and engineering. Our team at Winston-Salem State University (WSSU) focuses on QISE education by developing curricula that are tailored to the needs of the quantum industry. Recently, in collaboration with Clemson University, our team has established the Winston-Salem Quantum Education Collaboratory (WS-QEC) with the mission to attract and retain a diverse population of quantum engineering trainees from the Carolinas. The program has six modules with a strong emphasis on hands-on experiences over conventional lectures. The modules include 1) Python Programming, 2) Electronics and Circuits, 3) Vacuum Technology, 4) Cryogenics Measurements, 5) Optoelectronic and Microwave Systems, and 6) Quantum Simulations and Computations. The program also includes an intensive 8-week summer internship program that provides an opportunity for trainees to immerse themselves in experimental quantum research. The training and internship modules are complemented by one-on-one advising and career coaching sessions to guide our trainees toward careers in the QISE ecosystem.   

Higher-order thinking skills in an introductory mechanics course at a teacher education college in Japan.

Based on the revised Japanese national curriculum standards, called the "Course of Study", which was implemented in 2022, each high school was required to evaluate the abilities to think, judge, and express and an attitude to engage in learning autonomously in addition to the acquisition of fundamental knowledge/skills. However, many high school teachers are at a loss, not knowing how to evaluate the new evaluation perspectives. In this situation, students in teacher training programs themselves need opportunities to learn experientially how to develop and evaluate higher-order thinking skills including the abilities to think, judge, and express in each subject area. This study presents an approach to developing higher-order thinking skills in physics implemented in an introductory mechanics course for first-year students who wish to become high school teachers.   

Ten Years of Supporting Middle School Girls in STEM

On the tenth year of the Physics Wonder Girls Program, a free physics summer program to stimulate and sustain interest in physics among middle school girls, 32 rising 8th and 9th graders participated in an intensive week-long immersive program held on the University Campus of Saint Joseph's University. Campers were selected from a pool of high-performing students in the Philadelphia-New Jersey region and came from diverse communities. They were introduced to renewable energy and the basics of solar cells and built and tested solar-powered fidget spinners, solar cars, solar trackers, solar cookers, wind turbines and performed hands-on optics experiments. Campers received a free kit of materials for projects and experiments. Campers interact with physics majors and high school students who serve as crew, women physicists and engineers, experience virtual tours of plants and manufacturing facilities, and gave capstone presentations. We report on the products of the camp, as well as results of blind surveys of campers and parents.   

Using centrality measures to analyze social networks among engineering students

Social Network Analysis provides a powerful way to assess social structures within communities. Prior research found that centrality, a quantitative measure of how connected someone is in a network, and social interactions can predict student success as determined by their physics conceptual inventory performance and physics course grade. We aimed to create a visual network of an introductory physics course for engineering students and understand centrality within the network. Visual networks allow us to make inferences about communities which then guide quantitative analysis. Our visual analysis of the network allowed us to identify students central to the network (most connected) and students isolated from the network (not connected). Our data supports that students in affinity-based professional groups are most central in the classroom network. Additionally, we found that there were no isolated students in the network.   

Physics Education and Artificial Intellegence - Using ChatGPT to Teach Modeling and Coding

Tools using Artificial Intelligence are becoming readily available to students. Faculty and administrators at many colleges and universities are debating if such tools should be used, as well as how they can be used both effectively and ethically. In this project, introductory college physics students were instructed on the use and abilities of artificial intelligence tools, such as chatbots. The chatbot used in this research was ChatGPT. ChatGPT (chat generative pre-trained transformer), is a chatbot that students can utilize to learn how to effectively code in the coding program, Python. Before using ChatGPT to code, the students are given a pre-test survey to determine how well they know ChatGPT, how well they know how to code, and specifically how well they know how to code in Python. Survey questions were also presented to the students in order to judge their familiarity of chatbots and their previous use in other classes. After learning with ChatGPT, a post-test survey is conducted to determine how well the students have learned to code in Python as well as how effective ChatGPT was in assisting their study.

The students were also tasked with producing a proposal for the establishment of policies governing the use Artificial Intelligence in their research and in their course work This proposal was presented to the Physics Program and Provost for review and editing.   

Development of a scanning electron microscope activity for upper division STEM labs.

Our goal was to develop a lab activity aimed at upper division physics or chemistry majors that utilizes solder balls to demonstrate the functions and capabilities of a scanning electron microscope (SEM). SEMs are becoming more and more common in both industry and graduate research labs. Alternative activities are also outlined for colleges and universities that do not have undergraduate access to an SEM. This lab has two main objectives. First, this lab will demonstrate the difference between the backscattered electron detector and the secondary electron detector. Students will note that the surface details of the solder balls are very sharp when using the secondary electron detector, and the elemental composition of the solder balls are much more distinctive when using the backscattered detector. The second objective is to use the energy-dispersive x-ray detector (EDS) to analyze the elemental composition of the samples. Students will compare the percentages of lead and tin in the solder balls measured by the EDS detector to the manufacturer labeled percentages on the packaging. Students will gain relevant experience that will benefit them in their post graduation plans.   

Fully Online Bachelor of Science Degree in Physics

At Arizona State University we have developed the first and only fully online Bachelor of Science degree in Physics in the country, with a complete curriculum that matches the on-ground version identically. In the first two years, enrollment in the online program has grown to over 350 students, which is more than twice that of the immersion program. Key components of the curriculum include two semesters of Math Methods and two upper division labs, featuring custom-built simulators that produce signals with the full scope of “imperfections” that comprise real measurements including: noise (Poisson, 1/f, drift); background; hysteresis; resolution and bandwidth limitations; etc. We describe the particular challenges of building the online program, show examples of the Canvas-based assignments and discuss the demographics and performance of the cohort of online students.   

Remote Access: Redesigning the Physics Laboratory to Enhance Accessibility and Equity

The pandemic unwantedly pushed higher education into online teaching. This otherwise unwelcome experience, however, has unlocked previously untapped opportunities to reach underserved students struggling to succeed within the traditional path. Here we report on a two-semester remote introductory physics laboratory course we designed to provide authentic scientific training on par with traditional in-person laboratory instruction. The class centers on hands-on experiments performed by the students at home with instruments and supplies from a low-cost reusable laboratory kit we assembled. Activities have been thoughtfully designed to facilitate interactions among students and between students and instructors. We aim to provide a sound alternative to the in-person lab especially for at-risk and transfer students who face greater challenges to fulfill their academic requirements. Since its inception, the class has been on high demand, and the students have consistently cited flexibility as a reason for taking it.   

Instructor and Student Interactions in Remote and Traditional Undergraduate Physics Laboratories

The overarching goal of this study is to explore how undergraduate physics learning experiences and affective domains differ when comparing in-person and remote laboratory instruction. The recent ubiquity of online learning, particularly in physics laboratory settings, provides a unique context for exploring how to optimize physics laboratory instruction. The research was conducted at public research university in the Northeastern U.S. In-person, collaborative, introductory undergraduate physics laboratory courses enrolled approximately 720 students each semester, and the remote laboratories (performed individually with iOLab devices) served roughly 360 students. Interviews were conducted with a stratified sample of N=23 undergraduate physics students in both instructional modes. Coded interviews indicated several overarching themes: (1) Students in both types of classes preferred collaboration in performing data collection and analyses; (2) Many students were not well informed of instructional options when registering as first-year students; (3) The quality and frequency of teaching assistant interactions were more positive in face-to-face laboratory classes, which influenced students’ self-efficacy, agency, and comprehension. Findings indicated remote and traditional in-person laboratory instruction should promote peer-to-peer collaboration and instructor-student interactions to promote equity, rigor, and responsiveness to students’ individual learning needs.          

Modular Introductory Physics Laboratories using Active Engagement

Faculty at the University of Mount Union over the past decade have developed a modular introductory physics laboratory curriculum that applies activity-based pedagogies. During the weekly laboratory rather than focus on a singular topic, students work on four tasks: a set of concept questions and three different experiments.  This allows for a larger number of topics to be covered while only requiring one setup of a given experiment. The focus and outcomes of each experiment can be varied to tune the student learning experience or the desired learning outcomes.  Post-lab, students complete a short writing assignment answering specific questions related to their experience to put into their own words the concepts, experimental process or extensions to other ideas.  The Force Concept Inventory (FCI) Brief Electricity and Magnetism Assessment (BEMA) pre- and post-test are used to measure the success of student learning and to influence the fine tuning of the next experience.   This poster will provide examples of experiments demonstrating the variety of content that can be covered in a given laboratory period including using small computer fans to teach simple circuits.   

Polarimetry as a Gateway to Careers in Optics

Over the past two decades, we have found polarimetry to be an effective topic for attracting students to optics and training them for careers. Students appreciate applications of polarized light to a wide range of fields such as biology, medicine, environmental sensing, and materials science. Here, we showcase ways to incorporate polarimetry into the undergraduate curriculum, from simple measurements for first-year students to the construction of Stokes and Mueller polarimeters at the senior level. Many of the former students who worked on these projects are now optics professionals in industry, academia, and government laboratories.   

Required Course Based Outreach, The Benefit of Getting All Students to engage With The Community

Societal and systemic barriers can deter students from embracing the role of physicists and finding belonging within the field. To address this, we've integrated outreach into the physics major sequence. Outreach often attracts students with a pre-existing interest in public engagement. By making outreach a required component, we elevate its importance alongside traditional lab and lecture coursework. This inclusive approach acknowledges that, just as some students are inspired by theory or experimentation, others prioritize making a societal impact. These students don't see physics as an career option that has a large first order societal impact. Incorporating outreach into the curriculum demonstrates that we value this societial impact and welcomes students who also share this value. For all students taking this course, it accomplishes several goals: it deepens their understanding by explaing concept to a different audience, solidifies their identity as physicist role models in the community, and fosters a sense of belonging. We'll delve into the logistical and curricular challenges of implementing this course, along with the benefits to the community, students, and the institution.   

Growth and Study of Manganese doped Zinc Nitride Thin Films for Spintronics Applications

Dilute magnetic semiconductors are a class of materials that are synthesized by lightly doping semiconductors with transition metal elements. This gives rise to a material that is semiconducting as well as ferromagnetic with spin-polarized charge carriers. Such materials can be used in spintronics applications where not only charge but spin degree of freedom of charge carriers can be manipulated. We are reporting the thin film growth and study of manganese-doped zinc nitride by RF/DC magnetron sputtering on Si(100) and glass substrates. Films were grown by sputtering the zinc and manganese targets by DC and RF-powered magnetron guns in argon and nitrogen ambient. Several films were grown at different Mn/Zn ratios. The manganese doping was controlled by adjusting the RF power of the manganese sputtering gun whereas the DC power for the zinc target was kept at a fixed value for all the grown samples. The films were studied using spectrophotometry, x-ray diffraction, Hall effect measurement, atomic force microscopy and x-ray photoelectron spectroscopy. The effect of manganese concentration in the film on the electronic, structural, chemical, morphological and magnetic properties of the films will be discussed in the presentation.   

Revealing the Impact of Grain Boundaries on Thermal and Electrical Transport in 2D MoS2

TMDCs are pivotal semiconductor materials with immense potential for future devices. Understanding the impact of defects, especially GBs, on thermal and electrical transport in 2D TMDCs is crucial for thermoelectric applications. In this research, we have harnessed nonequilibrium molecular dynamics simulations and first-principles quantum-mechanical calculations to study the thermal and electrical transport properties across and along GBs within a monolayer of the quintessential TMDC material, MoS₂.

We found the presence of an interfacial phase (or interphase) within 4 nm from GBs, exhibiting distinctly anisotropic transport characteristics when compared to the pristine crystal lattice. Specifically, the interphase exhibits an astonishing 80% reduction in thermal conductivity across GBs, in stark contrast with negligible effects on heat conduction parallel to GBs. More remarkable is enhanced electrical conductivity in both directions, which can be attributed to unique mid-gap states at GBs that bridge electronic states within the discrete density of states of the pristine material, effectively smoothing them and thereby amplifying electrical conductivity.

The distinct properties of GB interphases unlock the thermoelectric potential of 2D TMDCs. Strategically arranging GBs achieves the balance needed for MoS₂'s thermoelectric promise.   

Doping effectiveness and stability in semiconducting polymers

Molecular doping of semiconducting polymers has emerged as a prominent research topic in the field

of organic electronics with new dopant molecules introduced regularly. FeCl₃ has gained attention as a

p-type dopant due to its low-cost, availability, ability to dope high ionization energy co-polymers, and

its use as a dopant that can be used with anion exchange. Here, we use a combination of UV-Vis-NIR

spectroscopy, four-probe sheet resistance measurements, and X-ray absorption near-edge structure

(XANES) spectroscopy to perform lifetime measurements to assess the stability of the doped polymers

over time, which is crucial for evaluating the long-term performance and reliability of the doped films.

FeCl₃ can cause radical side reactions that damage the conjugated polymer backbone, leading to

degradation of the electronic properties. The rate of this degradation is orders of magnitude higher

when the film is exposed to air. Anion exchange doping can reduce the [FeCl₄]⁻ concentration,

but does not necessarily improve the doping lifetime because anion exchange electrolytes can serve

as co-reactants for the degradation reaction. By comparison, doping with (2,3,5,6-Tetrafluoro-2,5-

cyclohexadiene-1,4-diylidene)dimalononitrile (F4TCNQ) as the reactive dopant results in lower initial

conductivity, but the lifetime of the doped polymer is almost tripled as compared to FeCl₃ doped

polymer films. These findings highlight that the use of FeCl₃ as a molecular dopant requires a

cost/benefit analysis between higher initial doping levels and lower film stability.   

Tunneling Induced Luminescence Investigation of Single Photon Emitters in 2D Semiconductors

Single photon emitters (SPE) are important components for various opto-electronic applications and quantum technologies. Defects in 2D materials such as transition metal dichalcogenides (TMDs) are promising candidates as SPEs due to their topographical flexibility, high binding energy and brightness. Their SPE characteristics can be enhanced via defect-engineering and environmental influences [1-3]. Here, we use scanning tunneling microscope induced luminescence (STML) to study the local optical properties of WSe₂ (a wide band gap 2D semiconductor), including how the optical response can be varied through environmental manipulation [3]. By studying WSe₂ samples that are isolated from a conductive substrate, we will show how quenching can be reduced in STML measurements, while plasmonic enhancement from the SPM tip can still be maintained. [2,3].

1) Michaelis de Vasconcellos et al, Physica status solidi 4, 2100566 (2022) DOI:10.1002/pssb.202100566

2) Luca Sortino et al, Nat Commun 12, 6063 (2021) DOI:https://doi.org/10.1038/s41467-021-26262-3

3) Renoud Pechou et al, ACS Photonics 7, 3061-3070 (2020) DOI:https://pubs.acs.org/doi/full/10.1021/acsphotonics.0c01101   

Peculiar Electronic Structure of Decavacancy V10 in Si Crystal

The electronic structure created by an atomic vacancy, called V₁₀, in silicon crystals is investigated by first-principles calculations based on the density-functional theory. The remixing of dangling bonds of silicon atoms adjacent to the vacant sites creates four deep levels in the band gap, and an unexpected result was obtained for these dangling-bond states: wave functions with nodes have lower energy than wave functions without nodes. This completely contradicts the textbook statement that "wave functions with more nodes have higher energy than wave functions with fewer nodes by the amount of kinetic energy." Detailed analysis reveals that this peculiar electronic structure is generated by the interaction between the rebond states buried in the valence and conduction bands and the dangling-bond states in the band gap. We argue that the  Jahn-Teller instability of the atomic structure of this system reflects this seemingly strange electronic structure. We also argue that large-scale ab initio calculations with 2000 Si atoms were essential for this discovery.   

Impacts of Metal Tips and Dopants on the Electronic Transport in 1-Dimensional CdS Nanorods

We synthesize 1-dimensional CdS nanorods (NRs) with and without Pt nanoparticle tips, and with and without Mn²⁺ dopants in the CdS host lattice [1]. A contactless, non-destructive imaging technique, dielectric force microscopy (DFM), is used to probe the electronic transport properties in as-synthesized CdS-based NRs. DFM experiments reveal low conductivity in undoped and untipped CdS NRs. The impacts of Pt tips and Mn²⁺ dopants on the electronic transport in CdS NRs, which are under investigation, will be reported.

References:

[1] W. MacSwain, H. Lin, Z. -J. Li, S. Li, C. Chu, L. Dube, O. Chen, G. Leem, and W. Zheng, J. Mater. Chem. A 11, 7066-7076 (2023).   

Jahn-Teller Defects in Solids: Integrated Infinite-mode Coupling Theory and Applications

Transition metals (TM), with their flexible chemistry and rich physics, are among the most versatile dopants for semiconductors to achieve exotic functionalities that would not be possible otherwise. Unfortunately, an accurate understanding of TM defects in semiconductors is often hampered by a multitude of challenges such as strong Coulomb correlations and the Jahn-Teller (JT) effect. Unlike in the case of molecular systems, JT defects in solids in principle involve an infinite number of phonon modes, and theory needs to go beyond the conventional few-mode JT models. Herein, we develop an integrated infinite-mode theory for treating JT defects in solids with quadratic coupling effects included and apply the theory to Ni doped CdS. Doping Ni in CdS has been shown to improve its photocatalytic activities, but the underlying mechanism is still not understood. We find that the interplay among crystal-field splitting, JT distortion and on-site Coulomb correlation results in the appearance of active defect states near the conduction band edge. Therefore, introducing Ni dopants in CdS may not only provide reaction sites but also introduce near-edge electronic states that can enhance photo-absorption or fine tune the band edge position for selective photocatalytic reactions.   

Electronic Uniformity in Template-Grown CsPbBr3 Nanorods

We synthesize all-inorganic perovskite CsPbBr₃ NRs with tailored dimensions, using amphiphilic bottlebrush-like block copolymer (BBCP) as nanoreactors [1]. A novel contactless scanning probe microscopy (SPM)-based imaging technique, dielectric force microscopy (DFM), is employed to study the electronic properties in template-grown CsPbBr₃ NRs. We find that all freshly prepared CsPbBr₃ NRs exhibit ambipolar behaviors which remain up to two months [2]. A transition from ambipolar to p-type behaviors occur after two months, and nearly all CsPbBr₃ NRs change to p-type within two weeks [2]. Furthermore, template-grown CsPbBr₃ NRs display improved nanoscale electronic homogeneity compared to CsPbBr₃ NWs synthesized via a conventional hot-injection method [3]. Our work shows that template-grown CsPbBr₃ NRs are promising materials for optoelectronic applications.

References:

[1] S. Liang, M. Zhang, S. He, M. Tian, W. Choi, T. Lian, and Z. Lin, Nat. Synth. 2, 719-728 (2023).

[2] E. Avila-Lopez, S. Liang, I. Elias, Z. Lin, and Y. S. Li, submitted (2023).

[3] Y. S. Li, S. Liang, T. Trieu, R. R. Bautista, and Z. Lin, ACS Appl. Energy Mater. 5, 4431-4438 (2022).

    

Optoelectronic Signatures of Photo-Induced Polarons in Two-Dimensional Lead Chloride Perovskites

Lead halide perovskites are of interest for light-emitting and photovoltaic applications due to the tunability of their bandgap across the visible and near-infrared spectrum coupled with efficient photoluminescence quantum yields.  Coupling of the photo-induced charges to the soft perovskite lattice is suspected to form large polarons, which are expected to show reduced interband radiative relaxation and longer non-radiative lifetimes.  Here we use ab Initio atomistic modeling to investigate polaron photophysics. Simultaneous negative and positive polarons are modeled within the perovskite layer analogous to a photoexcitation.  Spinor Kohn-Sham orbitals are used for the electronic basis and include relativistic corrections and the spin-orbit coupling interactions.  Nonradiative relaxation of the excited polaronic states are computed in terms of Redfield theory by propagating the excited-state reduced density matrix for electronic degrees of freedom weakly coupled to a heat bath. Nonadiabatic couplings between electronic and nuclear degrees of freedom, computed ‘on-the-fly’, are used to parametrize the rates of population transfer.  Einstein coefficients for spontaneous emission is used to compute the radiative relaxation rates of charge carriers.  Here we develop evidence that will improve the understanding of polaron dynamics in lead halide perovskites and their implications for radiative and nonradiative recombination.   

Variation of Carrier Mobility in Metal-Halide Perovskite Thin Films with Stoichiometry

Carrier mobility and frequency-dependent conductivity measurements probe the quality of photoconductive thin films. We use ultrafast THz spectroscopy to measure carrier mobilities in lead-halide perovskite films produced by vapor phase deposition and spin coating. Initial results show a strong dependence of carrier mobility on film stoichiometry.    A subset of samples also show suppressed conductivity at frequencies below 1THz suggesting partial carrier localization. Our optical pump/THz probe measurements determine effective mobilities from the ratio of light-induced change in conductivity to absorbed photon flux.  Film stoichiometry was determined from IR and THz spectroscopy and X-Ray diffraction measurements.  AFM was used to probe film structure.  The authors acknowledge technical support from Prof. Aaron Massari, Dept. Chemistry, University of Minnesota.    

Structure-Property Correlation and Strong Electronic Cross-Talk in Low Dimensional Metal Halide Hybrids

Low dimensional (2D, 1D, 0D) metal halide hybrids, supporting strongly bound excitons, show narrow band edge and broadband self-trapped excitonic (STE) emission. In the absence of general guidelines to enhance this broadband emission, structure-property correlation can be beneficial in designing highly emissive materials. This talk will highlight the fundamental factors that control the emissive properties of main group ns² metal halide based low dimensional (1D, 0D) hybrids. Our current results on utilizing doping strategy for the synthesis of multi-metallic halide hybrids that manifest interesting photo-physical properties and structural control will be showcased. Effects of electronic interaction between the metal halide units in such multi-metallic low dimensional hybrids will be highlighted. Mechanism of the electronic cross-talk between the isolated metal halide units in such systems will be discussed. Utility of such multi-metallic halide hybrids for anti-counterfeiting and negative thermal quenching applications will be highlighted. The talk will conclude with outlook of our current research work highlighting the existing issues in white light emission using main group low dimensional metal halide hybrids.   

Engineering Lead-Free Hybrid Halide Perovskite Quantum Wells

Halide perovskites are a relatively recent class of semiconducting materials that have caught the attention of many owing to their excellent optical and electronic properties. While lead-based perovskites still attract the most attention, concerns about their toxicity have made it vital to examine alternative materials systems (e.g., tin-based perovskites). Lower-dimensional tin perovskites have a higher degree of tunability and better stability compared to their 3D counterpart. However, most organic ligands incorporated in 2D perovskites are electrically insulating and hinder charge transport in the materials. Here, we design and synthesize novel semiconducting ligands for 2D tin perovskites to demonstrate precise energy level alignment between the organic and inorganic layers. Functionalizing the ligand with different donor and acceptor groups help finetune the bandgap and improve charge transfer in the perovskite. Based on the positioning of the levels, the ligands aid in either funneling the charge carriers to one layer or efficiently separating them. As a result, devices made with tin perovskites containing the novel ligands can be made comparable to the impressive performance of lead-based devices making them a viable alternative.   

First-principles calculations of optical properties and defect structures of Ge-alloyed Sn perovskites

Solar cells using methylammonium lead perovskite as a solar cell light absorbing material have achieved an astounding 25.5% conversion efficiency improvement, equivalent to silicon solar cells as of 2023. There are concerns about the toxic effects of lead in perovskite solar cell materials on human health and the environment, and there is an urgent need to completely replace lead with a more inert metal. In this study, optical properties and defect structures of double perovskite solar-cell materials in which lead is replaced by tin and germanium are analyzed by first-principles calculations to evaluate and design novel lead-free perovskite materials.  First-principles calculations were performed using the Vienna ab initio package (VASP) with PBE and HSE06 for the functional.  In the level diagram of defects of Cs₂SnGeI₆, many defect levels appeared in the band gap, but the formation energies of many of them were found to be high and difficult to generate. The V_Sn(-/0) and V_Ge(-/0) defects appearing near the VBM and CBM are considered to be defects that trap photogenerated carriers and reduce the conversion efficiency (V_Sn(-/0) refers to defect levels that ionize at the Sn vacancy site). The formation energies of these defects are strongly dependent on the chemical potentials of the constituent elements (Sn, Ge, and I), and defect formation can be controlled by changing the crystal growth conditions (chemical potentials). Optical properties of Cs₂SnGeI₆ will be discussed in the poster.

    

Phonon Lifetimes and Mode Softening in Cubic Cs2AgBiBr6

The best-performing Hybrid organic-inorganic metal halide perovskite (HOIP) devices contain toxic lead, resulting in a search for lead-free perovskite formulations. One promising lead-free archetype is the double perovskite A2BIBIIIX6 formulation, with Cs2AgBiBr6 reported to have a device-relevant 1.95 eV bandgap. [1,2,3] Recent anharmonic lattice dynamics calculations have suggested that the phase transition in Cs2AgBiBr6 proceeds by the condensation of a soft, zone-center optical phonon. [4] Raman scattering studies have not identified this phonon in the cubic phase, therefore no experimental confirmation of the phenomenon exists. [5] 

In this work, we use inelastic neutron scattering to characterize the acoustic and low-energy optical phonons modes. The acoustic phonon energies identified from constant Q-scans match well with room temperature phonon dispersions calculated from fully anharmonic first-principles lattice dynamics. [4] Compared to the prototypical HOIP, MAPI, Cs2AgBiBr6 acoustic modes exhibit a larger group velocity and longer lifetime, resulting in a longer phonon mean free path (MFP). We propose that the acoustic modes are the dominant contribution to the thermal conductivity in Cs2AgBiBr6. We also confirm the presence of a zone-center optical soft mode and track the temperature dependence. Ultimately, this work helps to understand the free charge carrier properties in double-perovskite CsAgBiBr6 which are largely governed by electron-phonon interactions.   

Lithography of complex topological structures in ferroic materials

Arbitrary polar rotation in oxide perovskites and spontaneous flux closure domain formationwithin a single material is rarely observed due to the high anisotropy energy inherent to ferroelectrics. Purelyphysical rotation of polarization has only been achieved by flexoelectricity, i.e., structural strain gradients,taking advantage of the coupling of ferroelectric and ferroelastic properties or depolarization field engineeringin thin film heterostructures, which combine ferroelectric and dielectric layers leading to curling behaviour of polarization and the creation of vortices-like structures. Non-trivial topological structures have been discoveredin confined ferroelectric layers within artificially engineered superlattices, altogether providing promisingalternatives for nanoelectronic devices based on negative capacitance, or fast broadband communicationsrequired for the 6G era thanks to intrinsic sub-THz resonances. However, examples on the manipulation ofthese topological structures is scarce and only few of them have been created via electric field litography sofar. Here, we will show advanced ferroelectric lithography methodes that will allow the creation of complextopological structures such as skyrmions, vortices and flux closures on demand.   

Dynamics of the electrocaloric effect: high-resolution measurements on microsecond timescales

The electrocaloric effect (ECE) in ferroelectrics is a promising candidate for improved cooling technologies and small cooling devices. While direct and reliable measurements of the reversible adiabatic temperature change ΔT as a caloric key parameter are already challenging, an access to the full dynamics ΔT(t) of the ECE and the correlation with the ferroelectric properties are highly desirable for a more fundamental understanding of the ECE.

Here, we present a direct and contactless method to investigate the temperature change ΔT(t) of the ECE with mK temperature resolution and μs temporal resolution via the infrared emission of the sample. Ferroelectric properties are simultaneously recorded. Measurements on material systems with a first order and a diffuse phase transition, respectively, show characteristic changes of the field dependence of the ECE as fingerprints of the order of the phase transition. Systematic studies of the frequency dependence of the ECE allow, e.g., to separate extrinsic effects like heat transport from the pure caloric temperature change. High-frequency measurements up to kHz further allow the direct measurement of ΔT even for μm thin samples.   

Ultrasound Pulse Echo Study of KLT

We explore the development of relaxor ferroelectric order in single crystals of K_1-x1Li_iTaO₃(KLT) with x = 0.01, 0.1, 0.2. The phase transitions occur upon cooling the crystal either spontaneously or under an electric field. We probe the sample by sending 1 µs-long 30 MHz ultrasound probe pulses and receiving their echoes. From this, we obtain the temperature dependence of speed and attenuation of ultrasound, i.e., information on elastic properties and polar clusters structure. The details of the experiment and current results are presented. Our goal is, through a comprehensive study of the elastic properties of this relatively simple material, to develop a model of the relaxor ferroelectric transitions that would be applicable to more complicated compounds.    

Electronic and magnetic properties of metallic quantum multiferroic EuTiO3-δ

EuTiO₃ has drawn interest in recent years, as it exhibits paraelectricity similar to SrTiO₃ and KTaO₃. Moreover, this insulating perovskite is a candidate quantum multiferroic, as it exhibits antiferromagnetic (AFM) order below T_N ~ 5.5 K; potential ferroelectric and magnetic quantum critical points might be reached by alloying and/or strain-tunning. Furthermore, prior theoretical and experimental studies of metallic EuTiO₃ have shown that carrier-doping can tune the ground-state spin configuration from AFM to ferromagnetic (FM). Considering the possible connection between ferroelectricity and superconductivity proposed for SrTiO₃, a search for superconductivity in metallic EuTiO₃ is of considerable interest. Here, we present a novel annealing technique to introduce oxygen vacancies and, hence, metallicity in floating-zone-grown insulating EuTiO₃. We leverage charge transport, magnetization, and x-ray diffuse scattering measurements to investigate the electronic properties of doped EuTiO₃, specifically: the cross-over between AFM and FM ground states, searches for superconductivity and multiferroic quantum criticality.   

Localized excitons in a proximitized moiré lattice

We report the observation of localized excitons in a monolayer MoSe2 when placed in the proximity of a moiré lattice formed via twisted hBN layers. When hBN is twisted with a small angle, it forms a moiré pattern with alternating potential domains at the interface. This potential difference can be used to control the properties of excitons located on the surface of the hBN. We demonstrate this effect by placing a monolayer of MoSe2 on the twisted hBN with varying twist angles. The presence of the underlying moiré potential results in the photoluminescence of excitons in MoSe2 blue shifting indicative of confinement effect. Using a Kelvin probe force microscope(KPFM), we observed potential modulation on the MoSe2 of ~ 40 meV at 4K.   

Real-time growth monitoring of oxygen plasma enhanced ZnO atomic layer deposition using in-situ spectroscopic ellipsometry

In this study, we use in-situ SE to monitor the real-time growth of ZnO ultrathin films fabricated by atomic layer deposition, where Zn(CH₃)₂ organometallic precursor and oxygen plasma serve as the main reactant and co-reactant, respectively. A simplistic model so-called dynamic dual box model is proposed to establish an extensive understanding of the cyclic surface modifications and the continuous growth mechanisms of ZnO thin films [1]. This makes it possible to develop reliable ALD recipes in-situ. We were able to collect in-situ SE data while growing ZnO ultra-thin films within the spectral range of 0.7-3.4 eV at a 67.9° angle of incidence. Additionally, we project that the model may be used to assess in-situ SE data that was collected during the deposition of different oxide materials. The effect of temperature on growth rate is studied to untangle its role in the thickness gain per cycle. Complementary crystallographic, chemical, and morphological investigations were performed by using x-ray diffraction, x-ray photoelectron spectroscopy, and atomic force microscopy, respectively.

References:

[1] Kilic, Ufuk, et al. "Precursor-surface interactions revealed during plasma-enhanced atomic layer deposition of metal oxide thin films by in-situ spectroscopic ellipsometry." Scientific reports 10.1 (2020): 10392.   

Electron-phonon coupling at complex grain boundaries in single layer MoS2

Electron-phonon coupling is an intrinsic interaction in semiconductors that helps define the temperature dependence of optical band gaps. The coupling constant strongly depends on electron and phonon dispersions in the material, which should change in the presence of planar defects. While grain boundaries generally are the result of uneven growth during crystallization of individual grains, they often can be tailored in particular orientations to design materials with better electric current mobility and intragranular thermal transmission. Hereby, we use a CryoRaman microscope to perform low-temperature measurements from 4K to room temperature using site-selective optical spectroscopy in single-layer MoS₂ to analyze the exciton decay rate as a function of their momentum. Simultaneously, we acquire the active Raman modes to probe the bonding covalence and calculate the phonon energy. Lastly, since mirror and tilt boundaries vary in the localized mid-gap states at the faceted interface, we employ aberration-corrected transmission electron microscopy (TEM) to correlate spectroscopic identities with alpha and beta defects along boundaries. This work details a step forward in energy harvesting of polycrystalline 2D materials for thermoelectric and optoelectronic devices.   

Steep Slope Threshold Switching Field-Effect Transistors Based on 2D Heterostructure

In dealing with the increasing power dissipation of electronic systems with increasing integration density, field-effect transistor (FET) with steep switching slope that overcomes the thermionic limit is vital to achieve low-power operations. Here, we report two types of threshold switching (TS) FETs based on 2D van der Waals heterostructures by virtue of the abrupt resistive switching of the hexagonal boron nitride (hBN) TS device. The common hBN dielectric layer functions as the switching medium for the TS device and the gate dielectric for the 2D FET enabling seamless integration of the hBN TS device and baseline 2D FET. TSFET in source configuration by connecting the TS device to the source terminal of the 2D FET offers an ultralow subthreshold swing (SS) of 2.2 mV/dec across six decades of drain current at room temperature and suppressed leakage current. In addition, the threshold voltage can be modulated by changing the drain voltage due to voltage division between the FET and TS device. TSFET in gate configuration by connecting the TS device to the gate terminal of the 2D FET also exhibits steep switching slope with ultralow SS of 3.5 mV/dec. The proposed compact device structures integrating 2D FET and TS device provide a potential approach of monolithic integration toward next-generation low-power electronics.   

Crossroad quantum dots in Graphene

In this study, we present the fabrication and characterization of quantum dots (QDs) based on a cross-road structure where geometric confinement and the specific cross-road architecture are expected to lead to two discrete electronic states separated from a continuum [1,2]. These QD devices are fabricated from few-layer graphene films with the help of e-beam lithography technique aiming at widths of the individual graphene ribbons of about 80 nm. The resulting structures exhibit novel properties that we investigate through electric transport measurements, allowing us to probe the energy levels within these devices. The combination of graphene's high carrier mobility with the geometrically tunable level spacing of the QDs offers a promising platform for diverse quantum device application. This research advances our understanding of low-dimensional QD systems and paves the way for the development of next-generation quantum technologies.

 

Financial support by the National Science Foundation through EPSCoR RII Track-1: Emergent Quantum Materials and Technologies (EQUATE), Award OIA-2044049 is acknowledged. The research was performed in part in the Nebraska Nanoscale Facility: National Nanotechnology Coordinated Infrastructure and the Nebraska Center for Materials and Nanoscience, which are supported by NSF under Award ECCS: 2025298, and the Nebraska Research Initiative.

 

[1] R. L. Schult, D. G. Ravenhall, and H. W. Wyld Phys. Rev. B 39, 5476(R) (1989)

[2] A F Sadreev 2021 Rep. Prog. Phys. 84 055901 DOI 10.1088/1361-6633/abefb9

    

Electronic Transport Properties of Two-Dimensional Violet Phosphorus-11

Violet Phosphorus (VP) is a 2D layered intrinsic p-type semiconducting Phosphorus allotrope. Because most known 2D semiconductors are n-type, finding new intrinsic p-type structures will allow for the further development of complementary n-p architectures and p-electronics without requiring doping of the material. This work explores the electrical properties of Violet Phosphorus-11 and its in-air degradation. Mechanical exfoliation of violet-P11 into few-layer-thick flakes was performed in a controlled atmosphere of inert gas. From these flakes, Field-effect Transistors (FETs) were built using Hall Bar geometry to calculate mobility and resistivity as a function of hole density in a cryostat. Atomic Force Microscopy then showed that violet-P11 experiences large area degradation faster than previously reported. A better understanding of VP's stability will help in the material's electric characterization and potential applications.   

Photo induced oxidation in WX2 monolayers

Monolayer transition metal dichalcogenides (TMDs) have emerged as promising materials in the realm of two-dimensional (2D) materials due to their potential applications in microelectronic and optoelectronic devices. To delve into their properties, this study employs Van der Waals-corrected density functional theory (DFT) for first-principles calculations. Specifically, it focuses on a detailed analysis of the adsorption and dissociation of O₂ and O₃ molecules on a monolayer of WX₂ monolayers. Utilizing a combination of density functional theory (DFT) and the climbing image nudged elastic band (CI-NEB) approach, this research conducts extensive calculations to elucidate the minimum energy path associated with the oxidation mediated by O₂ and O₃. This approach aims to uncover the energetically most favorable route for the oxidation of the monolayers by O₂ and O₃. The insights gained from these computational techniques are crucial for understanding the underlying mechanisms and kinetics of the oxidation process, thereby facilitating a deeper comprehension and potential optimization of such reactions in TMD monolayers.   

New 2D Semiconductors with Ultra-High Mobility at Room Temperature

Two-dimensional semiconductors have demonstrated great potential for next-generation electronics and optoelectronics, however, the current 2D semiconductors suffer from intrinsically low carrier mobility at room temperature, which significantly limits their applications. Here we discover a variety of new 2D semiconductors with mobility 1 order of magnitude higher than the current ones and even higher than bulk silicon. The discovery was made by developing effective descriptors for computational screening of the 2D materials database, followed by high-throughput accurate calculation of the mobility using a state-of-the-art first-principles method that includes quadrupole scattering. The exceptional mobilities are explained by several basic physical features; particularly, weak electron-phonon coupling strength   

Luminescence and Photochromic Properties in Eu3+-Doped K0.5Na0.5NbO3

K_0.5Na_0.5NbO₃ (KNN) has been widely used as a representative of lead-free ferroelectric perovskite materials. We investigated the luminescence and photochromic properties in Eu³⁺-doped KNN. X-ray diffraction and Rietveld refinement analyses revealed the lattice structures for KNN was to exhibit a mixed phase of orthorhombic, and tetragonal. The intensity of the photoluminescence (PL) was maximized at the Eu³⁺ doping concentration of 5%, which is in good accord with the structural properties of KNN. We also noted variations in PL intensity attributed to the photochromic properties of KNN. The diffuse reflectance in the visible light range has decreased by 17.6% after ultraviolet irradiation, and the PL intensity decreased by 68%. These changes could be restored up to 99% upon heating.   

Modification of Surface Photovoltage Response in Microcrystalline β-Ga2O3 Due to Remote Plasma Treatment

β-Ga₂O₃ has attracted recent attention due to potential uses in critical areas such as high-power/high frequency telecommunication devices, next generation solar cells, biological therapeutics, etc. Nano- and microcrystalline specimens are of particular interest for budding applications. Thus, there exists a need for both facile synthesis and thorough characterization of these materials. We produced β-Ga₂O₃ microcrystals with controlled morphologies via a simple bottom-up hydrothermal method: first precursor GaOOH samples were synthesized, which then underwent a subsequent calcination, leading to the final product. Surface electronic structure and charge dynamics of the obtained materials were probed via both time- and energy-dependent surface photovoltage (SPV) conducted prior to and following a remote plasma treatment (RPT). Our findings agree with theoretical predictions for sub-bandgap states and quantify the related surface charge dynamics. We also demonstrate successful modification of these states following RPT.   

Excitonic Resonance Raman features of magnetron sputtered WSe2

In this study, magnetron pulsed DC and DC/ RF sputtered tungsten diselenide (WSe₂) thin film, grown anisotropically along its c-plane as measured by XRD, studied using Raman spectroscopy at several excitation energies including 1.57 eV, 2.33 eV, and 2.86 eV will be presented. The characteristic WSe₂ phonon modes of E_2g¹ and A_1g at ~247 cm­^-1 and ~251 cm^-1 were resolved using linearly polarized backscattered Raman configuration. Circularly polarized Raman is also used to verify and resolve E_2g¹ and A_1g peaks. Under a specific laser irradiation wavelength of 785 nm (1.57 eV), a new Raman peak E_1g appeared at ~176 cm^-1 and exhibited excitation energy dependence. Resonance with exciton energy A leads to this E_1g Raman active but forbidden peaks to be observed in backscattered Raman configuration, suggesting broken selection rules in the crystal. Also, second-order phonon mode intensity is enhanced, and A_1g mode selectively improved with 1.57 eV excitation, which is close A exciton energy. At B exciton energy, Raman peak at 310 cm^-1 appeared, which is Raman inactive. These features in the Raman spectrum are interpreted as the strong resonance with exciton energies. This study addressed the fundamental fingerprint of excitonic resonance Raman phonon modes in layered transition metal dichalcogenides.   

Lanthanide-Doping of Inorganic Tin Clathrates Grown with Flux

Thermoelectricity – the ability to convert heat to electricity – has competing mechanisms that determine the effectiveness of a thermoelectric material and one way of enhancing it is to have weakly bound atoms rattling in cages, scattering phonons. Clathrates comprise cavities formed usually by p-block elements in which heavier atoms reside. Rare-earth doping has been shown to enhance the thermopower in clathrates comprising gallium, silicon and germanium. Here we report on the growth and characterization of lanthanide-doped tin-comprising clathrates of the form RExAE8–xGa16Sn30, grown with the Sn-self flux technique.   

Fabrication of Reactive Sputtered Deposited Cu-MoS2 nanoworm thin film for NO2 gas sensor

NO₂ is one of the most common atmospheric air pollutants causing lung, respiratory, and cardiovascular disease even at low concentrations. It originates mainly from vehicle emissions, burning of fossil fuels, and industrial production of nitric acids, and is a major threat to the human as well as the ecosystem. Therefore, the development of a highly sensitive and selective sensor for efficient detection of NO₂ is necessary for the well-being of human health and the environment. In the present work, we report the controlled synthesis of Cu-functionalized MoS₂ nanoworm thin films based on NO₂ sensors using a reactive co-sputtering technique. Structural and surface morphological properties were studied using XRD and FESEM analysis, respectively. The study of surface chemistry and defects of as-prepared samples was carried out using X-ray photoelectron spectroscopy and photoluminescence spectroscopy, respectively. The sensing performance of pure MoS₂ and Cu-MoS₂ thin films was studied towards nitrogen dioxide (NO₂) gas concentrations (2-200 ppm) at the optimum working temperature of 100°C. The Cu-MoS₂ sensor provides a high sensing response as compared to the pure MoS₂ thin-film sensor towards 20 ppm of NO₂ gas with a fast response and recovery time. The Cu-MoS₂ thin-film sensor is highly sensitive, stable, and selective towards NO₂ against NH₃, CO, and H₂ gases. The as-prepared 2D MoS₂ thin-film-based sensor, owing to its remarkable performance, might be used for low detection of NO₂ under a low working temperature regime.   

Non-linear transport in high-mobility 2D electron gas in very high Landau levels under sub-GHz excitation

Microwave-induced resistance oscillations (MIROs) occur when a 2D electron or hole gas is subjected to microwave radiation and weak magnetic field (B), such that the cyclotron frequency is smaller than the radiation frequency. Here, we report on experiments in the opposite limit, in which the cyclotron frequency greatly exceeds the frequency of radiation. In this regime, our measurements reveal another class of photo-resistance oscillations which, like MIROs, are periodic in 1/B. However, unlike MIROs, whose period is governed by the radiation frequency, the period of the oscillations under study is controlled by the radiation intensity.   

Anisotropic electronic transport properties in boron carbide films

Boron carbide films combine a large absorption cross-section for thermal neutrons and semiconductor properties making them ideal for portable, lightweight solid-state neutron detectors. Most basic sciences studies and device architectures have focused on diodes, current perpendicular to plane geometry, and DC detection schemes. In this talk, I will show that the presumed isotropic electronic transport in boron carbide films fades with increasing frequency. AC electronic transport measurements in the kHz regime revealed a sizable anisotropy and inhomogeneity in both out-of-plane and in-plane geometry that hints at a structural/chemical inhomogeneity, which could be exploited for directional charge flow.   

Engineering the Spin Transition and Carrier Type with High-Entropy Lattice Distortions in Rare Earth Cobaltates

There is growing interest in material candidates that provide knobs to tune their properties beyond traditional limits. Compositionally complex oxides, often called high entropy oxides, are excellent candidates, wherein a lattice site shares more than four cations, forming single-phase solid solutions with unique properties. Here, we demonstrate compositional complexity as a tunable parameter in a spin-transition oxide semiconductor La_1-x(Nd,Sm,Gd,Y)_xCoO₃, by varying the population x of rare earth cations.  As the compositional complexity increases with x, localized and uniform lattice distortions occur that have profound effects on the material’s semiconductor-to-metal spin transition and carrier type. Experimental measurements, together with first-principles calculations, demonstrate that atomic-range distortions from the varying rare earth radii induce a crossover from hole-majority to electron-majority conduction at x = 0.8 without the introduction of electron donors. Thus, we show that control of localized lattice distortions through compositional complexity is a facile knob to tune oxide semiconductors and spin transitions beyond traditional means.   

Three-dimensional atomic structure of amorphous solids

Amorphous solids are ubiquitous in our daily life and have widespread applications in science and technology. However, owing to the lack of long-range order, the 3D atomic structure of amorphous solids has eluded direct experimental determination. This fundamentally limits our understanding of the structure and properties of amorphous solids. Here, we perform atomic electron tomography (AET), a 3D reconstruction technique, which does not assume crystallinity [1,2], to determine the 3D structure of amorphous solids at the single-atom level. By reconstructing the 3D atomic coordinates of a multi-component metallic glass, we observe that several short-range order structures interconnect to form medium-range order, supporting efficient cluster packing models for metallic glasses [3]. Furthermore, we decipher the atomic packing of monatomic amorphous solids with liquid-like structure [4]. In contrast to Frank’s hypothesis that the most common motifs in monatomic liquids are icosahedra [5], we observe pentagonal bipyramid networks which give rise to medium-range order. Future work will utilize AET to probe the 3D structure and dynamics of amorphous-crystalline phase and glass transitions at the single-atom level.

1. M. C. Scott et al. Nature 483, 444 (2012).

2. J. Miao P. Ercius, S. J. L. Billinge, Science 353, aaf2157 (2016).

3. Y. Yang et al. Nature 592, 60 (2021).

4. Y. Yuan et al. Nature Materials 21, 95 (2022).

5. F. C. Frank. Proc. R. Soc. Lond. A 215, 43 (1952).   

Phases Control of Epitaxial MnTe through Buffer Layers

MnTe is one of the 3D semiconductors that can exhibit anomalous Hall effect. The potential edge states correlated with the alter-magnet properties especially in the α-phase MnTe is also under study these days. The epitaxial growth becomes one method to tune the electronic structure. In this work we have grown both α-phase and β-phase MnTe by Molecular Beam Epitaxy on GaAs (111) and sapphire (0001) substrates with different buffer layers.

 

While in bulk crystal MnTe α-phase is the most stable state at room temperature, in the epitaxial structure β-phase MnTe can also be achieved in the as-grown thin films without post-growth annealing. On GaAs (111) substrates α-phase MnTe are naturally favored without any buffer layer. When using Bi₂Te₃ series TI (topological insulators) the buffer layers on sapphire (0001) substrates, we found out that β-phase MnTe are favored on pure Bi₂Se₃ due to the smaller lattice mismatch. However, when we add some alloy effect to the buffer layer, though the lattice mismatch is still smaller in β-phase, α-phase is actually grown. This unveil the role of the entropy effect and the changed in the surface potential. The nanorods structure in MnTe α-phase can also be controlled by buffer layer control and a CrSe_x layer under it.   

Quantum logic gate analysis for Rabi oscillation driven by a time-dependent Rashba external field

 We study time-dependent (TD) spin phenomena driven by oscillating Rashba spin-orbit interaction (SOI). An electron is confined by a harmonic potential surrounded by a cylindrical hard-wall in a two-dimensional quantum dot (2DQD). An oscillating Rashba external field with a frequency w is applied perpendicular to the 2D plane. We numerically solve the corresponding TD Schödinger equation by employing the real-time, real-space finite difference method. We conduct projection and Fourier transform analyses and investigate the Rabi oscillation caused by the resonant interstate transitions.

 The harmonic confinement ω₀ produces eigenstates with equivalent energy separation. Consequently, the Rashba external field (w= ω₀) produces an infinite number of interstate resonant transitions. The selection rule requests an alternating spin-change between the individual transitions. Eventually, the multiple inter-neighboring-state (INS) transitions result in the complicated spin flip-flopping. Because the predominant INS coupling occurs between the ground and first-excited states, we remake the resulting spin-flip process between these two states and then draw it on the Bloch sphere. Thus, two-state Rabi oscillation driven by the Rashba SOI is expressed by the basic logic gates. By combining these gates, we restudy the complicated spin dynamics confined in the harmonic and cylindrical hard-wall hybrid potential.   

Singlet-triplet instability for multi-electron system confined by a harmonic potential in a two-dimensional quantum dot―generalized unrestricted Hartree–Fock approach with the real-space finite difference method―

An electron confined by the harmonic potential in a two-dimensional quantum dot (2DQD) provides the QD orbitals characterized by the radial n and angular l quantum number. Rashba electric field (Ξ) breaks the structure symmetry, and then resolves spin degeneracy in each QD state via spin-orbit interaction (SOI). However, the applied Ξ direction (zenith angle θ) varies the resolved separation D from zero (in-plane direction,(θ=π/2) to maximum (θ=0). Focusing on this directional feature, we study the singlet-triplet (ST) instability for the multi-electron system driven by the Rashba field.

Since the Rashba SOI couples opposite spin states, we use the generalized unrestricted Hartree–Fock (GUHF) approach. We solve the GUHF equation using the real-space finite-difference method. The single-particle first-excited states (n, l) = (0,±1), e.g., conserve spin degeneracy when X is applied in the in-plane direction. Thus, a four-electron system is expected to produce a ground-state triplet. As θ decreases, the Rashba SOI increases the energy separation Δ. However, until the exchange energy overcomes the single-particle excitation energy Δ, the ground-state triplet will remain. We explore the ST instability by varying θ and the harmonic confinement potential ω₀  for different numbers of electrons and reveal the ground-state spin-multiple phases of multi-electron systems.   

Antiparticle of exciton in semimetals

An emergent quantized field enriches quantum many-body systems. We propose an antiparticle analog of the exciton in semimetals as an emergent collective mode in interacting electron systems. We show that inter-band excitations in semimetals are generally comprised of both excitons and antiparticles of excitons. These two stand for two distinct inter-band collective modes in semimetals, having different energies and opposite conserved charges. The conserved charge here is a quantity conjugate to a joint U(1) symmetry of two electron's bands associated with the inter-band excitations. The opposite charges foster fertile scattering processes among the inter-band collective modes. In spin-polarized systems, they also suggest possible experimental detections of the antiparticles. We clarify that the effective theory of the inter-band excitations is given by a generalized Klein-Gordon theory. Our theory provides a comprehensive understanding of excitonic spectra in generic semimetals, bringing a new insight into electronic collective phenomena in solids.   

Variations in the Electronic Band Structures of Photothermalcatalytic Materials

Photothermal catalytic layered semiconductor-based devices have significant potential to efficiently perform overall water splitting, creating an alternative to fossil fuels. The electronic structure at the interfaces between layers plays a vital role in device effectiveness, but for the many possible combinations of material layers that electronic structure is unknown. In this poster we present theoretical electronic structure calculation results that demonstrate the degree of variability in layer-to-layer band gap, valence band edge, and conduction band edge that a prototypical sulfide-based semiconductor device would need to support when operating at elevated temperature.

Investigating bulk material variations at elevated temperatures will bracket the influence of thermal expansion on the electronic structure. To compare the band structures of the different materials we employ a single unified high-symmetry path in the Brillouin zone for all crystal types through all stages of thermal expansion. This sheds light on the thermal stability of layered semiconductor-based devices and provide insight into maintaining optimal electronic properties for water splitting applications.   

Photoluminescent from defects in isotopically enriched hexagonal boron nitride.

The hexagonal Boron Nitride (h-BN) has attracted significant attention due to its unique properties that enable advanced optoelectronic device fabrication. It has also been studied as a host of single photon emitters (quantum light emitters) like other two-dimensional materials. To better understand the electronic properties and lifetime of photoluminescence (PL) in hBN, we use photoluminescence (PL) and time-resolved photoluminescence (TR-PL) spectroscopy. Our observations indicate that narrow-width PL emission in the spectral region between 693 and 698 nm occurs at room temperature from states in the bandgap of hBN. These states may originate from lattice-embedded carbon atoms, which can potentially act as quantum light emitters that can be used for quantum technology applications.   

Heterojunctions in Cryogenic Conditions: Quantum and Operational Analysis

Various advances in condensed matter physics and computer engineering have rendered a fully comprehensive and intrinsic understanding of the behaviors of most common semiconductor heterojunctions, especially as it pertains to their respective electrodynamics on the quantum scale. Thus, the present study interpolates the material and operational understandings of semiconductor heterojunctions into cryogenic settings via observations previously published in journals and subsequent physical analysis of these findings. Subsequent theoretical and statistical analysis will then follow suit so as to render an exploratory image of future semiconductor technology. Comprehensive thermodynamic understanding of heterojunction behavior in extreme conditions could lead to interesting developments in semiconductor physics, condensed matter physics and potential application to quantum computing hardware.   

Polymer Donors Capable of Hydrogen-Bondings Enable Efficient and Stretchable Organic Solar Cells

Intrinsically stretchable organic solar cells (IS-OSCs) announced the new generation of wearable power sources. However, popular active materials are brittle, limiting its stretchability. Here, we develop highly efficient and durable IS-OSCs, by a new polymer donor (P_D­s, PM6- PhAmX (X=0, 3, 5, and 10)) capable of hydrogen-bonding (H-bonding). The incorporation of phenyl amide spacer (PhAm-FS) into the P_Ds increases the stretchability by enhanced molecular interaction from H-bonding. Consequently, the high power conversion efficiency (PCE, 17.5%) and crack onset strain (COS, 13.8%) were demonstrated in the PM6-PhAm5:Y7 blend, outclassing than PM6:Y7 blend (PCE = 15.5% and COS = 1.8%). More importantly, the IS-OSC based on the PM6-PhAm5:Y7 blend achieves the highest PCE (12.62%) among the reported IS-OSCs, and demonstrates outstanding stretchability.   

Chiral phonons in right- and left-handed quartzes investigated by circularly polarized Raman spectroscopy

 Recently, chiral phonons have attracted much attention [1-5] in chiral materials. Chiral phonons have angular momentum, corresponding to lattice vibrations with rotating atomic displacements [1]. It is known that the rotation direction of the plane of linear polarization owing to optical activity is opposite in right- and left-handed chiral crystals. Analogous to optical activity, the angular momentum and propagation direction of chiral phonons are expected to be opposite in right- and left-handed chiral crystals. It was recently reported theoretically that chiral phonons belonging to certain branches of α-quartz can only propagate in either the positive or negative direction of the crystal axis [3]. Therefore, investigating chiral phonons in the chiral crystals is important for controlling their angular momentum and propagation direction. However, there are few reports of chiral phonons in crystals with different chirality. 

 We performed circularly polarized Raman spectroscopy on the right- and left-handed quartzes at room temperature. In our presentation, we will report the details of experimental results and discuss the conservation laws to be satisfied in the Raman scattering by chiral phonons.

[1] L. Zhang and Q. Niu, Phys. Rev. Lett. 112, 085503 (2014).

[2] J. Kishine et al., Phys. Rev. Lett. 125, 245302 (2020).

[3] H. Chen et al., Nano Lett. 22, 1688 (2022).

[4] E. Oishi, Y. Fujii, and A. Koreeda, arXiv: 2210.07526 (2022).

[5] K. Ishito et al., Nat. Phys. 19, 35 (2023).   

Injection current spectroscopy in magnetic Rashba semiconductor (Ge,Mn)Te by mid-infrared excitation

Toward the realization of a resilient society, photoelectric conversion has been constantly explored in order to use them as renewable energy sources. One scenario of photoelectric conversion strategy would be utilizing bulk photovoltaic effect in materials lacking inversion symmetry. One mechanism responsible for such photovoltaic effect is injection current, originating from asymmetric optical excitation at ± k points in the momentum space. Such excitations can be realized in a lifted band symmetry through the Zeeman effect on spin-split bands, or in the presence of Berry curvature dipole with a circular optical excitation. This nonlinear optical effect has attracted renewed attention due to its quantum geometric origin, i.e., Berry curvature as their source. To maximize the yield of photocurrent, now it is proposed to utilize the diverging geometric phases at the Dirac points. We employ thin films of GeTe with giant Rashba-type spin splitting doped with Mn. The Fermi level can be tuned near the Dirac point of the valence band by growth condition. Photocurrent spectroscopy in the mid-infrared region reveals that a large zero-bias photocurrent appears normal to the in-plane external magnetic field B, which reverses its sign upon the reversal of B, consistent with the selection rule of injection current. In this presentation, we will discuss the detailed spectral features with the possible effect of Berry curvature near the Fermi level.   

Schottky Barrier Lowering of Metal/4H-SiC Junction with Ultrathin Aluminum Oxynitride Interlayer

Silicon Carbide (SiC) has been widely investigated to develop high power electronic devices as a reliable wide band gap semiconductor. The electrical characteristics of SiC Schottky diode depend strongly on the interface energy barrier, and a lower Schottky barrier is advantageous to improve power efficiency and acquire fast switching. We report experimentally that the Schottky barrier of metal/4H-SiC junction is reduced significantly with an ultra-thin (down to ~1.0 nm) aluminum oxynitride (ALON) interlayer inserted at the junction interface. The ultra-thin ALON layer was deposited by using the RF magnetron sputtering with the in-situ flashing to remove the native oxide. High-resolution transmission electron microscope (HR-TEM) images confirmed that the grown ALON film was amorphous. The Schottky barriers of metal/ALON/4H-SiC and metal/4H-SiC junctions were obtained by performing current-voltage (I-V), capacitance-voltage (C-V), and internal photoemission (IPE) measurements. The interface barrier was reduced by up to ~0.8 eV and the reduction was not related to the work-function of metal. The electrostatic potential change driven by the fixed charges in the interlayer or the Fermi-level depinning associated with the suppression of metal-induced gap states is generally known as the origin of Schottky barrier modulation with an interlayer. However, the Fermi-level pinning factor was found to remain almost unchanged in our case, implying that the surface states of 4H-SiC are NOT the main factor of the observed Schottky barrier reduction. The fixed positive charges in the ALON thin film are presumed to cause the reduction.   

Bringing the SWIR to Silicon with Upconversion Devices

Infrared imaging, encompassing a spectrum of applications from healthcare to autonomous vehicles, has emphasized the need for advancing Near Infrared (NIR) and Short Wave Infrared (SWIR) detection capabilities. The potential to transform NIR and SWIR photons into detectable NIR photons via upconversion, compatible with prevalent silicon-based cameras, poses a formidable challenge to the current InGaAs sensor-dominated market. This dominance is characterized by intricate fabrication methodologies and heightened device costs, constraining the scalability of imaging solutions in this domain. Our research introduces a paradigm shift through the deployment of solid-state triplet-triplet annihilation upconversion via a charge-transfer state sensitization process. We present a pioneering single-step solution-processed deposition of a bulk heterojunction upconversion film employing organic semiconductors. Demonstrations across varied substrates, including glass and flexible mediums, underscore the versatility and potential of this material system for state-of-the-art upconversion applications.   

Modelling shallow confinement in tuneable quantum dots as a 1D cubic potential

One physical system which realizes the generic model of an electron tunneling through a barrier into and out of a potential well is a tuneable barrier quantum dot. Pushing many of its applications to the limits of their fastest possible operation requires the tunneling of the electron to be as fast as possible which inevitably pushes the dot to the brink of losing its confining properties. The focus of our study is this shallow regime of confinement where the dot can hold a single electron in a single or a couple of discrete states. By considering the one-dimensional cubic potential we hope to describe universal properties of the weakly confined electron that would characterize it independently of the specific device realizing the confinement.

By comparing our cubic model predictions with data counting single electron capture events in dynamically modulated quantum dot experiments we, indeed, confirm universality across multiple dot realizations and driving protocols. Moreover, we show theoretically that the correspondence between the cubic model and experiment should increase with increasing magnetic field. We illustrate this with a comparison to experimental data from precision current sources. Finally, using the cubic potential we develop a model for the temperature dependence of the electron escape rate which is verified by comparison to data from another field of nano-electronics - Josephson junctions.   

Experimental investigation of microwave photons emitted by a quantum point contact

Quantum transport investigates the dynamics of electrical circuits displaying a quantum mechanical behavior. This is achievable by patterning circuits in the nm/um scale in clean room environments, and cooling them at T∼15 mK in dilution fridges. A remarkable aspect of such quantum dynamics is that the electrical current fluctuates, even in response to a strictly DC bias. Detecting these quantum fluctuations is highly informative as it conveys information on the granularity of charge, the statistics of the carriers but also on the characteristic transport times such as the electronic scattering time or on interaction effects.

Our lab has developed several experimental schemes and technics in order to measure efficiently such quantum fluctuations in the few GHz range.  In a qualitative level, measuring at this frequency range f_det∼6 GHz gives access to the quantum optical regime hf_det>>k_BT, where one needs to provide a quantum description not only for the electrical current flowing through the conductor, but also for the electromagnetic fields exchanged with its detection scheme.

In practice, we couple a large frequency bandwidth coil to a quantum point contact (QPC) developed on a 2D electron gas. In the quantum Hall effect regime, this gives rise to a single channel potential barrier with a tunable electronic transmission. Then, we amplify the radiated RF field leaking from the resonator in a HBT geometry and sample it at room temperature, in order to compute its second order coherence function. The final goal of our work is to prove experimentally that photons radiated by the QPC inherit the fermionic nature of the scattering electrons. In other words, radiated photons are antibunched in accordance with theoretical predictions. [1-2]

[1] Beenaker & Schomerus, Phys.Rev.Lett. 93, 096801 (2004)

[2] Hassler & Otten, Phys. Rev. B 92, 195417 (2015)   

First Principles Investigation of Stability, Structure & Properties of Sn-Bi Based Alloys

Development of electronic packaging consisting of 2D, and 3D die-package enhanced interconnects and sensitive optoelectronic components has necessitated a hierarchy of solder materials. This is to accommodate for the different melting points, adhesion characteristics, thermal expansion, and mechanical properties required at each stage. However, there is still a considerable knowledge gap in understanding the structural details at the atomic level of the stable alloy compositions and how thermodynamics drives the stability of the solid solutions, especially for Sn-based alloys. For example, a quick review of the available literature yields a convex hull for the binary SnBi alloy with positive theoretical energies of formation, revealing other thermodynamic drivers playing a significant role in stabilizing the solutions. We use a hybrid approach of first-principles simulation and machine learning to identify thermodynamically and mechanically optimal alloys for low-temperature solder applications. Our study extends the structural database for SnBi-based alloys, mainly focusing on low-concentration Bi systems, and sets a routine for screening stable binary/ternary alloys. We calculate the stability of Sn-Bi, Sn-Cu, Sn-Ga, Sn-Zn binary alloys, and Sn-Ag-Cu (SAC) alloys and calculate their mechanical properties to evaluate their thermodynamic and mechanical stability using first principles. We expect this will contribute to the structural database of SnBi-based alloys, particularly regarding the low-concentration Bi systems in SnBi alloys and other potential candidates for low-temperature solder applications.   

Effect of Pitch and Nanowire Diameter on the Lasing Threshold in InP Photonic Crystal Arrays

Electrically pumped 2D photonic crystal (PhC) lasers have the potential to fulfill the size demands for on-chip coherentlight sources in photonic integrated circuits. In this study, we investigate the effect of the PhC lattice constant (pitch) and the nanowire (NW) diameter on the lasing threshold of optically pumped PhC InP NW arrays at 77 K. The arrays were grown by selective area epitaxy on an InP substrate. The nanowires have mirror-like crystal facets enabling lasing at threshold fluences of less than 10 μJ/cm². NW arrays with pitches of 500, 570 and 630 nm and with NW apothems ranging from 76 to 93 nm have been investigated. The lowest lasing thresholds were obtained in arrays in which the apothem/pitch combination led to a slow Bloch mode (SBM) nearly resonant to or on the low energy side of the InP band emission. PhC samples with off-resonant higher SBM energy show increased threshold values. The observed behavior can be explained by considering both the carrier relaxation and the carrier lifetime in the gain material. InP nanowire arrays with optimized pitch and diameter for low threshold operation are an important step towards electrically pumped PhC lasers.   

On-chip photonic convolution in the fractional Fourier domain

An integrated and programmable photonic circuit architecture to perform a modified-convolution operation based on the Discrete Fractional Fourier Transform (DFrFT) is introduced. The latter is shown to be achieved in an on-chip platform by utilizing two nonuniformly spaced waveguide arrays of different lengths so that the DFrFT and inverse DFrFT operations are performed. The convolution kernel is implemented by programming phase shifters that modulate both amplitude and phase in an MZI array.

 

Numerical results demonstrate that the proposed device is capable of performing customary convolutional tasks such as signal smoothing and edge detection, even in the presence of noisy signals, which are further improved by performing even and odd pooling operations. Notably, the deliberate introduction of random defects into the lattice does not jeopardize the functionality of the proposed convolution device, showing its resilience to manufacturing errors. For completeness, full-wave simulations of pertinent designs based on conventional silicon photonics processes at the telecommunication wavelength are presented.   

Second harmonic generation enabled by van der Waals metasurfaces

Taming second order nonlinearities is of great importance for a range of applications from quantum and classical light sources to computing and communications. Here we study second harmonic generation (SHG) in bulk nanostructured 3R MoS2 metasurfaces. Unlike the most prevailing 2H phase, 3R MoS2 is non-centrosymmetric and possesses non-zero 2^nd order susceptibility. Prior works have studied SHG in exfoliated thin film flakes. In this work we study SHG generation enhancement in  resonant metasurface arrays. We pattern 3R MoS2 (thickness ~130 nm) into arrays of nano-disk resonators. Such disk resonators exhibit strong resonances far below the optical bandgap (0.775 – 0.886 eV), thanks to material’s intrinsically high refractive index. We design structures to be resonant at the pump wavelengths in the range of 1400nm – 1600 nm. In this case generated SHG signal occurs at and below MoS₂ A and B excitons (~1.85 eV and ~2 eV, respectively). By varying the pump wavelength and tuning the geometry of the metasurface we study the influence of second harmonic excitons and their extinction on the efficiency of the second harmonic generation. We also study theoretically and experimentally the interplay of different symmetries on the nonlinear wave-mixing. Our results show significant enhancement of SHG in patterned metasurfaces.   

Thermal management in on-chip superconducting coherent terahertz emitters with engineered cavities

On-chip BSCCO-based layered high-temperature superconducting emitters are sources of high-power coherent millimetre (mm)-waves, and terahertz (THz) photons, and have been used in various applications from imaging, to sensing and spectroscopy. Thermal management is one important factor in developing power-efficient and stable cryogenic mm-waves and THz photon sources, especially for their applications in next-generation telecommunication networks. Here, we analytically and experimentally study heat management and thermal analysis of BSCCO superconducting photon sources with engineered cavities.   

Promoting the Stories of Women in Physics

At Saint Joseph's University, two poster sessions showcasing the role of women and other under-represented communities in physics were held on both campuses of Saint Joseph's University. Participating students came from the two Introductory Physics courses, Modern Physics and Statistical Mechanics. Storytelling can enhance the learning of physics by providing context, promoting student engagement and diversity by celebrating the unique contributions of physicists from different cultures, ethnicities and gender. As part of course requirements, students researched biographies of physicists and gave a poster presentation summarizing the physicist of their choice. Students were asked to frame stories according to the 4 C's of storytelling (character, conflict, context, conquest) and focus on what motivated physicists to study physics in their youth, what unique challenges they faced, their contributions and hobbies apart from physics, and how they interacted with other scientists in their time. We will report on student responses and reactions to this effort, based on blind surveys and general observations.

Website: https://sites.google.com/sju.edu/sjuwomeninphysicsclub/home   

An Empirical Exploration of theFaraday/Einstein Unified Force Field Quandary

A longstanding limitation in the development of a comprehensive theoretical foundation for physical science has been the scarcity of data to fully explicate the hypothesized interrelationship of gravity, electricity and magnetics (GEM).  Michael Faraday and Albert Einstein devoted extensive time and energy to uncover experimental evidence and develop theoretical models to integrate GEM forces and establish empirical foundations for their unified field theories.  To this day, there remains a dearth of observational evidence which could allow a detailed investigation of factors which might reasonably be considered likely contributors to the hypothesized interrelationships of GEM force fields.    

An observational approach, designed to explore the Faraday/Einstein unified force field hypotheses and search for preliminary evidence of GEM unification is proposed. Utilizing geophysical measures and calculations of local gravitational acceleration (g), an experimental methodology was developed.  Preliminary evidence suggests that this approach yields (a) predictive patterns of diurnal geomagnetic ELF behavior, (b) highly correlated geomagnetic and atmospheric electrical activity, and (c) abundant evidence of three factor (GEM) correlations.  These findings, viewed in the context of gravitationally driven geophysical strain (g-strain), offer a conceptually robust and methodologically sound path forward for an empirical exploration of the Faraday/Einstein unified force field quandary.     

Artificial Intelligence: The Complex Networks Behind Legislation

Artificial intelligence is increasingly becoming more advanced and prevalent in all aspects of life, bringing to light the need for official standards and regulations. The regulatory process for emerging technologies like AI, however, is lengthy, and includes a wide array of agencies and stakeholders both within and outside of all branches of government before any legislation can be proposed, much less enacted. AI regulation is vitally important, and can also be used to demonstrate the overall regulatory process. The House of Representatives Committee on Science, Space, and Technology plays an important role in determining standards through NIST and thereby other government agencies, but there is much more to AI regulation than just the House Science Committee. Some other inputs to the regulatory framework include House and Senate Judiciary Committees, the Executive and Judiciary branches, and outside experts. The consequences and implications of AI are vast and far reaching. Through gaining a complete picture of the regulatory ecosystem, one can better understand the challenges and pitfalls that the U.S. is facing before any significant legislation – AI or otherwise – can be passed.   

Laminar forced convection flow past an in-line elliptical cylinder array with inclination

Flow past a cylinder array with various configurations has

wide range of practical engineering applications, such as in heat

exchangers, boilers, condensers, and energy storage systems. The

thermal performance of these systems is important in meeting the

efficiency standards with low cost and environmental impact. On

The physical model consists of flow around an in-line five elliptical

cylinder array. The inclination of the elliptical

cylinders increases with the number of the cylinder in the row: the

first cylinder has 0o inclination while the last has 90o inclination. The

fluid y p flow and heat transfer are solved as a transient problem to

the other hand, flow past a cylinder array has been attracting the

attention of many academic researchers because it contains

interesting fluid dynamics phenomena such as flow instability,

free-shear layer, flow separations, and vortex shedding, and many

others. the Reynolds number is the most important parameter that

affects the heat exchange between the cylinders and flow.

Obviously, increasing the Reynolds number increases the Nusselt

capture an expected vortex shedding street phenomenon. The

working fluid is air, Pr=0.71. Since the cylinders are tightly packed, it

is assumed that no flow or heat transfer is taking place in cross

direction along the lateral boundaries. The length of the cylinders are

typically long for heat exchangers, and therefore, the flow field and

heat transfer are considered to be two-dimensional, consisting of a

single row. Therefore, researchers are concentrating their efforts

on the heat transfer enhancement from the cylinders through the

modification of the flow pattern. Destroying the hydrodynamics

boundary layer and creating several separation and reattachment

points at the cylinders’ surface are the objectives of the flow

modification technique. In this regards, researchers examined

a and b, respectively. The inclination angle of the cylinders is θ, and

Fig. 1 depicts an elliptical cylinder with the important geometrical

parameters. various techniques, such as using an array of delta-winglet vortex

generator for in-line tubes, and this technique provided an overall

heat transfer enhancement of about 32%, but with a similar

pressure drop penalty.    

Thermochromic Materials for Solar Degradation Resistance and Energy Efficiency

Thermochromic materials (TCMs) possess reversible color changes with respect to the variation of temperature. TCMs have two apparent phases: a light phase upon heating, reflecting more radiation, and a dark phase upon cooling, absorbing more radiation. Their color change properties can be used to vary the throughput of visible light and solar energy for applications in windows and building surfaces. However, due to being partly organic, when exposed to sunlight with a wide range of wavelengths from UV to near IR, TCMs often degrade. This degradation limits TCM’s potential applications, such as coating building exteriors and energy storage. As the TCMs degrade, there’s an observable change in both phases, gradually becoming less distinct and effective as separate light and dark phases. Microencapsulation of TCMs by inorganic metal oxides, such as TiO₂, can potentially prevent this degradation. This project aims to develop a combined solar simulator and environmentally controlled chamber to obtain realistic TCM degradation data and its dependence on irradiation wavelength and environmental conditions like ambient temperature or humidity. Under conditions, data points will be tracked throughout the degradation by characterizing both phases before and after exposure for each testing cycle in the apparatus. The data presented focuses on the degradation of metal oxide encapsulated and pristine TCMs with various optical filters and the associated techniques, instrumentation, and characterization.   

Thin film thermocouples of textured polycrystalline topological insulators

Surface-mounted thin film thermoelectric (TE) devices hold significant contemporary interest for applications in localized cooling, power generation, and sensing. In this work, we report on the performance of thin film thermocouples of Bi₂Te₃ - Sb₂Te₃ and BiSb - Sb₂Te₃ deposited using a combination of pulsed laser ablation and magnetron sputtering in a combinatorial growth system of base pressure 5 x 10^-8 torr. Firstly, the plain films of Bi₂Te₃, Sb₂Te₃, and BiSb were investigated for their electrical conductivity, charge carrier concentration, and carrier mobility in the temperature range of 2 to 300 K. The ambient temperature Seebeck coefficients of BiSb, Sb₂Te_3, and Bi₂Te₃ were measured against copper with a laser heating technique. Next, single TE junctions of n-BiSb and p- Sb₂Te₃ and n- Bi₂Te₃ - p- Sb₂Te₃ were characterized and yielded a response of 270 µV/K and 250 (±10) µV/K respectively. This first-time comparative study shows that BiSb is a superior n-type counter electrode for Sb₂Te₃ compared to the n-type Bi₂Te₃. Moreover, Bi₂Te₃ is prone to Te antisite disorder which affects its TE properties significantly. In contrast, BiSb, being a solid solution, has less stringent demand on stoichiometry control, and it is also less prone to oxidation compared to Bi₂Te₃. Our results establish that BiSb is a viable counter electrode for surface-mounted TE devices in conjunction with the p-type Sb₂Te₃.      

Breaking the Limit of Size-Dependent CO2RR Selectivity in Ag Nanoparticle Electrocatalysts through Electronic Metal-Carbon Interactions: Insights from Computational Hydrogen Electrode Calculations

Experiments show that metal-carbon interactions between small diameter Ag particles and defective carbon supports can improve electochemical CO₂ reduction activity and break the size-dependent selectivity trend traditionally associated with coinage-metal catalysts. Specifically, < 2 nm diameter Ag electrocatalysts grown on a defective carbon support demonstrate a CO Faradaic efficiency of ~100% and turnover frequency of 2 CO/atom_Ag/s at -1.3 V vs. the reversible hydrogen electrode. X-ray photoelectron spectroscopy identifies a new Ag^d+ feature in Ag particles grown on defective graphite that indicates Ag-C interaction and the resulting charge transfer slightly depletes electron density in the Ag nanoparticles. Due to the current challenges in designing in situ interfacial experimental probes, we apply the computational hydrogen electrode approach to rationalize the experimental findings. The calculations predict a charge transfer from the Ag nanoparticle to a defective carbon surface, stabilizing the *COOH intermediate through reduced antibonding orbital overlap, significantly reducing the *COOH formation energy barrier, and improving CO₂-to-CO conversion selectivity compared with Ag nanocluster on defect-free carbon. These results provide new insights into carbon-supported electrocatalysts for CO₂RR and introduce a new approach for creating active and selective nanocatalysts.   

Understanding interfacial evolution in solid-state batteries using machine learning force fields

The interfacial instabilities in solid-state batteries (SSBs) significantly affect the cell performance. In this talk, we will demonstrate direct observation of interfacial evolution at the Li₇La₃Zr₂O₁₂ (LLZO) solid-electrolyte/LiCoO₂ cathode interface from large-scale molecular dynamic simulations enabled by validated machine-learning force fields (MLFFs). Our results unravel the relationship between the surface chemistries of LLZO and LCO and propensities for interfacial degradation. We will further address the impact of element doping (as often found in LLZO) on Li-ion transport in single grain LLZO and its grain boundaries (GBs). It is observed that dopants tend to segregate at the LLZO GBs and form clusters that can lead to prenucleation of dopant-rich secondary phases at the GBs. This phenomenon is presumed to be general regardless of the type of GBs. Our findings imply that interlayer design may be needed to alleviate the intrinsic interfacial degradation for enhanced performance.   

First-Principles Simulation of Novel Materials in Lithium-Sulfur (Li-S) Battery Applications

High-capacity energy storage is crucial for various technological applications, such as electricity-powered transportation. The current state of the art is lithium-ion (Li-ion) batteries, but research and development of battery technologies beyond Li-ion is critical for future needs. In the race to supersede Li-ion batteries, Li-S batteries are among the most promising candidates. However, some electrode design-related challenges must be overcome to enable their commercialization. Basic understanding of Li-S chemistry and material properties, including interactions at the electrode/electrolyte interfaces and the dissolution of polysulfides (otherwise known as the "shuttle-effect"), remains elusive though important. Atomistic simulation and density functional theory (DFT) calculations offer useful insights. Hence, we outline two baseline studies that we have undertaken in this framework.   

Poster: Stability enhancement in FAPbI3 perovskite absorbers via Guanidinium doping for photovoltaic applications

Hybrid halide perovskite (HHP) materials present a flexible version of the next-generation photovoltaic technology. Formamidinium lead iodide (FAPbI₃) perovskite has recently gained immense interest as a possible absorber of hybrid halide perovskite (HHP) based solar cells and is extensively investigated both on experimental and theoretical fronts. However, it is unstable against the moisture, making this material domain inappropriate for long run. In the present work, we deal with the synthesis of GA-doped FAPbI₃ (GA_xFA_1-xPbI₃) perovskite material via spin-coating method. The structural and optical properties have been investigated via X-ray Diffraction and UV-Vis/PL spectroscopy, respectively. From XRD, it is found that the GA content plays a vital role in the formation of α-phase and its stabilization over δ-phase. The optical investigation shows the optimum band gap of GA-doped FAPbI₃ perovskite for the photovoltaic application. Also, we have developed theoretical understanding of structural, electronic and optical properties of GA-doped FAPbI₃ using density functional theory (DFT) approach with good matching with experimental results. Our calculations revealed that GA-doped FAPbI₃ can be a suitable candidate for absorber layer in HHP based solar cells.   

Dynamic calibration of the injection-dependent carrier lifetime in GaAs

Characterization of defect-related recombination in photovoltaic materials is critical for improving the performance of solar cells. Injection-dependent lifetime spectroscopy is a sensitive and commonly used technique for investigating recombination rates in semiconductors. However, determination of the photoexcited carrier density during the lifetime experiment can be problematic. We employ a new dynamic calibration method, which relies on a combination of quasi-steady-state and transient measurements, to obtain the lifetime as a function of charge carrier density in a GaAs/GaInP heterostructure.   

Sustainable Water Sourcing: Solar-Driven Potable Water Extraction from Atmospheric Moisture

Water scarcity is a rapidly growing problem that touches nearly all stretches of the world. Atmospheric water harvesting is a promising solution to this problem. Our approach involves using a liquid desiccant and a permeable hydrogel in order to capture atmospheric water and store it in its liquid phase, which we have previously demonstrated. However, a critical stage to this process is being able to release potable water from the hydrogel and desiccant setup. The goal is to find passive means to release this water. However, challenges arrive due to the elevated boiling temperature of desiccant solutions. To undertake this problem, we use a sun concentrating trough optimized with solar tracking to evaporate and condense potable water from the liquid desiccant solution storage. All experimentation takes place in low-humidity Las Vegas, one of the most difficult places to capture water, to ensure that our atmospheric water harvester has promising applications anywhere.   

Organic thin-film synaptic transistor for emulating artificial synapse and non-volatile memory

Ion gels, solidified ionic liquid electrolytes by structuring polymer networks, have attracted significant attention in various applications due to their exceptional material properties. These properties include a high specific capacitance, remarkable thermal, and electrochemical stability, non-flammability and rubber-like mechanical robustness. Pressure sensors, which convert external mechanical deformations to electrical signals, find utility in a wide range of fields such as human skins, soft robotics. For these sensors, it is crucial to have high sensitivity, a broad sensing range, and a quick response time. In the case of capacitive sensors utilizing ion gels, they offer significant advantages for pressure sensors due to their stability, rapid response, and simple device designs. However, sensitivity of these pressure sensors is often insufficient, which limits their practicality and applicability. To address this, we incorporated organic thin-film transistors and high-capacitance ion gels and successfully fabricated highly sensitive pressure sensors. By employing thin-film transistor-based sensors, very small mechanical stimuli can be magnified into substantial electrical signals, resulting in a significant enhancement in sensitivity. Additionally, synaptic transistors demonstrated with the pressure sensors exhibited reversible transitions between short-term plasticity, long-term plasticity, and non-volatile memory functions.   

Title: Nitride Nanopatterning for Optoelectronic Advancements

Nanopatterning of inorganic materials is an emerging field with a wide range of applications such as optoelectronics, photonics, energy, and biomedical engineering. Group III nitride materials particularly Gallium Nitride (GaN) and Aluminum Nitride (AlN), are noteworthy due to their exceptionally wide bandgaps, enabling emissions across the ultraviolet (UV) and visible spectrum. Nitride-based planar structures are commonly used for blue LEDs and recently nanostructures have gained attention for growth on low-cost dissimilar substrates, better light extraction properties, and carrier confinement. Nitride material growth is challenging due to high-temperature requirements and lattice mismatch with conventional substrates. We used Sequential Infiltration Synthesis (SIS) to develop nanopatterns of AlN, allowing for scalable and well-ordered growth of patterned nanomaterials. We have used polystyrene-b-polymethylmethacrylate (PS-b-PMMA) self-assembled nanostructures as a guiding pattern. We analyzed the nitride patterns using Scanning electron microscopy and Fourier transform infrared spectroscopy. Nanopatterning nitride materials with SIS could lead to new, cost-effective substrate-independent nitride-based optoelectronic device applications.   

2D materials Enhance Thermal Boundary Conductance at van der Waals Interfaces of β-Ga2O3

Wide bandgap (WBG) semiconductors have enabled the advancement of next-generation radiofrequency, opto-, and power electronics. Among them, β-Ga₂O₃ has emerged as a leader because it can withstand higher voltages with higher efficiencies and can be fabricated using relatively cheap melt-growth techniques. However, it suffers from limited thermal conductivity which could lead to Joule heating and performance degradation. Therefore, to ensure efficiency and reliability of devices with β-Ga₂O₃ channels, effective methods of heat dissipation are needed. In this study, we show that high TBC at β-Ga₂O₃/2D interfaces can be used to improve β-Ga₂O₃/substrate TBC by adding interlayers of 2D materials at the interface. β-Ga₂O₃ has large vibrational density of states in the low-frequency range where it overlaps well with the flexural phonons of 2D materials leading to a high TBC across β-Ga₂O₃/2D interfaces, unlike other WBG materials such as diamond. Layers of hBN show the highest TBC of 19.9 MW/m²K for combined 3D-2D-3D interfaces of β-Ga₂O₃/hBN/Ti at room temperature. We show that TBC relates to the overlap of vibrational densities of states (DOS) and that it can be further increased by more than 30% when the number of 2D layers is increased from 1 to 12 due to an increase in the number of flexural phonon branches, which increases the DOS overlap. Our study provides important information and will contribute to the realization of efficient thermal management of thin-film wafer-bonded β-Ga₂O₃ electronic devices.   

Synthesis and Characterization of Boron Nitride Dots

 Zero-dimensional (0D) boron nitride nanoparticles (BN dots) are biological and environmentally compatible for biomedical applications. There is growing interest in using BN dots for electronics and optoelectronics applications [1]. BN dots can be produced mainly in two ways: top-down or bottom-up method. Top-down methods shrink large materials to nanoscale quantum dots, such as the breaking of bulk hexagonal BN powders (h-BN) into 0D structures. In the bottom-up methods, B and N precursors are used for producing BN dots.

Recently, we demonstrated that BN dots can be chemically functionalized to form high-brightness fluorophores (HBFs) for biological detection [2]. For such an application, it is desired that all the BN dots are small and uniform in size. In this study, we compare two different top-down approaches to synthesizing uniform BN dots. Firstly, we combine ultrasonication and solvothermal treatment of bulk h-BN powders into BN dots. Secondly, we combine cryo-assisted liquid-phase exfoliation and ultrasonication. The yields and purity of BN dots in these two approaches are compared. We further examine their size distribution by atomic force microscopy (AFM) and transmission electron microscopy (TEM). The optical properties of the products are also characterized by UV-Vis and fluorescent spectroscopy. The details of the synthesis approach and the properties of these BN dots will be discussed in the conference.   

Hierarchical Mn2O3 Nanoparticles with high Electrochemical performance

Manganese oxide valence states in the redox reactions prove advantageous in augmenting the electrochemical characteristics and thus enhance the supercapacitive performance of the material. In the present study, hierarchical Mn₂O₃ nanostructures are synthesized via facile autocombustion technique using various concentrations of classic biochemical Good’s buffer, and piperazine, and subsequently evaluated for their electrochemical performance.

The XRD study confirms the presence of crystalline Mn₂O₃. The SEM imaging confirmed that the amount of piperazine affects the shape, size, and morphology of the cuboidal Mn₂O₃.  The Mn₂O₃ with 6 mM piperazine has the highest surface area (8.67758 m²/g). The electrochemical analysis performed in the three electrodes system was assessed in 1, and 6 M of KOH electrolytes using nickel foam. In cyclic voltammetry, 0 mM PIPES has the highest specific capacitance (608.05 F/g) at 1 mV/s scan rate at 1 M KOH electrolytes, and for 6 M KOH, 6 mM PIPES has the maximum specific capacitance (970.16 F/g). The charge-discharge curves for 0 mM piperazine have ~413 F/g, maximum, specific capacitance at 1 M KOH and 6 mM PIPES has ~808 F/g at 6 M KOH, maximum energy and power density are observed.  This superior electrochemical performance of Mn₂O₃ is attributed to the high surface area and better coordination of Mn³⁺ ions in the presence of PIPES. Further enhancement in electrochemical performance is expected for the Mn₂O₃-rGo composite, which is under study.   

Leaf-based Hydrovoltaic Power Generator

With the increasing demand for electronics for a growing number of applications, electronic waste created after discarding these devices continues to grow. This poses a growing threat to environment and public health as most of the electronic devices are discarded releasing heavy metals and other chemicals into the soil and water sources.. Therefore, using bio-based materials for electronics could be an alternative for minimizing the environmental footprint of electronic devices.  Here, we present our work on the development of a leaf-based hydro voltaic power generator that can generate power from the movement of moisture due to the concentration gradient of water. Using microporous leaves developed using chemical treatment, and sandwiching them between metal electrodes as current collectors, we have been able to generate an open circuit voltage of 700mV. In this presentation, we will discuss the mechanism of the generation of the electric current from this setup as well as optimization of the device to improve its performance.  The device like the one we have created  demonstrates a promising method for the development of bio-based power generators that can generate continuous electrical energy for low-powered devices from water sources.     

The National Spherical Torus Experiment: Advancing the Physics of Magnetic Confinement Fusion

The National Spherical Torus Experiment (NSTX) at the Princeton Plasma Physics Laboratory has provided much of the physics basis for the spherical tokamak (ST) magnetic plasma confinement concept for fusion energy production; concepts which are currently being designed for future fusion pilot plants. NSTX is currently in the midst of an upgrade, and researchers are continuing to advance the physics understanding of ST plasmas to maximize the benefit that will be gained when the upgraded device (NSTX-U) returns to operation and to increase confidence in projections to future devices. STs have certain advantages: their more compact size (than conventional tokamaks) means they can provide higher plasma current more economically. Their low aspect ratio, of major to minor radius, improves stability with favorable average magnetic curvature, enabling high beta (the ratio of plasma pressure to magnetic pressure). There are challenges as well: managing high heat flux, and start-up and sustainment of the plasma without space for an induction coil. The objectives of NSTX-U research are to: (i) to extend particle confinement physics of low aspect ratio, high beta plasmas to the lower particle collisionality levels relevant to future device regimes, (ii) to develop stable, non-inductive scenarios with the self-generated current needed for steady-state operation, and (iii) to develop conventional and innovative power and particle handling techniques to optimize plasma exhaust in high performance scenarios.   

High-efficiency mapping of resonant inelastic x-ray scattering of sodium-ion battery cathodes

High degree of reversibility [1] of the oxygen redox reactions in sodium-ion batteries (NIBs) makes them attractive candidates for large-scale energy storage solutions, provided that the oxygen activity can be optimized to significantly boost their capacity. High-efficiency mapping of resonant inelastic x-ray scattering (mRIXS) is a powerful tool for investigating the chemistry of NIBs [2, 3]. Tracking the energy of the emitted photons across an absorption edge introduces an extra dimension of information relative to the conventional x-ray absorption spectroscopy (XAS) studies, allowing for an unambiguous access to different decay channels, including unconventional oxidation states of oxygen and the transition metal, as well as the hybridization between them. Here, we demonstrate the oxygen K-edge RIXS maps of a model solid-state battery cathode system, NaNiO₂, as well as discuss perspectives for future in-operando measurements.

 

[1] C. Fang, Y. Huang, W. Zhang, J. Han, Z. Deng, Y. Cao, et al., Routes to high energy cathodes of sodium-ion batteries. Adv. Energy Mater. 6:1501727. (2016)

[2] W. Yang, and T. Devereaux, Anionic and cationic redox and interfaces in batteries: Advances from soft X- ray absorption spectroscopy to resonant inelastic scattering, J. Pow. Sour. 389, 188-197 (2018)

[3] J. Wu, Z.-X. Shen, and W. Yang, Redox mechanism in Na-ion battery cathodes probed by advanced soft X-ray spectroscopy. Front. Chem. 8:816 (2020)   

Investigation of sodiation performance in Na3V2(PO4)3/C nanoflakes as a cathode in sodium-ion batteries

Sodium-ion batteries are a next-generation and cost-effective alternative to rechargeable lithium-ion batteries. However, the energy density of the battery is driven by its cathode and using sodium ion as a carrier limits its capacity, cycle life and rate capability. In this work, we explore the enhancement in the electrochemical performance of Na₃V₂(PO₄)₃/C (NVP/C) as a promising cathode material in SIBs. Sodium vanadium phosphate is a NASICON-type structure and, thus, shows less strain during intercalation and de-intercalation of sodium ions. NVP/C has been prepared through the sol-gel method, and its detailed material characterization has been carried out. The powder XRD pattern confirms the phase purity for NVP/C indexed using JCPDS no. 53-0018. The morphological investigation shows grains of size 20-50 nm. Various electrochemical measurements- EIS, CV, galvanostatic cycling, etc. were carried out in the coin cell half-cell configuration. The CV curves show sharp redox peaks as 3.45/3.29 V attributed to V⁺³/V⁺⁴. The multiple peaks during reduction suggest the transfer of Na⁺ ions from Na(1) to Na(2) site. The charge-discharge profile provides a specific capacity of 89.25 mAh/g at 2C and a coulombic efficiency of 99.85%. Also, various Ex-situ characterization techniques, like FESEM, AFM, etc., will be recorded to analyze the morphology and subsequent roughness of the electrode before and after cycling.   

Hydrothermal Treatment of Microalgae for Biofuel Production

Microalgae as a source of biofuel is not only important for sustainable energy but is also vital for meeting emission standards. However, the drying, extraction, and catalytic conversion processes necessary to convert microalgae to fuel are cost prohibitive compared to petroleum diesel fuel at its current price. To enable this sustainable fuel resource, the present project aims to investigate and optimize biofuel production using Hydro-Thermal Liquefaction (HTL) process. The algae will be directly combusted in a PARR Reactor, co-fueled with diesel or biodiesel to power engines. The algae components of proteins, carbohydrates, and oil have a combined heat of combustion near that of ethanol. In our preliminary research, an HTL process was developed where the algae are cooked at different experimental conditions, such as DI water content, diesel volume, algae mass, temperature and pressure, duration of cooking and de-oxygenation. HTL can be performed on wet substances without drying, so the main issue is controlling the salt content in the algae. The microstructural studies were conducted on the algae samples processed for 30 minutes and 2 hours show the presence of carbon to oxygen in 2:1 with the rest of the elements such as Cl, K, Na, P, S, and Mg in less than 1.5 wt%. Overall, this research will provide data critical to meeting the potential of microalgae as a directly combustible biofuel.   

Leaf-Based Triboelectric Nanogenerators

With the increasing practice of using low-powered devices for a wide range of applications, there is a growing interest in developing power-generating devices that may output low power density but would do so reliably and operate for a long duration. Triboelectric Nanogenerators (TENGs) are a type of such device that can convert residual mechanical energy common in nature into electrical energy that can be stored and used for powering electronic devices. Here, we report the development of leaf-based TENGs (L-TENGs) with the goal of creating fully bio-based power-generating devices. We optimized the power output of L-TENGs by varying various parameters such as leaves from various locally available trees, chemical treatment of the leaves, counter contact materials, operational frequencies, and type of electrodes. An optimized L-TENG with graphite electrodes resulted in the devices with 8 V open circuit voltage output and 0.8 uA short circuit current, with a total power density of approximately 89.5uW/m². The development of power-generating devices such as L-TENGs we report demonstrates the potential of using biological materials as eco-friendly and sustainable sources for electronic devices.   

MultiBinding Sites United in Covalent-Organic Frameworks (MSUCOF) for H2 Storage and Delivery at Room Temperature

The storage of hydrogen gas (H₂) has presented a significant challenge that has hindered its use as a fuel source for transportation. To meet the Department of Energy's ambitious goals of achieving 50 g L^-1 volumetric and 6.5 wt % gravimetric uptake targets, materials-based approaches are essential. Designing materials that can efficiently store hydrogen gas requires careful tuning of the interactions between the gaseous H₂ and the surface of the material. Metal-Organic Frameworks (MOFs) and Covalent-Organic Frameworks (COFs) have emerged as promising materials due to their exceptionally high surface areas and tunable structures that can improve gas-framework interactions. However, weak binding enthalpies have limited the success of many current candidates, which fail to achieve even 10 g L^-1 volumetric uptake at ambient temperatures. To overcome this challenge, We utilized quantum mechanical (QM) based force fields (FF) to investigate the uptake and binding enthalpies of 3 linkers chelated with 7 different transition metals (TM), including both precious metals (Pd and Pt) and first row TM (Co, Cu, Fe, Ni, Mn), to design 24 different COFs in-silico. By applying QM-based FF with grand canonical Monte Carlo (GCMC) from 0-700 bar and 298 K, We demonstrated that Co-, Ni-, Mn-, Fe-, Pd-, and Pt-based MSUCOFs can already achieve the Department of Energy's hydrogen storage targets for 2025. Surprisingly, the COFs that incorporated the more affordable and abundant first-row TM often outperformed the precious metals. This promising development brings us one step closer to realizing a hydrogen-based energy economy.   

Synthesis and optical characterization of Eu3+-doped CaTiO3 embedded into a–SiO2 sonogel hosting

Ceramic powders of Ca_1-xEu_xTiO₃ (x = 0.0, 0.01, 0.02, 0.03 and 0.04) were synthesized by the polymeric complex method and annealed at 1000 °C for 1 h.  These phosphors were embedded into a–SiO₂ sonogel hosting at different dopant ratios to obtain luminescent Ca_1-xEu_xTiO₃:SiO₂ glasses. The powders and glasses were characterized by X-ray diffraction, scanning electron microscopy, absorption, and photoluminescence spectroscopy. The obtained powders have an orthorhombic crystal structure. The luminescence spectra from all samples show the characteristic red emission peaks from the Eu³⁺ ion associated with inter-electronic energy level transitions. However, the excitation spectra in these nanophosphors are dominated by the ⁷F₀–⁵L₆ transition (395 nm), as opposed to the dominant charge-transfer related band at~260 nm commonly reported.   

Machine Learning Refinements to Metallicity-Dependent Isotopic Abundances

The project aims to use machine learning algorithms to fit the free parameters of an isotopic scaling model to elemental observations. The processes considered are massive star nucleosynthesis, Type Ia SNe, the s-process, the r-process, and p-isotope production. The analysis on the successful fits seeks to minimize the reduced chi squared between the model and the data. Based upon the successful refinement of the isotopic parameterized scaling model, a table providing the 287 stable isotopic abundances as a function of metallicity, separated into astrophysical processes, is useful for identifying the chemical history of them. The table provides a complete averaged chemical history for the Galaxy, subject to the underlying model constraints.   

Development of Copper Powder Demagnetization Stage Compatible with Cryogen-free Cryostats

Motivated by demand to investigate two-dimensional electron systems (2DES) at ultra-low, electron temperatures below 10 mK, our goal is to develop compact, modular cells that ensure proper thermalization of the on-chip electrons within nano-sized devices down to 1 mK and in sizeable magnetic fields ≥ 1 T. The approach involves an "in-cell" magnetic cooling platform compatible with the cryogen-free dilution cryostats. This method entails immersing copper powder directly into liquid ³He, which serves as a coupling agent between the refrigerant, the electrical contacts, and the on-chip electrons. Avoiding bulk copper in the magnetic field required for traditional demag systems eliminates most of the eddy current heating resulting from Pulse Tube vibrations, while also reducing the demag time. This approach has been used in "wet" dilution cryostats to study quantum fluids [1], but its adaptation to cryogen-free systems is novel. Ultimately, the sample response is studied while both magnetic filed and temperature are changing, and the results of numerical simulations and experimental findings will be presented. 

[1] R.C.M. Dow, et al. J Low Temp Phys 47 (1982) 477; D.I. Bradley, et al. J Low Temp Phys 57 (1984) 359.   

Characterization of Al as a material for the superconducting cable

Small attenuation is essential for the coaxial cable used at low temperature, and superconducting aluminum below the transition temperature is one of the promising materials. We investigated low temperature properties, such as Tc of Al, aiming to apply as both the center and outer conductors of the semirigid coaxial cable.   

High-Resolution Diffraction Grating Filter Holder Design

Spectroscopic capabilities are typically reserved for large telescopes operated by large colleges and universities and are not seen with smaller colleges and universities. Our current miniature grism (Patent No.US20170357038A1) is a 3D printed housing that contains 5 optical elements and is installed in the filter wheel. This grism includes a 600 line/mm with a peak spectral resolution of 1.1nm VPH (Volume Phase Holographic) grating. We present a new grism design with a compound grating-prism element with a 2000 lines/mm VPH tuned for a maximum efficiency of 70% at 656nm with a max spectral resolution of <0.3nm (<150km/s at H-). The changes made to this design entail modifying the current grism housing to be compatible with this new grism, creating and testing this housing on an optical table to demonstrate the expected performance increase. We expect that at max resolution, we will be able to make precise measurements of H- doppler broadening from Be stars caused by a decretion disk from near-critical rotation. The miniature grism was originally installed on the Robert L. Mutel Telescope (RLMT) at Winer Observatory in Sonoita, AZ, and is currently operated by the Macalester, Augustana, Coe College, Remote Observatory (MACRO) Consortium.   

Diffuse reflectance-based femtosecond stimulated Raman spectroscopy of opaque systems

Raman spectroscopy is a non-invasive and non-destructive technique that obtains vibrational information of a system but is notorious for producing small signals. By measuring the vibrational spectrum of a system through femtosecond stimulated Raman spectroscopy (FSRS), we can measure the detailed ultrafast structural dynamics of the system upon photoexcitation. Additionally, stimulated Raman scattering (SRS) is known to greatly increase the magnitude of detected signal relative to traditional spontaneous Raman spectroscopy. However, typical FSRS experiments require transparent samples. To overcome this limitation, we adjusted the collection optics used in traditional FSRS experiments to collect a diffusely reflected probe pulse as it scattered off opaque, turbid samples. We collected the ground-state stimulated Raman spectra of 12.5% (v:v) ethanol in a 1% intralipid solution and cyclohexane-intercalated poly(tetrafluoroethylene) microbeads. Further, we characterized the SRS signal obtained by comparing the signal intensity and incident pump-probe polarization dependence of the data collected using both traditional FSRS and diffuse reflectance-based FSRS (drFSRS). While the initial drFSRS experiments focused on obtaining the ground-state Raman spectrum of several opaque systems, improvements to drFSRS could allow for the measurement of ultrafast structural dynamics of opaque systems.   

Comprehensive model of anomalous intense coherent secondary photoemission from an oxide semiconductor

The recent discovery of an anomalous intense and coherent secondary photoemission signal from 2x1 surface reconstructed SrTiO₃¹ has several perplexing aspects that evade explanation from the conventional theoretical framework of secondary photoemission. We present a comprehensive model which can coherently explain all the puzzling features of the experiment including the presence of a second energy dependent threshold in addition to the typical photoemission threshold, the dramatic orders of magnitude increase in intensity upon decreasing temperature, and the coexistence of monochromaticity alongside high quantum efficiency within a positive electron affinity material. This model is based on a novel point of view which includes the components of Auger recombination and flat electronic bands. Furthermore, as a future test of our model we show that it predicts below photoemission threshold emission under specific conditions. Finally, guided by the salient features proposed to make the 2x1 reconstructed SrTiO₃ exceptional, we identify a diverse set of other materials which are predicted to exhibit the same anomalous behavior.

1. Hong, C. et al. Anomalous intense coherent secondary photoemission from a perovskite oxide. Nature 617, 493-498 (2023).   

Temperature-dependent optical properties of monocrystalline CaF2, BaF2, and MgF2

The alkaline earth metal difluorides are critical optical components for applications in non-contact temperature sensors, thermal imaging, and infrared spectroscopy due to their characteristically low refractive index and wide optical transparency spanning the ultraviolet to mid-infrared. Despite their technological importance, a systematic investigation into the temperature dependence of their optical properties is lacking. In this study, spectroscopic ellipsometry was used to obtain the refractive index of monocrystalline CaF₂, BaF₂, and MgF₂ for wavelengths between 220 nm and 1700 nm, and for temperatures between 21 °C and 368 °C. The refractive index of CaF₂ and BaF₂ was observed to decrease linearly with increasing temperature, which can be largely attributed to a reduction in the mass density due to thermal expansion. In contrast, the refractive index of MgF₂ was found to vary nonlinearly with temperature, which suggests competing effects from the material’s electronic polarizability. The temperature-dependent refractive index data reported here provide a finely-resolved mapping of the thermo-optic coefficient for these three materials, which could inform the development of optical devices operating at elevated or unsteady temperatures.   

Infrared Imaging of Cryogen-Free NMR Superconducting Magnets with a variable temperature insert

Cryogen-free superconducting magnets are an attractive alternative to conventional liquid helium-cooled magnets with applications involving nuclear magnetic resonance (NMR), dynamic nuclear polarization (DNP), electron paramagnetic resonance (EPR) applications and Mossbauer effect between others, as they offer reduced operational costs since they don't require cryogen liquids such as liquid helium and/or nitrogen. However, cryogen-free magnets also pose new challenges in terms of thermal management and thermal stability, especially when they involve a variable temperature insert (VTI). In this study, we use infrared imaging to investigate the thermal behavior of a Cryogenic Ltd 9.4 T cryogen-free NMR magnet with incorporated VTI and how it may help to monitor the working of the system. We evaluate the effects of external disturbances, such as power outages on the magnet performance and safety and compare it with a wet 300 MHz Bruker magnet. Our results show the possibilities and advantages of infrared imaging as a monitor tool for cryogen-free NMR magnets.   

Poster:Designing Thermopower Measurement Probe

Thermoelectric effect is a phenomenon in which an electrical voltage difference is induced by a temperature difference across a material. It can commonly be observed in semiconductors and semimetals, and it can be characterized by Seebeck coefficient (thermopower), which is the ratio of negative voltage difference to temperature difference when the heat is applied at one end of a sample. The thermopower values can be positive or negative depending on the type of charge carriers: holes or electrons. This effect has many applications, such as power generation from waste heat, thermocouples for temperature sensing and control, thermocouple vacuum gauge, and thermoelectric refrigerators. Many strongly correlated electron materials in our laboratory exhibit this thermoelectric property, therefore, we need to develop a probe for thermopower measurement that can be used in a cryocooler. In the previous design and data analysis, we used the two well-known materials, Nickel 201 alloy and Platinum 99.9%, to test the accuracy of the probe. We found that the type T differential thermocouple that we used could not sense accurate temperature differences below 100K and only one sample holder cannot subtract the background contribution from wiring efficiently. In the new probe design, we plan to install two Cernox thermometers on the either side of a sample holder (i.e., hot side and cold side) because Cernox has a wide range of sensitivity down to 0.3K. We will also install two sample holders to set up a reference material such as a thin Pt wire for the purpose background subtraction. In addition, to reduce the measurement time, we plan to adopt a slope method over steady state method, as long as each measurement-maintained temperature difference within 3% of the regulating temperature.   

Analysis of heating and cooling rates of polar bear hair by means of phosphor thermometry: A feasibility study

To survive within the extreme habitats of the Arctic, Polar bears (Ursus maritimus) have evolved numerous thermoregulatory adaptations.  One such adaptation is the structure of their hair which is hollow in nature.  Using the natural variation between polar and brown bears, we investigate the thermoregulatory properties of bear hair, specifically heating/ cooling rates using phosphor thermometry techniques. Polar bear hair strands were uniformly coated with La₂O₂S:Eu phosphor particles. A 405 nm diode laser firing at 20 Hz and of 30 µs duration excited the luminescence. A photomultiplier (PMT) with an intervening bandpass filter of 515 nm of 10 nm full-width half-maximum was used for signal detection, while attached to a fiber bundle  situated 1.5 cm above the emitting region.  Decay characteristics at and above room temperature were collected with decay times correctly reflecting the set temperature. This study paves the way for customized and accurate thermometry on a scale appropriate for microscopic evaluation of thin specimens.   

Resonant ultrasound spectroscopy (RUS) for determining elastic moduli of soft materials.

The elastic moduli give important information needed for engineering applications. Simple techniques for finding them can greatly aid in developing designs by understanding material properties. Based on the classical RUS design [1] we have built an instrument for exploring materials elasticity. In our setup the excitation signal is driven with a Rohde & Schwarz signal generator (SMY-01) connected to a piezoelectric transducer. Having passed through the sample, the signal is received by another transducer and cleaned up with a Stanford Research Systems (SR810-DSP) lock-in amplifier. The advantage of our setup is that it allows for work at low frequencies, which implies possibility of studying soft materials. Performance of the instrument was tested on recording the resonances of aluminum and magnesium samples with the purpose of elucidating their elastic moduli. Another benefit of our design is that it does not require expensive components and can be adopted for undergraduate education.

[1] A. Migliori, J. Sarrao, “Resonant Ultrasound Spectroscopy”, 202 p., Wiley-VCH, 1997   

Modeling NEMS Non-Linearities with Commercial Quartz Tuning Forks

As technology develops, Nanoelectromechanical System (NEMS) oscillators become progressively smaller in accordance with Moore's law. However, the small NEMS tend to easily enter a nonlinear regime, in which controlling them represents a technological challenge. With the goal of developing an efficient method to control nonlinear NEMS, we model their behavior with commercial 32768 Hz quartz tuning forks. We use a software-defined network analyzer that excites fork vibrations with continuous wave signals and records their amplitude and phase with respect to the excitation signal. We present preliminary results of our studies performed in air and in vacuum. Our data exhibits an onset of strong nonlinearity with a negative relationship between the fork's excitation amplitude and resonant frequency, similar to the response of NEMS. Next, we will concentrate on the transition between linear and nonlinear regimes. We believe that using a modulated excitation signal will enable us to keep the nonlinear oscillator under control.   

An Economical and Efficient Helium Recovery System for Vibration-Sensitive Applications

Here, we report the design of a liquefaction system that is ideal for recovering the helium (He) vapor from vibration-sensitive cryogenic instruments. We demonstrate its performance by recycling the boil-off from a commercial low-temperature scanning probe microscope (SPM). It features a very high He recovery rate and induces negligible vibration noise to the SPM. Given its adaptability, affordability, and homemade-friendly nature, we anticipate that our system will impact a broad spectrum of research fields.   

Modulus Aquatic Research Station with Automatic Vertical Profiling

Harmful algal blooms (HABs) pose a dangerous threat to both aquatic life and human health, largely due to their toxin-producing capabilities. The most common type of bloom-forming algae is cyanobacteria, commonly known as blue-green algae (BGA). BGA thrives in warm, nutrient-rich water, and both average surface water temperatures and nutrient loads are increasing in lakes across the globe due to climate change. The ability to forecast HAB formation is becoming an increasingly pertinent task, and it is impossible to give out early warning by manually taking field samples and then analyzing the samples in a laboratory. In order to model bloom dynamics and predict the onset of blooms, a long-duration and high frequency automatic monitoring system is needed. This engineering research project focuses on the development of such a monitoring station, consisting of an aquatic floating platform, an attached meteorological station, and a multiparameter probe for measuring various water quality parameters. A motorized reel was built to send the probe to specific depths in the water column at pre-configured periods, allowing for pseudo-continuous profiles of water quality parameters. Data is automatically transmitted to a cloud server so the data can be remotely accessed from anywhere with a WiFi connection. By using this device, future researchers and students will be able to collect high-frequency data over an extended period of time, which will make early warning HAB forecasts possible.   

Modular until it's Not – Imaging Fast, Hard X-Rays at NIF

The proposed multi-frame gated x-ray imager (MGXI) is a fast, hard x-ray imaging diagnostic for use in ICF and HED experiments at the National Ignition Facility (NIF), such as Compton radiography and hot spot imaging. MGXI has goals to image 10-100 keV x-rays with 100-1000 ps temporal resolution in 2-8 frames and >5% DQE. Modularity of the versatile testbed for initial MGXI component experimentation starts with testing microchannel plates (MCPs) under vacuum with an electron gun and a simple photodiode (PD) array. Simultaneously, MCPs will be modeled in Computer Simulation Technology (CST) to determine the effects an applied magnetic field has on the electron trajectories.   

Cryogenic Threshold Engineering in commercially available MOSFETs

Here we illustrate cryogenic threshold engineering by selecting a commercially avilable field effect transistor to minimise its threshold voltage at low temperature, reducing the necessary supply voltages for associated cryo-circuitry. We demonstrate DC characterisation of commercially available, low-voltage, FETs in the range 295K-1.5K, extracting key parameters such as subthreshold slope, threshold voltage and peak transconductance. We further demonstrate the applications of cryogenic threshold engineering by first simulating a common source amplifier and then cooling an amplifier designed with depletion mode n-type FETs. To quantify the improvement of in operation of the amplifier a Figure Of Merit (FOM), the ratio of Gain-Bandwidth-Product to power consumption is defined and measured in both simulation and experiment. We found in both simulation and experiment that an order of magnitude improvement in the FOM was attributed to the movement of the threshold voltage upon cooling. Whilst bellow 30K the FETs suffered from freeze-out, we believe this technique could be used to improve the power consumption of cryogenic electronics in areas such as quantum computing, where management of the thermal mode is critical.   

Superconducting Heatswitches with Diffusion Bonded Joints

Superconducting (SC) heat switches allow for the on-demand control of a thermal load between objects by exploiting the thermal properties of superconductors in their SC and normal states. Typical approaches for constructing SC heat switches include soldering or mechanically clamping a superconductor with a high conductivity metal, such as copper. In this work, we present the effects of diffusion-bonded aluminum-copper joints on the thermal conductance of a SC heat switch in the closed state. Samples were zero-field cooled to milli-Kelvin temperatures and subsequently driven to their normal state to measure the thermal conductance in the closed state. In-situ calibration was performed to account for any systematic variations in thermometry. The temperature-dependent thermal conductance of a diffusion-bonded SC heat switch was compared to a similar SC heat switch with indium-soldered joints. Preliminary results suggest an improved thermal conductance for the diffusion-bonded SC heat switch. Additional measurements in the open state and with minimum aluminum geometry variations are needed to assess the overall performance of these SC heat switches with different joint mechanisms.   

Innovative Transcranial Magnetic Stimulation Coil Designs Utilizing Multi-Magnetic Materials for Focal Brain Stimulation in Small Animals

Transcranial magnetic stimulation is a non-invasive therapeutic approach with proven efficacy in treating certain neurological disorders. To broaden the application of TMS to a wider range of neurological disorders, the induced electric field (e-field) must be able to target specific regions of the brain. Animal coil designs are promising for studying TMS effects and developing new procedures for treating various neurological and psychiatric disorders.

In this study, we used multi-magnetic materials in TMS coils for the first time to our knowledge. We also considered the non-linear, hysteretic behavior of the cores in our FEM simulations of induced e-field and magnetic field in the brain models of the rat. Our study involved e-field comparison across various coil configurations using our customized anatomically accurate rat head model. Iron-cobalt-vanadium (Permendur) alloy known for its high relative permeability, high saturation magnetization and low coercivity was used as the core material for all simulations. We have also introduced a shape-conforming, flexible, diamagnetic pyrolytic graphite with susceptibility of -4.5×10^-4 for our top performing coil. Simulation results were validated by comparing the simulated magnetic field results with experimental measurements obtained from the v-tip coil with a carbon steel AISI-1010 core at varying tip distances. This thorough study advances our knowledge of TMS coil designs and their optimization, particularly for small animal applications.   

Comparison of tissue parameters extracted from hyperspectral images by inverse adding-doubling and tissue indices

Hyperspectral imaging (HSI) is a noncontact, noninvasive method that uses UV-NIR light to capture the physiological and morphological properties of biological tissues. A promising use case of HSI is the study and diagnosis of various types of tumors by extracting tissue parameters, such as melanin and hemoglobin concentration. A well-established method for parameter extraction is the inverse adding-doubling (IAD) algorithm. Despite being faster than traditional methods like inverse Monte Carlo, it still does not allow real-time tissue parameter extraction.

This study examines various tissue indices, such as erythema and oxygenation indices, as an alternative to IAD.  First, the correlation between tissue parameters extracted with IAD and tissue indices was examined on simulated skin reflectance spectra. Then, we imaged various murine tumor models and human forearms using an in-house developed HSI system covering the 400–1000 nm spectral range. Finally, IAD-extracted tissue parameters were compared to calculated tissue indices.

Preliminary results indicate a positive correlation between melanin concentration and melanin indices, as well as blood oxygenation and oxygenation indices. Tissue indices show promise for real-time tissue property extraction from hyperspectral images.   

Enhanced Head Immobilization for Gamma Knife Radiosurgery

Elekta Icon Gamma Knife is a radiotherapy treatment system that delivers very precise doses of radiation to brain tumors, arteriovenous malformations (AVMs), and other neurological conditions. To treat the patient, their head has to remain still and cannot move more than 1.5mm. Currently, high precision is achieved by using a patient-specific thermoplastic immobilization mask on a rigid frame, in conjunction with video tracking of reflective markers placed on the frame and tip of the patient's nose. Head movements that exceed 1.5mm automatically stop delivery so the patient can be repositioned. Experience over the past several years with Gamma Knife at Mary Bird Perkins Cancer Center has shown that the immobilization mask adequately limits side-to-side head motion, but head pronation is not as well controlled. In order to combat this, an add-on brace was created in CAD software and 3D printed using resin. It presses against the upper lip and teeth of the patient to restrict head pronation and thus allow for controlled and uninterrupted treatment. Following the development of the brace, head movement will be tracked with and without the brace, and eventually the performance of the brace will be evaluated during Gamma Knife treatments.   

Re-evaluation of lethal radiation dose in Drosophila melanogaster using 350KeV electrons

The original goal of this research is to measure radiation dosages from 350KeV electron beam based on response to radiation of Drosophila melanogaster. 

As published earlier, LD50 is greater than 452Gy for all development stages. In this research, we look throughout from pupae stage into adulthood considering development rates with dose-dependent differences. Fruit flies were irradiated at the most sensitive time: the egg stage. Effective LD50 including long term effects is significantly reduced. For the maximum pupae population recorded at 173hr, LD50 was noted around 48Gy, while for the complete adult population at 310hr, LD50 was about 15Gy. The outcomes showed that if observed long enough, fruit fly eggs will not die right away after radiation, they will develop to the pupa, late pupa or adult formation phase and die at various stages. The concept of LD50 must be modified based on the observed stage of development.

The global aim is to identify optimal radiation effect conditions on fruit flies for the development of the next generation which may lead to the creation of a radiation-resistant biological system that can be applied to living organisms as well as be transferable to HeLa cells and other non-biological systems.   

Single module of a Compton camera detector for online beam range monitoring in proton therapy

The key advantage of proton therapy over conventional radiotherapy is the dose deposition pattern: unlike X-rays, protons are fully stopped in patient's tissues with a distinct maximum at the end of their range: the Bragg peak. This enables precise coverage of a tumor volume while sparing the nearby healthy tissues. However, accurate control of the proton beam range is still considered a challenge. The SiFi-CC (SiPM and scintillating Fiber based Compton Camera) group develops a method of in vivo proton range monitoring with a Compton camera. Such a detector exploits the Compton effect and registers prompt gamma rays emitted in interactions of protons with the tissues' nuclei. Our design is a trade-off between the camera performance and its cost. In our approach, both detector modules (scatterer and absorber) will consist of stacked scintillating fibers with dual readout via silicon photomultipliers. Our simulation studies have shown that such a solution is feasible and appropriate for online range monitoring in proton therapy. The scintillating material and fiber coating were chosen based on an extensive study of the fiber properties. I am going to present the overview of the SiFi-CC project and discuss the performance of a single module of a Compton camera in proton beam conditions.   

Validation of TMS Animal Phantoms That Mimic Conductivity and Anatomy of the Brain

Transcranial magnetic stimulation (TMS) has been found effective in the treatment of neurological and psychiatric conditions and is approved by the FDA to treat OCD, smoking cessation, and depression. Though this technology is by and large noninvasive, trials on live subjects are not always appropriate, which lead to the development of phantoms that mimic the electrical properties and anatomical features of the brain. These phantoms are individualized by computationally processing magnetic resonance images (MRI) and utilizing 3d printing technology to create molds for the brain regions. A well characterized composite of PDMS and carbon nanotubes (CNT) is used to fill the mold and mimic the conductivity of the native brain. Forming a network of CNT in the composite is crucial in reaching repeatable and uniform conductivities. One of several ways of achieving this is through high shear forces, which prevents haystacking of the CNT in the composite. 

These phantoms will allow for real time measurement of induced electric fields and voltages in the brain regions when stimulated by a time-varying magnetic field. Three dipole probes are placed neutrally orthogonal to create a triaxial dipole (TAD) probe that can measure the E field as a vector rather than just a point measurement. The phantom contains multiple TAD probes to help characterize the field.    

A High Speed, Solid, 3D Dosimeter Prototype

An important aspect of modern radiation therapy methods is a verification of dosimetric radiation delivery. To perform quality assurance of the dose delivery in a matter of minutes, a novel, solid detector prototype was built with water equivalent scintillators that were machined, cut, and arranged in a three-dimensional array. Roughly 1600 polystyrene rods doped with the organic scintillating agents P-Terphenyl and BisMSB were used to build the prototype. High-frame rate CCD cameras captured cross-sectional images of two sides of the scintillators. A neural network then used the scintillator images to reconstruct a three-dimensional image of energy distribution. This prototype was tested using a 9 MeV electron beam with conventional and ultra high dose rates, up to 600 Gy/s, at The Ohio State University Comprehensive Cancer Center. Here, the prototype design and construction details, the deep learning studies performed with GEANT4/GATE simulations, as well as the detector performance during beam tests are reported.   

The Effect of the Temporal Bone on Ultrasound Transmission

Focused ultrasound (FUS) has shown great promise in the field of neuromodulation. FUS is under investigation as a novel treatment for mesial temporal lobe epilepsy (MTLE) through modulating the hippocampus. The loss of energy transmission through a series of locations along a segment of ex vivo human skull has been investigated to determine the most effective treatment paths. Experimentally, a 0.5-MHz planar transducer was used to sonicate through two segments of ex vivo human temporal skull bone. Analysis of the scanned field enabled a determination of the level of attenuation and distortion of the transmitted signal. After successful transmission measurements of the temporal bone specimens, comparative analysis with simulations created using the Matlab package kWave was performed. A series of 2D simulations were compared with a matching scan performed on a segment of the skull, using density data as obtained from CT scans of the bone specimens. The resulting data will allow for the prediction of transmission fields for human patients using existing CT scans, enabling an assessment of the treatment path.   

Validation of Computational Blood Clot Elastometry Model Through Design and Testing of Magnetomotive Ultrasound Tissue-Mimicking Phantoms

Heart disease is the leading cause of death in the United States, with a significant percentage of these deaths being related to complications from blood clots. Although ultrasound can approximate the compressive stiffness (Young's modulus) of clots as a proxy for their age, a quantitative elastometry technique may be valuable for making clinical treatment decisions. Contrast-enhanced Magnetomotive Ultrasound (MMUS) coupled with a finite element model is currently under study as a possible solution. Using COMSOL Multiphysics, we designed a computational elastometry model of a clot submerged in a blood-like fluid and found the resonance frequencies of clinically relevant clot geometries. To validate our model, we designed blood clot-mimicking phantoms by setting gelatin in 3D printed molds and quantitatively measured Young's modulus using MMUS resonance frequency analysis. The resonance frequency that we measured for each shape agreed within one standard deviation and no more than 11% error with the computational model for the same geometry and was sufficiently precise to allow for differentiation among stiffnesses. This indicates that our computational model is realistic and may therefore allow us to detect Young's moduli with MMUS for a wide range of realistic blood clots.   

Robust Lung Segmentation Method from CT Images Using Wavelet Transform and K-Means Clustering

Lung segmentation from CT images is a critical task for early lung disease detection. However, existing methods are often limited by their sensitivity to noise and their inability to identify small and irregular lung structures. Here, we present a novel lung segmentation method using wavelet transform and k-means clustering. The proposed method first applies Gaussian smoothing to the input image to reduce noise. Then, the wavelet transform is used to decompose the image into a set of coefficients. These coefficients are then used to extract feature, which is used to train a k-means clustering algorithm. The clustering algorithm assigns each pixel in the image to one of two clusters: lung or non-lung. Finally, morphological operations are applied to the clustered image to remove noise and artifacts.

This algorithm gives an accuracy of 98.46%, DSC 46.15 %, and JSI 85.91%. The algorithm executed without applying gaussian filter and gives an accuracy of 98.48%, DSC 46.22 %, and JSI 86.18%. The mean values for these metrics were slightly higher indicating a marginal improvement in performance. The proposed method has several advantages over existing methods. It is more robust to noise, it can identify small and irregular lung structures, and it is relatively fast and efficient. Our algorithm can accurately identify and separate lung tissues from lung CT images, which can assist radiologists in diagnosing lung diseases.   

Heat Island Effect and Inner City Community Gardens

Urban community gardens are popular sources of locally grown fruits and vegetables that can mitigate the need to combat food desserts in our cities. This project is a study of the heat island effect on tomatoes grown in center city Philadelphia, compared to tomatoes grown in the pinelands of New Jersey at the Stockton University sustainability farm. Tomatoes are a good source of vitamin C, and phytonutrients lutein and lycopene, and are typically grown in both of these areas. We worked with nine varieties of tomatoes started from seedlings. We considered historical data and computer modeling in the study the heat island effect.   

Progress towards storage resonators for Bosonic circuit QED systems in the W-band

Recent progress in bosonic circuit QED (cQED) setups hold promise as a hardware efficient route to fault tolerant quantum computation. One of the core components of such a setup is a high-Q cavity which serves as long-lived quantum memory to store fragile quantum information, instead of storing it in the Hilbert space of the two-level system (qubit). In this work, we will present finite element electromagnetic simulations alongside measurement results on different copper “Pillbox” cavities designed in the W-band (75-110 GHz). Eventually, this cavity will host a Sapphire chip with a patterned nonlinearity and a readout resonator to demonstrate a bosonic cQED system with universal control over the memory state.   

Novel mm-Wave and InfraRed Filter Design for Reducing Quasiparticles in Superconducting Qubits

Nonequilibrium quasiparticle excitations can be a limiting source of error in superconducting qubits, causing relaxation, spurious excitation, and dephasing. One major source of quasiparticles is blackbody radiation from higher-temperature stages of a cryostat traveling down microwave cables. To mitigate this source of decoherence, high frequency signals (100-300 GHz) must be attenuated. Typically filters made with Eccosorb can accomplish significant attenuation, but a long filter length is required, which causes undesirable levels of attenuation in the microwave regime. We present work on designing and testing novel filters with greater high-frequency attenuation and less microwave attenuation. We show a novel meandering coplanar waveguide filter that can achieve greater than 40dB of loss above 100GHz and less than 1dB loss at 5GHz using a Corning glass dielectric, which has been shown to have attenuation which sharply increases at higher frequencies. We have used finite-element simulations to test various iterations of the design at microwave (1-10 GHz) and mm-wave (100-300 GHz) frequencies. Our simulations show loss more than 200x higher at 110 GHz than at 5 GHz. Further design optimizations could push this ratio even higher by increasing scattering of the mm-wave radiation. We discuss these improvements and experimental tests of filter efficacy.    

Synthesis and Fabrication of A15 Compounds for Superconducting Quantum Electronics

Recent advances in quantum technology have sparked interest in compound superconductors for fault-tolerant quantum circuits and superconducting detectors. Here, we review the potential for A15 superconductors to be integrated into quantum electronics. A15 intermetallic compounds are a family of cubic superconductors with critical temperatures up to 23 K. A15s were subjected to intensive research until interest waned due to the discovery of superconductivity in cuprates in the 1970s. In our work, we revisit A15s as promising superconducting alloys for applications where high kinetic inductance is required. We surveyed the literature for the various growth and characterization data available on 20+ A15 compounds, and we found that more than half of them were grown as single crystals, but thin film samples were able to achieve the highest critical temperatures. Additionally, A15 materials exhibit high disorder as evidenced by large critical fields, although this information is mostly available for bulk crystals. To fully assess the compatibility of A15s with superconducting circuits, further studies on their thin-film growth and cryogenic microwave characterization will be essential.   

Combining two gates in one

We present an example of optimising a type of multi-degree-of-freedom two-qubit gate( fSim) in superconducting qubit systems.We study how the static parameters in the system Hamiltonian and pulse-shaping affect gate speed and fidelity. Gate performance under relaxation noise ( T1) and dephasing noise ( T2) is also investigated.   

Creating a Database of Well-simulated Superconducting Quantum Circuit Elements

We introduce SQuADDS, a Superconducting Qubit And Device Design Simulation database, an open-source design database and simulation package engineered for the rapid design of superconducting qubit architectures. We present our simulation workflow using Qiskit Metal and ANSYS HFSS to create a database of modular circuit elements. We report on the robust validation of this methodology against experimental benchmarks.   

Exceptional entanglement transition: non-Hermiticity meeting non-classicality

The non-Hermitian (NH) extension of quantum-mechanical Hamiltonians stands as a transformative breakthrough in physics. Over the last two decades, a plethora of intriguing NH phenomena have come to light, observable in both quantum and classical systems. This convergence prompts a pivotal inquiry: what NH signature distinctly separates quantum mechanics from its classical counterpart? Addressing this query is pivotal for authentic NH quantum effects, a realm yet unexplored. This study bridges the gap by unveiling unique entanglement phenomena, including exceptional entanglement transition, manifesting at the EP of an NH interacting quantum system. We present concrete evidence of these purely quantum NH effects using a naturally-dissipative light-matter scheme, meticulously engineered within a superconducting circuit QED platform. Our findings establish the groundwork for the exploration of genuinely quantum-mechanical NH physics, marked by EP-enabled entanglement behaviors. This breakthrough expands our comprehension of quantum mechanics and promises innovative applications in various fields of science and technology.   

Parasitic free gate: An Error-Protected Cross-Resonance Switch in Weakly Tunable Architectures

We proposed an error-protected switch by combining a cross-resonance gate with a tunable coupler. The switch swaps the states of qubits between entangled and idle modes. In either mode, qubits can become free from stray couplings. We further utilize a weakly tunable qubit as an optimum coupler to bring the two modes parametrically near each other. This remarkably enhances the tuning process by reducing its leakage.   

Hardware-aware quantum process tomography via Bayesian inference

The Pauli transfer matrix can be experimentally determined by quantum process tomography, where measurements of an exponentially large number of observables subject to an exponentially large number of initial conditions completely characterize the quantum process. When the goal is to characterize a small number of quasi-static parameters in a known (hardware-dependent) Hamiltonian, this problem can often be simplified. This is the case, for example, in a common model of electron spin qubits in quantum dots. For this system, it is possible to exploit an analytic description of the Pauli transfer matrix given a two-spin Heisenberg exchange and a magnetic field gradient. By exploiting this analytic description, we show that Bayesian inference techniques can be used to adaptively optimize preparations and measurements to rapidly learn the relevant parameters of this two-qubit system.   

Multiqubit entangling gates with multi-exchange interactions between spin qubits

In the pursuit of optimizing quantum circuits, the prevailing quantum computing paradigm leverages a sequence of quantum gates, primarily composed of one- and two-qubit gate operations from a universal set. While these gates are versatile, their utilization often necessitates lengthy sequences, posing challenges for quantum coherence and circuit complexity. Notably, for semiconductor quantum dot systems employing spin qubits, the exchange interaction between neighboring spin qubits has emerged as the standard mechanism for enabling two-qubit gates. However, the short-range nature of this exchange coupling imposes a significant overhead when implementing such gates between distant qubits.

In this study, we explore an alternative approach to optimize quantum circuits, where the exchange interaction is harnessed simultaneously across multiple qubits. This technique not only simplifies the practical implementation but also holds promise for enhancing quantum circuit efficiency. Through numerical optimization methods, we seek to identify optimal quantum circuits using this multi-qubit exchange interaction approach.

Our research investigates the efficacy of this method in generating typical entangled states and compares it with the conventional exchange-based approach. We demonstrate that the multi-qubit exchange interaction approach considerably reduces the depth of quantum circuits, showcasing its potential for efficiently implementing large-scale quantum computations. This work underscores the practicality and efficiency of employing multi-qubit exchange interactions as a valuable tool for quantum circuit optimization.   

Characterization of Polar Surface Effect on Silicon Carbide Defect States for Quantum Material Application Using DFT approach.

Silicon Carbide (SiC) polytypes, specifically 4H-SiC and 3C-SiC, emerge as promising host materials for defects, comparable to diamond, with the ability to house defect states serving as spin qubits. Ideally, it is desirable to position defects within a range of 10-30 Angstroms from the surface for effective spin readout. While extensive investigations into various bulk SiC defects have been conducted using both Density Functional Theory (DFT) and experimental methods, there needs to be more exploration into the impact of the SiC surface on these defects. We aim to characterize the defect states, namely the Divacancy (V_SiV_C) and Nitrogen-Vacancy (N_cV_Si)^-1, in the vicinity of 3C-SiC (111) and (001) surfaces as well as 4H-SiC (0001) surface. Using DFT methods, we calculate energy levels, zero phonon lines, and zero-field splitting of the defects as a function of the depth from the surface, surface orientation, and passivation. In general, surfaces exhibit surface states due to dangling bonds at the slab-vacuum interface, a phenomenon observed in materials such as SiC, Au, and Al. Furthermore, SiC, a naturally polar material, generates asymmetric slabs, resulting in spontaneous polarization across the slab. Thus, Silicon Carbide defects are influenced by both surface states and the internal electric field across the slab arising from the opposing dipole moments on the C- and Si-terminated surfaces. This study uses DFT methods to investigate the polar surface effect on silicon carbide defect states.   

Spectroscopy of silicon vacancy centers in Silicon Carbide

Color centers are point defects in crystals that can provide an optical interface to a long-lived spin state. They are one of the leading candidates for qubit platforms. The two most studied color centers are nitrogen vacancy center in diamond and silicon vacancy center in silicon carbide. In this work, we focus on experimentally studying the creation of silicon vacancy centers in silicon carbide. Due to its non-linear properties and wide bandgap, SiC enables the path for having integrated color center platforms and distributed quantum information processing. We will present the irradiation process performed on 500 um thick SiC samples using 3-8MeV electron beam while varying the electron fluence to create silicon vacancy defects. In addition, the spectroscopy setup used to detect these defects through photoluminescence will be shown. Photoluminescence is used to characterize vacancy defects by using resonant laser excitation where electrons are excited from ground state to excited state and relaxes back to the ground state emitting a photon at 861nm. The density of point defects is quantified by the intensity of the photoluminescence spectra. The goal of this project is to study and tune the electron beam parameters to create controlled and localized defects.   

Electric driving of the excited orbitals of the NV- center in the ultrastrong regime

The NV center in diamond is a versatile spin qubit widely used for nanoscale sensing of magnetic and electric fields. Under cryogenic conditions (T<7K), it displays lifetime-limited spin-selective optical transitions, which have been used for the entanglement of remote spins [1].  Those transitions however suffer from their sensitivity to electric and strain fields such that different NVs require active stabilization to interact.

Here, we show the electric dipole responsible for this instability can also be exploited for control of the optically excited states. We use microwave electric fields to drive Rabi oscillations between two optically excited orbitals (Ex, Ey) in the ultra strong regime. Photoluminescence excitation of those states show clear Rabi splitting as well as second order terms. Notably, this driving suppresses first order fluctuation of the electric field in the NV transverse plane and can be used for fast tuning of the NV optical resonance. These results open prospect for enhanced electric sensitivity and to optimize NV-NV optical entanglement.

[1] Pompili, Matteo, et al. "Realization of a multinode quantum network of remote solid-state qubits." _Science_ 372.6539 (2021): 259-264.   

Development of a Frequency-Locking Optical System for Metastable-State Control in Trapped Barium Ions

Trapped atomic ions are one of the most promising approaches to realizing quantum computers. One active topic in trapped-ion quantum information research focuses on the so-called “omg” architecture which utilizes a combination of optical, metastable, and ground-state qubits, where qubit states are encoded in the internal electronic states of each ion. Among the ion species available, barium ions offer several advantages for implementing omg schemes, such as long-lived metastable states and isotopes with favorable values of nuclear spin. The barium ion has a key transition of relevance to the omg architecture, between the S_1/2 ground state and D_5/2 state, that occurs at a wavelength of 1762 nm. Due to the long lifetime of the D_5/2 metastable state, a laser with very narrow linewidth is needed to drive the transition with precise control and achieve long coherence times. We demonstrate an optical system to lock a 1762 nm laser to an ultra-high finesse cavity by utilizing the Pound-Drever-Hall (PDH) technique. Experimental results from single-ion spectroscopy validate the achievement of the desired narrow linewidth, thus paving the way for quasi-dual-species operation within a chain of identical ions and potentially eliminating challenges in the manipulation of dual-species chains of ions.   

Quantum Simulation of Spin Chains with Trapped Atomic Ions

We perform quantum simulations of spin chain Hamiltonians using 171-Yb+ in two trapped ion platforms: a four-blade linear trap and a next-generation monolithic chip trap with individual and simultaneous optical addressing. Natively, we realize Ising-like Hamiltonians with long-range spin-spin interactions that obey approximate power-law falloff (r^(-α)) with distance r across the chain, where α is controlled by the detuning of the optical dipole forces from the collective sidebands of motion [1]. Using quantum simulation tools such as Trotterization and Floquet engineering, we generate nonnative Hamiltonians for long-range XY and Heisenberg-like spin chain models [2]. Another tool, dynamical decoupling, enhances coherence by averaging out noise such as Stark shift via global pulse sequences [2]. Using four ions, we demonstrate our quantum simulation toolbox to generate the Haldane-Shastry model, a quantum integrable and exactly solvable Heisenberg-like chain in the inverse square law regime (α=2) [2].

[1] C. Monroe, W. C. Campbell, L. -M. Duan, Z. -X. Gong, A. V. Gorshkov, P. Hess, R. Islam, K. Kim, G. Pagano, P. Richerme, C. Senko, and N. Y. Yao, Rev. Mod. Phys. 93, 025001 (2021).

[2] W. Morong, K. S. Collins, A. De, E. Stavropoulos, T. You, and C. Monroe, Phys. Rev. X Quantum 4, 010334 (2023).   

Harnessing LC Oscillators for Quantum Entanglement and Quantum Operations

We emulate quantum entanglement and Bell states in classical electrical circuits by representing quantum states as voltage oscillations of LC oscillators. In general, an N-qubit quantum system is modeled using 2^N LC resonators and quantum operations performed by applying time-dependent perturbations to the resonator and connecting capacitors. We demonstrate how such perturbations can be used to perform the Hadamard and CNOT operations to generate maximally perturbed states in a two-qubit Bell state circuit. The emergence of entangled and Bell states are manifested in the time-evolution behavior of the voltage states in which the first and third resonators exhibit in-phase sinusoidal voltage oscillations with 70.7% reduced amplitudes compared to the initial oscillations while the voltages of the other two LC oscillators remain negligible. We analyze the probability distribution and statevector representation of the Bell states through circuit simulations and IBM Quantum Composer tools and confirm the successful realization of quantum entanglement in the electrical circuit. This research opens the door to utilizing classical electrical components for simulating quantum phenomena with potential applications in quantum cryptography and quantum computing paradigms.   

Gate-Tunable Circuit QED Experiment in a Three-Dimensional Cavity Architecture

Hybrid quantum systems based on nanowire Josephson junctions enable the realization of novel qubits such as gatemons, 0-<!--[if gte msEquation 12]> style='mso-bidi-font-style:normal'>π qubits and Andreev qubits. Furthermore, circuit quantum electrodynamics (circuit QED) can serve as a technique to probe Majorana zero modes. Previous related cQED experiments were performed in a two dimensional (2D) architecture involving superconducting coplanar waveguides. However, a magnetic field perpendicular to the substrate can significantly degrade the resonator performance and vortex pinning for in-plane magnetic field compatibility requires strenuous efforts. In this work, we present a three-dimensional copper cavity architecture design, compatible with a DC gate line and magnetic field, for probing hybrid devices. We test the design by demonstrating the gate-tunable qubit-cavity interaction and the qubit spectroscopy. Our technique allows the probing of hybrid superconducting-semiconductor devices in a 3D circuit QED architecture where gate voltages and a magnetic field are necessary.     

Cryogenic Microwave Wafer-Scale Characterization of Superconducting Resonators for Improved Fabrication Yield

Superconducting resonators are used for the readout of superconducting transmon qubits. As quantum computers scale, fabrication yield becomes a critical component for success. Errors during the fabrication process results in larger distributions and offsets from designed parameters. For superconducting devices, this can lead to issues with frequency crowding and weak coupling to the qubit. We used a 4 K wafer prober to form a statistical data set for the center frequency of superconducting readout resonators across an entire wafer. The resonators were measured with a single port probe in hanger-mode configuration. We were able to produce wafer maps showing frequency variation which can be used to inform fabrication process.   

Exploring the mechanisms of transverse relaxation of copper-phthalocyanine spin qubits

Quantum information science has catalyzed a search for suitable qubit platforms that would enable powerful, at-scale quantum devices. Paramagnetic spins in molecular crystals have emerged as promising spin-qubits, owing to their coherence time and potential scalability via synthetic chemistry. A key factor governing qubit performance is the phase relaxation time, which limits the number of quantum operations. Here, we combined numerical methods and dynamical decoupling experiments to investigate dephasing of electron spins in copper-phthalocyanine (CuPc) embedded in a $eta$-XPc matrix, where X represents an non-paramagnetic atom. We find that at cryogenic temperatures the CuPc electron dephasing is dominated by interactions with off-resonance electrons in the material — a factor overwhelmingly dominant over interactions with nuclear spin species. We confirm this insight by comparing experimental results (including echoes and spin-locking experiments) with simulations. Our research further unveils that the XPc matrix has a marginal impact, even when X contains hydrogen nuclear spins, in principle enhancing the nuclear spin bath. Other effects, such as the stability of the molecular crystal as a function of X, influencing the T1 longitudinal relaxation times, might be more pronounced. 

These insights are crucial for tailoring the molecular matrix to achieve specific thermal or optoelectronic properties, hinging significantly on the choice of the X atom, with potential impacts on advancing molecular spin qubit research   

Physical gate-set tomography

Physical models of quantum gates can directly incorporate experimental degrees of freedom, such as laser power or microwave phase, but the forward simulation required to use these models can result in impractical overhead in computational time. In this poster, we develop a method for efficient, accurate interpolation of quantum process matrices over physical parameter space, and we apply our method to study the sensitivity of quantum applications at both the gate and circuit level.  We then implement an extension of gate set tomography (GST) that provides a comprehensive view into the errors suffered by a quantum information processor. In its standard form, GST fits a general Markovian model to experimental data in terms of process matrices that are often difficult to interpret. Our extension to this method uses process matrices interpolated over physical parameters in the optimization loop of GST to directly estimate physical model parameters, providing a clear description of the errors in a quantum processor, while reducing the required number of GST sequences by orders of magnitude compared to its standard form.

This material was funded in part by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research's Early Career Research Program. SNL is managed and operated by NTESS LLC, a subsidiary of Honeywell International, Inc., for the U.S. DOE's NNSA under contract DE-NA0003525. The views expressed here do not necessarily represent the views of the DOE or the U.S. Government.   

Synergetic quantum error mitigation by randomized compiling and zero-noise extrapolation for the variational quantum eigensolver

We present a quantum error mitigation approach for the variational quantum eigensolver (VQE), demonstrating particular efficacy in addressing coherent noise. Our investigation reveals that even a small amount of coherent noise can produce considerable errors, which are difficult to suppress through conventional error mitigation techniques. The proposed error mitigation scheme offers a significant reduction in these errors by employing a synergistic combination of randomized compiling (RC) and zero-noise extrapolation (ZNE). This approach functions by utilizing RC to transform coherent noise into stochastic Pauli noise, which can then be predictively and effectively suppressed via ZNE. We provide numerical simulations of VQE applied to small molecular systems using the unitary coupled cluster ansatz with single and double excitations (UCCSD). Our findings show that the proposed strategy can effectively diminish energy errors induced by various forms of coherent noise (including over-rotation and crosstalk noise) by up to two orders of magnitude.   

Tracking Dispersive Shifts Beyond the Resonance Linewidth Using Real-Time Measurement-Based Feedback

In circuit QED, dispersive readout is the established technique for measuring qubits, qudits, quantum sensors, and other quantum devices: different quantum states induce different shifts in the frequency of a coupled readout resonator. One challenge is engineering the system couplings to maximize the signal‑to‑noise ratio (SNR) of the returning microwave probe tone. Decreasing the resonator linewidth can increase SNR, but the response saturates when the dispersive shift becomes comparable to the linewidth. In a sensor, the standard technique to address this saturation is to adjust the parameters of the sensor itself--stabilizing the response--and treating the parameter adjustment as the measurement signal. However, most circuit QED resonators are designed to be fixed‑frequency and thus cannot be adjusted. Here, we address this challenge by using real-time measurement-based feedback to determine the resonance frequency and adjust our probe frequency to track the resonance. We show that this frequency-tracking can be achieved in less than one microsecond on an FPGA-based feedback system such as the Quantum Machines OPX controller. We discuss the advantages and limitations of our technique, and how it can be used for quasiparticle detection experiments and to improve qubit and qudit readout SNR.   

Closed-loop gate-set optimization via quantum optimal control for an ensemble of nitrogen vacancy centers in diamond

Precise control of a quantum system is a prerequisite for quantum information, quantum computing, and quantum metrology. Quantum gates on ensembles of nitrogen vacancy (NV) centers usually suffer from decoherence and other influences from the surrounding spin environment, imperfect state preparation and therefore limited total operation fidelity. Large state preparation and measurement (SPAM) errors cause the typically used quantum process tomography to fail. We explore the applicability of gate set tomography in combination with maximum likelihood estimation and randomized benchmarking for the closed-loop optimization and evaluation of whole gate sets for the usage in e.g. sensing pulse sequences with ensembles of NV centers.   

A Rubik's Cube inspired approach to Clifford synthesis

The problem of decomposing an arbitrary Clifford element into a sequence of Clifford gates is known as Clifford synthesis. Drawing inspiration from similarities between this and the famous Rubik's Cube problem, we develop a machine learning approach for Clifford synthesis based on learning an approximation to the distance to the identity. This approach is probabilistic and computationally intensive. However, when a decomposition is successfully found, it often involves fewer gates than existing synthesis algorithms. Additionally, our approach is much more flexible than existing algorithms in that arbitrary gate sets, device topologies, and gate fidelities may incorporated, thus allowing for the approach to be tailored to a specific device.   

Practical Quantum Computation via Circuit Partitioning and Qubit Reuse

Effective quantum computation on near-term hardware is, in part, constrained by a limited qubit count. In this work, we introduce a quantum circuit partitioning method that combines and builds upon existing techniques of circuit and gate cutting and qubit-reuse compilation. Our proposed approach can drastically reduce the number of qubits required for a quantum circuit by alternating steps of cutting and qubit reuse ordering.

Our method is tailored for quantum processors that allow mid-circuit measurements and resets, a feature that enables repurposing qubits during the computation. Unlike existing methods, our wire cutting approach can cut through the same wire multiple times and require up to a single ancilla qubit, leveraging mid-circuit measurement and reset capabilities. This reduces the number of required ancilla qubits by allowing their reuse. As a result, qubit reuse enables more ways to perform circuit partitioning.

We experimentally verify our work on the Quantinuum H1 trapped ion quantum processor, where we realize a specific class of ansatz circuits used in variational quantum algorithms that are well-suited for our partitioning technique. We demonstrate that, given a proper circuit implementation, our methods provide an evident improvement in physical qubit cost and the number of possible ways to perform circuit partitioning.   

Utilizing Numerical Instantiation to Enable Circuit Resizing

Mid-circuit measurement and reset (MMR) is a combination of primitive operations that various quantum technologies manufacturers have integrated into their platforms, including superconducting, trapped-ion, and neutral-atom-based quantum hardware vendors. MMR's original purpose was to implement quantum error correcting codes, but it has also enabled new circuit optimization approaches in the NISQ-era. These approaches optimize a circuit by reducing their required number of qubits in a technique called circuit resizing, allowing users to execute larger programs on cheaper, smaller quantum chips with potentially fewer gates. Not all circuits are resizable; previous algorithms can only resize circuits when they satisfy certain gate dependence relationships, severely restricting the potential set of programs that can benefit from this optimization. This work introduces a numerical-instantiation-based resynthesis algorithm that restructures non-resizable circuits into resizable ones. Our algorithm is resource-efficient and topology-aware, removing the need for expensive mapping and increasing the potential for optimization. We reduce the number of qubits by 21.4% in otherwise un-resizable circuits. When compiling to linear and T topologies, we show a CNOT gate reduction of 34.9% and 48.5%, respectively, compared against state-of-the-art compilation pipelines.   

Belief propagation as a partial decoder

One of the fundamental challenges in enabling fault-tolerant quantum computation is realising fast enough quantum decoders. We present a new two-stage decoder that accelerates the decoding cycle and boosts accuracy. In the first stage, a partial decoder based on belief propagation is used to correct errors that occurred with high probability. In the second stage, a conventional decoder corrects any remaining errors. We study the performance of our two-stage decoder with simulations using the surface code under circuit-level noise. When the conventional decoder is minimum-weight perfect matching, adding the partial decoder decreases bandwidth requirements, increases speed and improves logical accuracy. Specifically, we observe partial decoding consistently speeds up the minimum-weight perfect matching stage by between 2x-4x on average depending on the parameter regime, and raises the threshold from 0.94% to 1.02%.   

A Specification Format and a Verification Method of Fault-Tolerant Quantum Circuits

Quantum computations are expressed in general as quantum circuits, which are specified by ordered lists of quantum gates. The resulting specifications are used during the optimisation and execution of the expressed computations. However, the specification format makes it difficult to verify that optimized or executed computations still conform to the initial gate list specifications: showing the computational equivalence between two quantum circuits expressed by different lists of quantum gates is exponentially complex in the worst case. In order to solve this issue, this work presents a derivation of the specification format tailored specifically for fault-tolerant quantum circuits. The circuits are considered a form consisting entirely of single qubit initialisations, CNOT gates and single qubit measurements (ICM form). This format allows, under certain assumptions, to efficiently verify optimized (or implemented) computations. Two verification methods based on checking stabilizer circuit structures are presented.   

Critical Properties of Weak Measurement Induced Phase Transitions in Random Quantum Circuits

Competition between entangling dynamics and wave function collapsing measurements in quantum many-body systems can induce a measurement induced phase transition (MIPT) between phases with distinct entanglement structure. MIPTs in random quantum circuits are described by non-unitary Conformal Field Theories (CFTs) with zero central charge. We study the properties of these CFTs in Haar random circuits subject to various measurement models by computing the Lyapunov exponents, central effective charge, and bulk critical exponents. Specifically, we compute these quantities in two models of weak measurements, a measuring device modeled as a continuous Gaussian probe and a softened version of the standard projective measurement, at various measurement strengths. The effect of weak measurements on the universality class of the MIPT will be discussed.   

Simulating fermionic scattering using a digital quantum computing approach

Collider experiments play a central role in understanding the subatomic structure of matter, as well as developing and verifying the fundamental theory of elementary particle interactions. However, comprehending scattering processes at a fundamental level in theory remains a significant challenge. The necessary involved time evolution and the with time rapidly increasing bond dimension in Tensor Networks make simulating the scattering process with this classical method challenging. On the other hand, quantum computers hold great promise to efficiently simulate real-time dynamics of lattice field theories. In this work, we take the first step in this direction toward simulating fermionic scattering using a digital-quantum computing approach. Specifically, we propose a method based on Givens rotation to prepare the initial state of the fermionic scattering process, which consists of two fermionic wave packets with opposite momenta. With a time evolution operator based on the underlying Hamiltonian acting on the initial state, the two fermionic wave packets propagate and interact with each other. Using the lattice Thirring model as the test bed and the Qiskit Statevector simulator, we observe an elastic scattering between fermions and antifermions in the strong interaction region. In addition, we clearly observe an entanglement production in the scattering process. We consider our work also as an indispensable step towards a quantum simulation of a scattering process on a real quantum device.   

Study of long-range Ising model using irreducible representations of SU(2)

Ising models dictate a broad class of natural spin-dynamics bridging integrability and chaos, of interest to quantum simulation and metrology. When they exhibit permutation symmetry by infinite-range interactions, they collapse to a single irreducible representation (irrep) of SU(2) of the collective spin (the symmetric subspace). Finite but long-range interactions tend to preserve much of the collective character, avoiding chaos when initialized in the largest SU(2)-irrep¹. Meanwhile irreducible spherical tensors form physically motivated orthonormal operator bases within irreps, and admit generalizations² across multiple irreps, but the generalized tensors' algebras beg exploration. We truncate a transverse Ising model with slow-decaying interactions, keeping first-order accessible subspaces from this symmetric irrep, and analytically decomposing the truncated Hamiltonian into generalized spherical tensors. We study the dynamics as the system leaks into lower-spin irreps via observable phenomena like dynamical quantum phase transitions. We develop Heisenberg equations of motion on these spherical tensors, and numerically probe the truncation's quality of approximation for finite-size systems.

¹Lerose, Alessio, "Theory of robust quantum many-body scars in long-range interacting systems." arXiv:2309.12504

²Klimov, A.B. and Romero, J.L., "A generalized Wigner function for quantum systems with the SU(2) dynamical symmetry group." 2008 J. Phys. A: Math. Theor. 41 055303   

Lossy Compression for Schrödinger-style Quantum Simulations

Simulating quantum circuits on classical hardware is a powerful and necessary tool for developing and testing quantum algorithms and hardware as well as evaluating claims of quantum supremacy in the Noisy Intermediate-Scale Quantum NISQ regime. Schrödinger-style simulations are limited by the exponential growth of the number of state amplitudes which need to be stored. In this work, we apply scalar and vector quantization to Schrödinger-style quantum circuit simulations as lossy compression schemes to reduce the number of bits needed to simulate quantum circuits. Using quantization, we can maintain simulation fidelities >0.99 when simulating the Quantum Fourier Transform, while using only 7 significand bits in a floating-point number to characterize the real and imaginary components of each amplitude. Furthermore, using vector quantization, we propose a method to bound the number of bits/amplitude needed to store state vectors in a simulation of a circuit that achieves a desired fidelity, and show that for a 6 qubit simulation of the Quantum Fourier Transform, 16 bits/amplitude is sufficient to maintain fidelity >0.9 at 10⁴ depth.   

VQE in the Early Fault-Tolerant Era

We examine the performance of the variational quantum eigensolver (VQE) on a small surface-code architecture. VQE and its variants are commonly considered for implementation on near-term hardware due to their ability to trade off shorter circuit depths for high sampling costs, making them less vulnerable to errors. In the early fault-tolerant era, where many errors may still escape undetected, this advantage may still be appealing; however, VQE also relies on rotations by small angles, which consume many T states. We show that even relatively low physical error rates, and correspondingly lower logical error rates, can still lead to significant degradations in performance, depending on what choices are made in how those rotations are approximated.   

Alternative photonic encodings for multi-photon simulation of molecular polaritons on quantum devices

In a Fabry-Perot cavity, molecules can strongly couple to the photon field, allowing access to higher energy states that may drastically change their chemistry. However, simulating these polaritonic states can be computationally intractable, with each photon number potentially resulting in a different state. As a result, most methods only investigate the effects of one or two photons. By simulating these systems on a quantum computer, we may gain advantages in allowing for higher Fock states. We investigate the effects of light-matter coupling on a quantum device, and report on various ways of encoding photonic Fock states on the quantum computer.   

Rabi Oscillations and Entanglement between two Rydberg Atoms in an Optical Cavity studied by the Jaynes-Cummings Model and Quantum Circuits on Qiskit

Rydberg atoms are highly excited atoms in which one electron has a large principal quantum number. Due to their unusual atomic properties, Rydberg atoms are promising building blocks of two-qubit gates and light-atom quantum interfaces in quantum information processing. For two atoms at close distance (< 10 μm) the Rydberg blockade prevents the two atoms to be simultaneously in the excited state whereas this blockade is absent for atoms far apart. Recently, this effect was used to engineer a quantum processor based on two-dimensional arrays of neutral atoms which are trapped and transported by optical tweezers. Motivated by these experiments, we study the light-atom interaction and entanglement of two Rydberg atoms interacting by the Rydberg blockade in an optical cavity using the Jaynes-Cummings model. We find a rich variety of Rabi oscillations and entanglement as a function of initial conditions and interaction time, which may be used to generate two-qubit gates. Furthermore, we develop and simulate a quantum circuit of this system using Qiskit, an open-source software development kit designed to emulate the operation of a real quantum computer and discuss the fidelity of the quantum circuit.   

Single-Qubit Stabilization via Quantum Reservoir Engineering

Superconducting circuits have emerged as a powerful platform for quantum computing and quantum simulation. The long coherence, strong interactions, and high controllability make superconducting circuits ideal for studying many-body phases of synthetic quantum matter comprised of microwave photons. We leverage parametric modulation to engineer tunable baths synthesized by driven-dissipative processes in our superconducting circuit lattice, and apply them to study quantum dynamics in both coherent and driven-dissipative settings. I will present our experimental efforts to realize efficient single qubit stabilization using the engineered baths, and progress towards multi-qubit stabilization.   

Mapping a topology-disorder phase diagram with a quantum simulator

The competition and interplay of topology and disorder has been one of the most famous topics in the field of condensed matter physics. In addition to the intuitive tendency to bring the system into a topologically trivial and localized phase, it has been discovered that disorder can also induce nontrivial topology and transport. To reveal rich and diverse phase structures, mapping phase diagrams plays an important role in both theoretical and experimental sides. Quantum simulation provides a prospective way to study the target model, explore the phase diagram and reveal the underlying mechanism. Thanks to the unprecedented controllability, superconducting quantum simulators have been introduced to investigate complex many-body physics and bring thought experiments into reality. To our best knowledge, the effort to map a phase diagram with a rich structure is still lacking. Here we report a systematic experimental study of the topology-disorder phase diagram with 32 qubits on a programmable analog quantum simulator. We implement one-dimensional (1D) disordered dimerized tight-binding models over a wide parameter range and observe diverse phases, including the topological Anderson insulator (TAI) and the inverse Anderson localization (IAL). Our experiment manifests the efficiency, accuracy and flexibility of the superconducting-circuit device and paves the way to the demonstration and understanding of many-body phenomena with noisy intermediate-scale quantum simulators.   

Simulating conical intersections with multiconfigurational methodson a programmablesuperconducting quantum processor

Quantum computing has become an emerging technology in chemical simulations,

as they have been proved to provide expontential accerelations in

computational effort solving quantum many-body problems .

For the time being, quantum devices available to us are generally

noisy intermediate-scale quantum (NISQ) processors, which are generally

composed of tens (or slightly over one hundred) of qubits, if possible.

Regarding to the exponential growth in usage of gates in fully quantum

algorithms such as quantum phase estimation, hybrid quantum-classical

(HQC) algorithms such as Variational Quantum Eigensolver (VQE), has

been considered as prefered in NISQ-era practices, since they usually

require shallower circuits and less coherence time, although at the

expense of additional classical computing treatments. In both simulation

and real quantum devices, variational quantum algorithms has been

successfully used in acquiring energy diagrams for molecular systems.

Other than energy properties, there are applications such as calculating

electronic/energy transition rate, molecular

spectropy, dynamical polarizabilities

and Born-Oppenheimer/non-adiabatic or quantum dynamics.   

Quantum Equation of Motion in Active Spaces for Computing Molecular Excitation Energies in Near-Term Quantum Computing

Determining the properties of molecules and materials is one of the premier applications of quantum computing. A major question in the field is: how might we use imperfect near-term quantum computers to solve problems of practical value? Inspired by the recently developed variants of the quantum counterpart of equation-of-motion (qEOM) approach and the orbital optimized variational quantum eigensolver (oo-VQE), we present a quantum algorithm for the calculation of molecular excitation energies and excited states using the active space approximation.   

Evaluating Ground State Energy with Low-Depth Quantum Circuit and High Accuracy

Solving electronic structure problems is widely recognized as one of the most promising applications of quantum computing. However, due to limitations imposed by the coherence time of qubits in the NISQ (Noisy Intermediate Scale Quantum) era, it's vital to design algorithms with shallow circuits.

In this project, we develop a novel Variational Quantum Eigensolver (VQE) ansatz based on the QCC (Qubit Coupled Cluster) [1, 2] approach, which demands optimization over only n parameters rather than the usual n+2m parameters, where n represents the number of Pauli word time evolution gates e^-itP, and m is the number of qubits involved.

We evaluate the ground state energy of O₃, Li₄, Cr₂, and C₄H₈, using CASCI(4,4) method in conjunction with the enhanced QCC ansatz, UCCSD (Unitary Coupled Cluster Single-Double) ansatz, or FCI (Full Configuration Interaction) method as the active space solver. Furthermore, we assess our enhanced QCC ansatz on two distinct quantum hardware platforms, one superconducting-based and one trapped-ion-based. In the end, we conclude with a gate count analysis on both setups.

References

(1) Ryabinkin, I. G.; Yen, T.-C.; Genin, S. N.; Izmaylov, A. F. Journal of Chemical Theory and Computation 2018, 14, 6317–6326.

(2) Ryabinkin, I. G.; Lang, R. A.; Genin, S. N.; Izmaylov, A. F. Journal of Chemical Theory and Computation 2020, 16, 1055–1063.   

Collective-Excitation Spectra in Quantum Spin Glasses Out of Equilibrium

There exists an established connection between long-range interacting quantum spin glasses and combinatorial optimization problems, which serves as the main motivation behind the field of quantum annealing. On one hand, in disordered quantum spin systems, the focus is on exact methods (such as the replica trick) that allow the calculation of system quantities in the limit of infinite system and ensemble size. On the other hand, when solving a given instance of an optimization problem, disorder-averaged quantities are of no relevance, as one is solely interested in instance-specific, finite-size properties (such as the true solution). Here, we apply the Schwinger-Keldysh formalism to the semi-classical fluctuations around a spin mean-field [PRX Quantum extbf{4}, 030335 (2023)] to obtain the excitation spectrum of the non-equilibrium dynamics along the annealing path. For the example of the quantum Sherrington-Kirkpatrick spin glass, we show that this method provides approximate access to the instance-specific location (along the path) and size of the minimal gap, which is a quantity crucial to quantum annealing.   

Drone- and Automobile-Based Quantum Key Distribution

Quantum communication systems provide the ability to transmit provably secure messages. When interconnected, these systems act as nodes to form a larger quantum network. While these nodes are typically connected via fiber-based channels or fixed free-space point-to-point links, there have been many advancements in the last decade that enable these nodes to include rapidly deployable, re-configurable, and wireless mobile platforms such as aerial drones and satellites. When working with these mobile nodes, their size, weight, and power profiles (SWaP) pose constraints that potentially impact the overall system performance. Here, we will discuss our progress towards developing a compact robust quantum communication platform that is deployable on both drone-based and automobile-based mobile nodes. Quantum-secured random keys are distributed amongst a system of these mobile nodes using a modified BB84 quantum key distribution (QKD) protocol; distances of 10-20 km should eventually be possible. A mobile system such as this would further expand and enhance nascent existing quantum networks by integrating wireless quantum communication capabilities.   

Communincation-efficient blind quantum machine learning with quantum bipartite correlator

Distributed quantum computing is a promising computational paradigm for performing computations that are beyond the reach of individual quantum devices. Privacy in distributed quantum computing is critical for maintaining confidentiality and protecting the data in the presence of untrusted computing nodes. In this work, we introduce novel blind quantum machine learning protocols based on the quantum bipartite correlator algorithm. Our protocols have reduced communication overhead while preserving the privacy of data from untrusted parties. We introduce robust algorithm-specific privacy-preserving mechanisms with low computational overhead that do not require complex cryptographic techniques. We then validate the effectiveness of the proposed protocols through complexity and privacy analysis. Our findings pave the way for advancements in distributed quantum computing, opening up new possibilities for privacy-aware machine learning applications in the era of quantum technologies.   

Towards More Feasible Quantum Networks Based on Cavity-QED and Continuous-variable Codes

Quantum repeaters (QRs) are the main approach to realize long-distance quantum communication. The main building blocks of conventional QRs are high-efficiency quantum memories (QMs) which are necessary for a practical realization. Here we propose a memoryless QR protocol based on cavity-QED using optical states encoded in one of the rotation-symmetric bosonic codes (RSBCs). Such rotational symmetry enables the fidelity of the transmitted state to be partially restored by doing the syndrome measurement. We evaluate the performance of our repeater protocol by calculating the secret key rate (SKR) in a QKD scenario as our figure of merit. We compare different RSBCs and for the one with the highest SKR calculate the cost coefficient. Those values are comparable with other existing memoryless QR systems. In addition, the performance of other RSBCs is improved adding multiple channels and selecting specific syndrome measurement outcomes by using QMs or cluster states. Next we compare both approaches by determining the tradeoff of the main parameters, such as the coherence time and the gate efficiency. Our results show that that this repeater system might be realized with the state-of-art technology.   

Impact of quantum noise on Ramsey spectroscopy

We investigate the impact of quantum noise on Ramsey spectroscopy involving a single probe qubit.Considering the impossibility of a full reset of the quantum bath after each measurement shot, we show how the entanglement between system and bath adversely affects the accuracy of frequency estimation in a Ramsey experiment. Our findings are rooted in exact formulas for the expectation values of qubit observables interacting with a bosonic bath, assuming a general zero-mean Gaussian stationary pure dephasing process. These formulas were derived using a cumulant expansion technique, which offers an efficient avenue for the analytical study of non-Markovian open quantum systems. Furthermore, we conducted numerical simulations in which the bath comprised a finite number of qubits subject to classical stochastic noise. Consistent with the analytical findings, these simulations demonstrated a significant impact of the quantum bath on the system's measurements. Our analysis sets the stage for a comprehensive characterization and precise control of quantum noise across a range of configurations employed in sensing and estimation applications.   

Quantum Enhanced Parameter Estimation Without Entanglement

Entanglement is generally considered necessary for achieving the Heisenberg limit in quantum metrology. We construct analogues of Dicke and GHZ states on a single N + 1 dimensional qudit that achieve precision equivalent to symmetrically entangled states on N qubits, showing that entanglement is not necessary for going beyond the standard quantum limit. We define a measure of non-classicality based on quantum Fisher information and estimate the achievable precision, suggesting a close relationship between non-classical states and metrological power of qudits. Our work offers an exponential reduction in the physical resources required for quantum-enhanced parameter estimation, making it accessible on any quantum system with a high-dimensional Hilbert space.   

Robust quantum sensing via statistics

Many quantum sensing algorithms exist for measuring a broad range of signals, for example low-frequency signals [1] or high-frequency signals [2]. However, for signals with limited coherence times, such methods are insufficient, since long measurements average the signals to zero. Here, we propose and analyze a method to robustly detect the amplitude of such signals, which protects the result from phase and frequency changes, and can account for amplitude distributions.

In our method, we measure the standard deviation of the signal instead of the amplitude. We show that this has the same sensitivity as conventional methods for a high signal-to-noise ratio (SNR), and goes towards an N^1/4 (N: number of data points) dependence for a low SNR. Moreover, the memory requirements and computational complexity of this method are low, which suits long measurements.

One important application is the search for light dark matter [3]. For the axion and dark photon candidates, the dark matter field can be measured with nitrogen-vacancy centers as an effective periodic magnetic field with a limited coherence time. Given the minuscule signals, long measurement times are required, which makes the proposed method ideal.

[1] Phys. Rev. Appl. 18, 034058 (2022).

[2] Phys. Rev. X 12, 021061 (2022).

[3] arXiv:2302.12756 (2023).   

Optimal entanglement testing for ranging and communication

Given a system A known to be entangled with another system B, the entanglement testing problem asks one to identify the system B mixed among m>= 2 identical systems. This problem serves as a model for the measurement task encountered on the receiver's end during quantum ranging and entanglement-assisted communication, as discussed in [Phys. Rev. Lett. 126, 240501 (2021)]. In general, the optimal measurement approach for such a task is expected to involve joint measurements on all m+1 systems. However, surprisingly, we demonstrate that this is not the case when the subsystems containing system B are subjected to entanglement-breaking noise. Utilizing the recently developed measurement technique of correlation-to-displacement conversion, we present a specific design for the entanglement testing measurement that can be implemented with local operations and classical communications (LOCC) on the m+1 systems. Furthermore, we prove that this measurement approach achieves optimality in terms of error probability under noisy conditions. When applied to quantum illumination, our measurement design enables optimal quantum illumination ranging in scenarios with low signal brightness and high levels of noise.

*NSF, DARPA, ONR, Cisco Inc.   

The tunnel-time problem and a solid-state platform for quantum metrology via weak value enhancement

We propose and construct a solid-state platform to explore the tunnel-time problem [1] which is related to the Larmor clock, and build upon this construct to provide for a weak-value enhancement for quantum metrology [2]. Quantum metrology that employs weak-values can potentially effectuate parameter estimation with an ultra-high sensitivity and has been typically explored across quantum optics setups. Recognizing the importance of sensitive parameter estimation in the solid-state, we propose a spintronic device platform to realize this. The setup estimates a very weak localized Zeeman splitting by exploiting a %Fabry-P'erot resonant tunneling enhanced magnetoresistance readout. We establish that this paradigm offers nearly optimal performance with a quantum Fisher information enhancement of about ten-thousand times that of single high-transmissivity barriers. The obtained signal also offers a high sensitivity in the presence of dephasing effects typically encountered in the solid state. These results put forth definitive possibilities in harnessing the inherent sensitivity of resonant tunneling for solid-state quantum metrology with potential applications, especially, in the sensitive detection of small induced Zeeman effects in quantum material heterostructures. 

[1] A. Mathew, K. Y. Camsari and B. Muralidharan, Phys. Rev. B, 105, 144418, (2022). 

[2] M. Subramanian, A. Mathew and B. Muralidharan, Phys. Rev. Applied (2023) (ArXiv: 2211.17060).    

Progress Towards an All-Optical Quantum Diamond Magnetometer

Precision magnetometry via nitrogen vacancy (NV) centers in diamond typically utilizes microwaves to drive the center's spin state transitions. However, delivering microwaves becomes technically challenging in extreme environments such as inside a nuclear fusion reactor. Under such conditions, an all-optical quantum diamond magnetometer offers a microwave-free approach to measuring magnetic fields. Measurements can be made by leveraging the fact that an NV-center's fluorescence quenches in the presence of an off-axis magnetic field. In this poster, we present basic principle and experimental progress towards this all-optical quantum diamond magnetometer.   

Dynamical criticality of single magnetic nanoparticles near phase transition

Understanding the critical phenomena of magnetic nanoparticles (MNPs) is crucial to both fundamental physics and the state-of-the-art technology. NV centers in diamond simultaneously provide nanoscale spatial resolution, high magnetometry sensitivity and large temporal dynamic range under ambient conditions, and therefore are ideal quantum sensors for studying the dynamical criticality of MNPs. We developed a broadband sensing protocol with NV center spins to study the magnetic fluctuations of single magnetic nanoparticles near the critical point. We observed paramagnetic and superparamagnetic fluctuations of the MNP and extracted the correlation time and amplitude of the magnetic fluctuations.   

Machine learning-enchanced quantum sensors for smart sensing

Characterising the time over which quantum coherence survives is critical for any implementation of quantum bits, memories and sensors. The usual method for determining a quantum system’s decoherence rate involves a suite of experiments probing the entire expected range of this parameter, and extracting the resulting estimation in post-processing. Here we present an adaptive multi-parameter Bayesian approach, based on a simple analytical update rule, to estimate the key decoherence timescales (T₁, T₂^∗ and T₂) and the corresponding decay exponent of a quantum system in real time, using information gained in preceding experiments. This approach reduces the time required to reach a given uncertainty by a factor up to an order of magnitude, depending on the specific experiment, compared to the standard protocol of curve fitting. A further speed-up of a factor ∼ 2 can be realised by performing our optimisation with respect to sensitivity as opposed to variance.   

Quantum reservoir computing with a superconducting resonator in the semi-classical regime

Quantum reservoir computing is a promising approach to quantum neural networks capable of solving hard learning tasks on both classical and quantum input data [1]. Multiple implementation schemes were proposed, using basis states of a qubit system [2], basis states of a system of coupled quantum oscillators [3], or field-quadratures of a system of parametrically coupled quantum oscillateurs [4] as reservoir neurons. However, experimental realizations were lacking. Here we implement experimentally reservoir computing on a quantum oscillator in the semi-classical regime. We use the fundamental mode of a superconducting resonator as a quantum oscillator, and its field quadratures as reservoir neurons. We sample the two quadratures multiple times for the same input data point in order to increase the number of effective neurons. We encode the input data in the amplitude of the resonant drive, and we set the amplitude range in the Kerr regime, in order to obtain the nonlinearity that is essential for data processing. We test the performance of the superconducting reservoir on a simple benchmark task for reservoir computing, that is sine and square waveform classification. This task specifically tests the memory of the neural network and thus its capacity to process temporal data series. We demodulate each pair of output neurons from a 20 ns oscillator emission. Using 8 samples per data point and thus 16 effective neurons, we obtain > 99% accuracy on this task. This is an improvement in terms of the number of necessary neurons compared to reservoir computing with classical oscillators : with a single spintronic nano-oscillator, this task requires 24 effective neurons [5]. This is the first experimental implementation of reservoir computing with superconducting circuits and an important step towards the experimental realization of quantum reservoir computing with the basis states of coupled quantum oscillators that will fully exploit the quantum nature of this system. [1] S. Ghosh, A. Opala, M. Matuszewski, T. Paterek, and T. C. H. Liew, "Quantum reservoir processing" npj Quantum Information 5, 23 (2019). [2] K. Fujii and K. Nakajima, "Harnessing Disordered-Ensemble Quantum Dynamics for Machine Learning", Physical Review Applied 8, 024030 (2017). [3] Julien Dudas, Baptiste Carles, Erwan Plouet, Alice Mizrahi, Julie Grollier, and Danijela Markovic, "Quantum reservoir computing implementation on coherently coupled quantum oscillators" npj Quantum Inf 9, 64 (2023). [4] G. Angelatos, S. Khan, and H. E. T¨ ureci, "Reservoir Computing Approach to Quantum State Measurement Gerasimos", ", Physical Review X 11, 041062 (2021). [5] M. Riou, F. A. Araujo, J. Torrejon, S. Tsunegi, G. Khalsa, D. Querlioz, P. Bortolotti, V. Cros, K. Yakushiji, A. Fukushima, H. Kubota, S. Yuasa, M. D. Stiles, and J. Grollier, "Neuromorphic Computing through Time-Multiplexing with a Spin-Torque Nano-Oscillator", , IEEE Trans Electron Devices, (2017)   

Quantum and Classical Machine Learning Studies of Optimal III–Nitride Epitaxy

Considerable interest exists in the development of machine learning–based approaches for identifying optimal materials designs and synthesis conditions. In this work, data describing over 100 plasma–assisted molecular beam epitaxy (PAMBE) growth trials each of GaN and InN have been organized into separate, composition–specific data sets. For each growth record, the complete set of experiment parameters are associated with a measure of crystallinity as determined by reflection high–energy electron diffraction (RHEED) patterns. Additionally, a Brag–Williams measure of lattice disorder (S²) is included as a second figure of merit for investigation. Quantum and classical supervised learning algorithms – including logistic regression, tree–based algorithms, and quantum variational circuits – are trained on the data and used to study which growth parameters are most statistically important for influencing crystallinity and S². The probabilities of obtaining monocrystalline GaN and InN thin film crystals are predicted across processing spaces of the two most important synthesis parameters. The machine learning predictions of these growth characteristics agree with published values for obtaining single crystalline GaN and InN thin films. S² is also predicted across the same processing spaces. The predictions indicate that different growth conditions are of interest depending on whether a single crystalline sample or a well–ordered lattice (as measured by S²) is desired.   

A Quantum Data Fitting Approach to Parametrize Dependences of ICF Implosion Asymmetries

A quantum data fitting algorithm was developed to characterize the correlations between measured core asymmetries and the sources of nonuniformities in laser-driven inertial confinement fusion (ICF) implosion experiments. This approach constructs an ICF experimental observable as a superposition of quantum many-body wave (QWF) functions in terms of Legendre polynomials. The multi-parameter correlations are explored by analyzing the behavior of the corresponding density matrix that stores a minimal set of QWF eigenstates. The objective is to quantify the mapping relationship between measured core asymmetries and their sources. This machine learning algorithm will be ultimately applied to develop a real-time symmetry control system to improve the fusion energy output by minimizing the low-mode asymmetry. The quantum data fitting model was applied to construct mapping relationships for a wide range of experimental observables in OMEGA implosions. The model performs well in fitting ICF implosion metrics, including fusion yields and areal densities, and asymmetries observed in nuclear and x-ray image measurements. A decent correlation was found between hot-spot flow velocities and target positioning, beam pointing, and beam-to-beam laser power balancing. By parameterizing the dependencies of core asymmetries, the causality of low modes can be identified, guiding future efforts to mitigate the impact of low-mode nonuniformities on ICF implosions.   

Quantum Polyspectra for Uncompromising and Universal Evaluation of Quantum Measurements

The analysis of a continuous measurement record poses a fundamental challenge in quantum measurement theory. Different approaches have been used in the past as records can, e.g., exhibit predominantly Gaussian noise, telegraph noise, or clicks at random times. This poster summarizes our latest findings, showing that quantum measurements from all the aforementioned cases can be analyzed in terms of higher-order temporal correlations of the detector output and be related to the Liouvillian of the measured quantum system. The comparison of temporal correlations via so-called quantum polyspectra is based on expressions derived without approximation from the stochastic master equation [1] and automated without requiring manual post-processing of the detector output. This allows for fitting of system parameters such as tunneling rates in a quantum transport experiment [2]. The very general stochastic master equation approach includes coherent quantum dynamics, environmental damping, and measurement backaction at arbitrary measurement strength. This enables a systematic evaluation of quantum measurements from the realms of conventional spin noise spectroscopy, quantum transport experiments, and, as our newest finding, ultra-weak measurements with stochastically arriving single photons [3,4]. [1] Hägele et al., PRB 98, 205143 (2018), [2] Sifft et al., PRR 3, 033123 (2021), [3] Sifft et al. PRA 107, 052203, [4] Sifft et al., arXiv:2310.10464   

A simple proof for the equivalence of cost function concentration and gradient vanishing

Barren plateau problems are usually studied based on the vanishing of the gradient for parametrized quantum circuits. However, an explicit parametrization is not necessary and a (parametrization-free) Riemannian optimization has various advantages. Here, we report on a simple proof, establishing the equivalence of cost function concentration and gradient vanishing in the Riemannian optimization of quantum circuits. When the variable unitaries are sampled according to the uniform Haar measure, the cost function variance is strictly equal to half the variance of the Riemannian gradient. Thus, the barren plateau problem can be diagnosed equally well by studying cost function concentration. In many cases, the cost variance is easier to assess than the gradient variance. This report complements arXiv.2104.05868, which proves the equivalence of cost concentration and gradient vanishing in Euclidean space, and has the same implication as arXiv.2011.12245, namely that neither gradient-based optimization nor gradient-free optimization can resolve the barren plateau problem.   

Assessing Energy Estimation Algorithms for Early Fault-Tolerant Quantum Computers

Early fault-tolerant quantum computers (FTQCs) are likely to be typified by not only a limited number of logical qubits, but modest logical error rates and the relatively significant overheads associated with implementing non-Clifford operations. Recent years have seen the development of numerous variations on quantum phase estimation (QPE) that promise to be well-adapted to the constraints of early FTQCs – but it is unclear which will achieve the best performance in energy estimation for even the smallest instances. In this contribution, we will compare models of several resource-limited approaches to QPE in terms of robustness to logical errors, the impact of algorithmic errors, and projected runtime as a function of accuracy. We will focus primarily on QPE applied to eigenvalue estimation for Trotterized Hamiltonian simulation, with the aim of staking out resource requirements for small classically simulable benchmark problems that might become viable on systems with thousands of physical qubits.   

Block encoding implementation of matrix product operators

Qubitization has recently emerged as an innovative and versatile algorithm in the quantum simulation area and beyond. It can be traditionally split into two separate routines: block encoding, which encodes a Hamiltonian in a larger unitary, and signal processing, which applies almost any polynomial transformation to such a Hamiltonian using rotation gates [1]. Block encoding typically constitutes the bottleneck of the entire operation and several problem-specific techniques were introduced to overcome this problem [2, 3].

Our work presents a method to block-encode a Hamiltonian based on its matrix product operator (MPO) representation. Specifically, we encode every MPO tensor in a larger unitary of dimension D + 2, where D is the number of subsequently contracted qubits. Given any system of size L, the total amount of ancillaries for our block encoding scales as O(L + D), while the circuit’s decomposition in one and two-qubit gates requires O(L2^D+2 ) operations.

[1] J. M. Martyn, Z. M. Rossi, A. K. Tan, and I. L. Chuang, Grand unification of quantum algorithms, PRX Quantum 2, 040203 (2021).

[2] D. W. Berry, C. Gidney, M. Motta, J. R. McClean, and R. Babbush, Qubitization of arbitrary basis quantum chemistry leveraging sparsity and low rank factorization, Quantum 3, 208 (2019).

[3] S. Takahira, A. Ohashi, T. Sogabe, and T. S. Usuda, Quantum algorithms based on the block-encoding framework for matrix functions by contour integrals (2021), arXiv:2106.08076 [quant-ph].   

Magic of Random Matrix Product States

Magic, or nonstabilizerness, characterizes how far away a state is from the stabilizer states, making it an important resource in quantum computing. 

In this paper, we study the magic of the 1-dimensional Random Matrix Product States (RMPSs) using the L₁-norm measure. We firstly relate the L₁-norm to the L₄-norm. We then employ a unitary 4-design to map the L₄-norm to a 24-component statistical physics model. By evaluating partition functions of the model, we obtain a lower bound on the expectation values of the L₁-norm. This bound grows exponentially with respect to the qudit number n, indicating that the 1D RMPS is highly magical. Our numerical results confirm that the magic grows exponentially in the qubit case.    

Quantum Scrambling Mereology under Long-Time Dynamics

The recent work of Zanardi et al. associated each possible partition of a quantum system with an operational subalgebra and proposed that the short-time growth of the algebraic out-of-time-correlator ("A-OTOC") is a suitable criterion to determine which partition arises naturally from a system's unitary dynamics. We extend this work to the long-time regime. Specifically, we consider the long-time average of the A-OTOC ("A-OTOC LTA") as our metric of subsystem emergence; under this framework, natural system partitions are characterized by the tendency to, on average, minimally scramble information over long time scales. We derive an analytic expression for the A-OTOC LTA under the non-resonance condition (NRC). This is then applied to several examples in which we perform minimization of the A-OTOC LTA both analytically and numerically over relevant families of algebras. For simple cases subject to the NRC, minimal A-OTOC LTA is shown to be related to minimal entanglement of the Hamiltonian eigenstates over the emergent system partition. Finally, we conjecture and provide evidence for a general structure of the algebra which minimizes the LTA for a given NRC Hamiltonian.   

Entanglement conditions and entanglement measures

This project explores bounds on entanglement negativity using operator inequalities,

building on the results of [1].

We are looking for a way to quantify entanglement, as an alternative to calculating

the full negativity, which would otherwise require the computation of the

partial transpose of the reduced density matrix, a laborious procedure for largedimensional

systems.

Instead, for non-PPT states, by choosing an appropriate set of operators it is possible

to gain quantitative information about the entanglement by using the inequalities

in [1]. This can then be converted into a lower bound on the negativity.

We then provide different ways this procedure can be carried out, and we give several

examples.

[1] M. Hillery, M. S. Zubairy, Phys. Rev. Lett. 96, 050503 (2006)   

Performing high-fidelity single qubit gates on the biased noise architecture of Kerr-Cat qubits

The energy barrier seperating the computational states of the Kerr-Cat qubit allows for a biased noise architecture. At the same time it makes gates that are supposed to change the state of the qubit less reliable and makes designing high-fidelity gates challenging. We explore the effects of detuning and single photon drives that map the initial states out of the regular code space while the gate is in process and return it to the code space when the gate finishes. This way we can cicumvent the effect of the energy barrier and realize reliable gates.   

Quantum Technology Master's Internship Program at University of Oregon: Hands-on Training for Future Quantum Engineers

As Quantum Industry scales up on the path towards maturity, it is becoming increasingly clear that there needs to be a more robust talent pipeline apart from the current one that relies primarily on PhD level workforce [1,2]. Following the successful model of the already established master's internship programs at University of Oregon [3,4], we have designed a new five academic quarters Quantum Technology Master of Science program. The program incorporates two academic quarters of hands-on practical classes tailored for the skills needed for the quantum industry and pairs the students with industry or national labs partners for internships for as much as three academic quarters. In this presentation, we discuss the practical skills we focus our curriculum on based on our conversations and feedback from the quantum ecosystem leaders and outline the choices we have made in designing our curriculum.

 

[1] M.F. J. Fox, B.M. Zwickl, and H. J. Lewandowski, Preparing for the quantum revolution: What is the role of higher education?, Phys. Rev. Phys. Educ. Res. 16, 020131 (2020).

[2] C.D. Aiello et. al., Achieving a quantum smart workforce, Quantum Sci. Technol. 6 030501 (2021).

[3] https://internship.uoregon.edu/

[4] https://electrochemistry.uoregon.edu/   

Faithful geometric measures for genuine tripartite entanglement

We present a faithful geometric picture for genuine tripartite entanglement of discrete, continuous, and hybrid quantum systems. We first find that the triangle relation $mathcal{E}^alpha_{i|jk}leq mathcal{E}^alpha_{j|ik}+mathcal{E}^alpha_{k|ij}$ holds for all subadditive bipartite entanglement measure $mathcal{E}$, all permutations under parties $i, j, k$, all $alpha in [0, 1]$, and all pure tripartite states. It provides a geometric interpretation that bipartition entanglement, measured by $mathcal{E}^alpha$, corresponds to the side of a triangle, of which the area with $alpha in (0, 1)$ is nonzero if and only if the underlying state is genuinely entangled. Then, we rigorously prove the non-obtuse triangle area with $01$, and the triangle area is not a measure for any $alpha>1/2$. Hence, our results are expected to aid significant progress in studying both discrete and continuous multipartite entanglement.   

Title: Using Machine Learning to Isolate and Fit Optical Emission Lines of Gaseous Nebulae

The growing volume of archived spectral data together with the anticipated volumes of data from future telescope missions necessitate the development of new, efficient methods of analyzing spectral data. Machine learning technologies present one possible approach to automatic and effective spectra analysis. In this work, we demonstrate a machine learning–based approach to automatically identifying and characterizing features of interest in optical emission spectroscopy data of gaseous nebulae. To start, the continuum must be identified, fit and removed from the spectral data. After analyzing the continuum, a trained classifier model differentiates between the spectral emission lines and noise in the signal. With the emission lines identified, a clustering algorithm is used to isolate each peak before it is fit to a Voigt profile. From the optimized profile, the characteristic values (width, height, central wavelength, etc.) are determined for each peak identified within the spectra. The characteristics of each line can be matched to a corresponding atomic transition that emits light at an optical wavelength. This approach is demonstrated by analyzing archived HST/STIS spectra of the binary star Eta Carinae.   

Training Convolutional Neural Networks with Artificial Data to Classify Scintillator Data

Isomeric states are sensitive to changes in nuclear structure. Observing evidence of isomeric transitions is important to expanding our knowledge of nuclear structure as a whole. Our detector is a monolithic inorganic planar scintillator coupled to a position-sensitive photomultiplier tube, designed to measure energy deposited from β particles, internal conversion electrons, and γ rays. However, energy depositions that occur very close together in space and/or time are unrecoverable by the current analysis pipeline, and the datasets' size makes hand-analysis impossible. This drives the development of a new method to produce artificial scintillator data and a machine learning solution based on convolutional neural networks trained on artificial data for the purpose of classifying experimental data. This method has promising results in both classification of single vs multiple interactions and using regression to find the energy and position of interactions in artificial scintillator data.   

Machine-learning the angle-resolved spectral function of a hole in a quantum antiferromagnet

Understanding charge motion in a background of interacting quantum spins is a basic problem in quantum many-body physics. The most extensively studied model for this problem is the so-called t-t'-t''-J model, where the determination of the parameter t' in the context of cuprate superconductors was inconclusive. Recently we reported [1] that the model Hamiltonian parameters can be accurately predicted by using a fully connected feed-forward neural network (FFNN) to learn the angle-integrated spectral functions, i.e. the density of states (DOS), of a mobile hole in the t-t'-t''-J model. Here, we present a systematic study of the angle-resolved spectral functions. With a dataset of about 3.4x10^4 spectral functions generated in the self-consistent Born approximation, we show that the patterns produced by the principal component analysis, an unsupervised machine learning method, for k = (π/2, π/2), (π, 0), (π/2, 0) and (π/5, π/5) are ear-like, similar to those for the DOS, but heart-like for k = (0, 0) where the quasiparticle spectral weight is vanishing. Nevertheless, FFNN allows for accurate prediction of 93% of the Hamiltonian parameters by using the full k = (0, 0) spectral function with root mean squared error less than 0.007, compared with 99% for k = (π/2, π/2), (π, 0) and 100% for the DOS. Our results suggest that it may be possible to predict material parameters by deep learning angle-resolve photoemission spectroscopy (ARPES), including the laser-based ARPES where the k points are most accessible near the zone center k = (0, 0). [1] J. Lee, M. R. Carbone, and W. Yin, Phys. Rev. B 107, 205132 (2023).   

Broadband on-chip spectrometer enabled by machine learning methods

We present a novel machine learning-based approach for high-accuracy broadband spectrum reconstruction in on-chip random spectrometers. Furthermore, we generalize the concept of random spectrometers using random matrix theory and introduce a new spectrometer design that offers a smaller footprint while maintaining equivalent performance.   

Artificial intelligence-based modeling for predicting precipitates in aluminum alloys

In this study, we tried to predict the precipitation phase that can be precipitated as a stable phase in aluminum matrix using artificial intelligence with simulation database. OQMD (Open Quantum Materials Database) is a database that contains structural properties of vast materials and thermodynamic properties based on DFT calculations. First of all, in OQMD, based on lattice mismatch, search for precipitates that are likely to exist in a stable or metastable phase with the host aluminum lattice at the same time, and extract various factors such as lattice constant, formation energy, and volume per atom to create a basis data for machine learning. Among the precipitates of the refined data, those that could exist as alloys were classified by referring to TCAL8 (TCS Al-based Alloy Database), experimentally proven alloys were selected and classified through machine learning. We tried to implement effective classification performance by modifying the CNN algorithm, which leverages a strong deep structure. And through the results of this machine learning, it is possible to predict new stable precipitation phases that are worth experimentally researching in addition to the previously known aluminum alloys.   

Connecting polymer network mechanical properties with molecular-level behavior through data science

Polymeric materials are ubiquitous in nearly every aspect of modern society and are continuously transforming the way human beings interact with physical world. Despite many publications by the scientific community, the generated polymer data hasn’t been efficiently aggregated to provide a comprehensive picture of polymer network properties. Herein, utilizing a recently developed polymer graph data model CRIPT (Community Resource for Innovation in Polymer Technology), the mechanical properties and molecular characteristics of polymeric materials in hundreds of literature reports were aggregated and used to generate different Ashby plots. Specifically, a GPT-4 zero-shot prompt was utilized in conjunction with traditional scientific publication database search prompts for identifying useful papers related to the mechanical properties of associative polymer networks. The mechanical properties data were then manually extracted and classified based on different measurement techniques, including tensile testing and oscillatory rheology. In terms of molecular characteristics, the data related to both strands and junctions were recorded, such as backbone glass transition temperature, bond energy and dissociation rate. The generated Ashby plots are meaningful in terms of two aspects, (1) advancing fundamental understanding of the relationship of network macroscopic properties and molecular level behavior, (2) future development of polymeric materials with desired properties combination.   

Indexing topological numbers on images by transferring chiral magnetic textures

Topological analysis finds extensive application across diverse research domains, unveiling intricate features and structural relationships inherent in geometric objects. Specifically, within the realm of data analysis, the exploration of the topological properties of various images yields rich insights into the underlying geometric information they encapsulate. This research introduces a novel approach for investiigating the topological properties of arbitrary grayscale images. The method leverages a straightforward procedure borrowed from two-dimensional magnetism studies to compute topological numbers. Machine learning techniques are employed to imprint chiral magnetic textures onto the images, followed by the direct computation of the topological number. Computation of topological number is achieved by integrating the solid angles formed by adjacent spin vectors within the converted images. Our method successfully and consistently identifies the topological numbers of various grayscale images, exhibiting robust performance even in the presence of minor noise. Moreover, we underscore the method's efficacy and potential applications by applying it to an analysis of the topological characteristics present in handwritten digits within the MNIST dataset.   

Machine Learning for the Discovery and Optimization of Organic Dyes

Organic dyes have a variety of applications in modern life. They constitute many of the colors used in textile technology, and have advanced material uses such as dye-synthesized solar cells and organic light emitting diodes (OLEDs). Many of these applications depend on the photonic and electronic structure of the molecule, which can often be understood though DFT and TD-DFT. However the tailored design of dyes for specific applications remains a challenge for scientists and engineers; mainly due to the expense involved in calculating the relevant properties, but also the oftentimes narrow intersection of properties required for tailored applications (a wool dye must me water insoluble, nontoxic, have a net positive charge, be photostable, etc). Here, we present a machine learning based tool for the design and discovery of tailored organic dyes. Machine learning models are used to screen large libraries of molecules and predict their application based on their intersection of properties. A few of the applications included in this tool are textile dye, OLED, food coloring, and photon harvesters. It is our hope that the widespread use of this tool by materials scientists and engineers will allow for an acceleration of dye discovery and a lessening of experimental burden.   

Quantifying the effect of realistic variations in sequence-define macromolecule aggregate morphology with supervised machine learning

Block copolymers have the capacity to self-assemble into an assortment of intricate architectures, with applications in things like drug delivery and personalized medicine. New techniques in chemistry allow for increasing control over these architectures through sequence control at the monomer level rather than the block level, greatly expanding the horizons for the design of their properties. However, chemical synthesis is imperfect, and inherent stochasticity in synthesis and self-assembly poses a significant challenge for the precise modeling and control of these systems. While it is known that different monomer sequences result in different morphologies, predicting the exact response to variability with the monomer sequence is a challenging problem. In this work, we utilize an unsupervised machine learning method to quantitatively characterize the morphologies of self-assembled model copolymers. We find that the morphology response to sequence variability can be accurately predicted using neural networks, and we identify preferred pathways through the low-dimensional morphology space. This analysis sheds light on how sequence variability can be tolerated and perhaps even controlled to design sequence defined copolymers for technological applications.   

Prediction of Frequency-Dependent Dielectric Function for Solid Materials: A Multi-Fidelity Machine Learning Approach with Physical Insights

The quest for innovative solid materials, ideally suited for integration into next-generation optoelectronic devices, demands the development of accurate and efficient tools for predicting frequency-dependent optoelectronic properties. Data-driven predictive models can efficiently screen a broad spectrum of materials, alleviating the scalability constraints of first-principles methods like Density Functional Theory (DFT) while retaining their accuracy. In this study, we employ deep graph neural networks (GNNs) to forecast the frequency-dependent complex dielectric function of solid materials. We implement regularizations in the loss function to refine the error distribution and enhance GNN precision regarding physical features such as band gaps, resonant peak locations, and function smoothness. Our dataset encompasses 17,805 crystal structures generated using the OptB88vdW DFT functional and 7,358 refined using the more accurate Tran-Blaha modified Becke Johnson (MBJ) potential. We employ transfer learning to fine-tune our GNNs, enabling us to compute absorption coefficients with MBJ-level accuracy. The synergy of advanced ML techniques, including GNNs, physically informed learning, and transfer learning across multi-fidelity datasets, yields precise predictions of the frequency-dependent dielectric function, enhancing generalizability beyond observational domain and advancing optoelectronic device development.   

Development of Artificial Intelligence-Based Forcefields To Model Tunnel Barriers In Superconducting Qubits

In this study, we developed inter-atomic potential models to predict surface reactions between atomic configurations of water and TMA (Tri-Methyl-Aluminum) within the context of Atomic Layer Deposition (ALD) using Artificial Intelligence (AI). The main goal of the ALD process is to generate a thin alumina layered less than 1 nanometer tunnel barrier as a part of the building block of the Josephson Junctions for superconducting qubits. Depositions of water that deliver Oxygen and TMA that carries Aluminum are alternated during deposition; each layer should be as atomically conforming as possible to guarantee full coverage and thus no leakage to enhance the quantum circuit's fidelity. To ensure a high-quality Alumina tunnel barrier, understanding the atomic interactions between water and TMA is crucial, and the Machine Learning Interatomic Potential (MLIP) using AI can be employed to reduce the time and cost while guaranteeing the accuracy of quantum mechanics as well. We systematically evaluated the efficacy of the MLIP by assessing the resulting surface reactions and dynamics during each half-cycle of ALD process. The computing works have been performed using NERSC supercomputing facility and Missouri State University' sAI workstation.   

CryinGAN: Design and evaluation of point-cloud-based generative adversarial networks using disordered interface structures

Generative models have received significant attention in recent years for materials discovery, but current efforts have mostly focused on generating simpler unit cells, and less attention has been given to advancing these models for more complex disordered materials. These models have also been developed by evaluating on the new, unverified materials being generated, resulting in limited metrics to evaluate model performance. In this work, we demonstrate how developing and evaluating generative models using a fixed set of disordered materials can improve these models for more complex materials, through direct comparisons between training and generated structures. Using a disordered Li₃ScCl₆-LiCoO₂ battery interface as our material system, we tested different point-cloud-based generative adversarial network architectures that further include bond distance information in the discriminator, instead of just atom coordinates. By analyzing the energy and structural features of the generated data, we were able identify reasons for the success/failure of design choices across architectures. We will show that our best performing architecture, Crystal Interface Generative Adversarial Network (CryinGAN), is capable of generating low-interface-energy structures with > 250 atoms that are energetically and structurally similar to the training structures.   

Probing Physics-Informed Generative Representations of Many-Body Wavefunctions

The inclusion of physics-informed constraints has been shown to improve the performance of neural networks, particularly within the context of solving partial differential equations. Here, we adopt a similar strategy for generative models, including GAN and VAE, and apply this method to simulated ground state snapshots of 1D XXZ spin chains. We investigate how incorporating relevant observables into the models helps them recover the underlying physical structure of the input data, including ferromagnetic, antiferromagnetic, and paramagnetic phases. By choosing the optimal physical features, this method can be used in order to more accurately represent unknown wavefunctions when given experimental data.   

Applying a Convolutional Neural Network for Cancer Cell Image Segmentation

The recent resurgence in AI has enabled scientists to use neural networks for efficiently identifying trends in large data sets and has also brought about new ways that biological processes can be studied. Specifically, analyzing the behaviors of certain macrophage and breast cancer cocultures grown in vitro. A convolutional neural network (UNET) is trained on time series images of MDA-MB-231 breast cancer cells and their respective ground truths, according to specific color channels, so that the network can learn to segment the cell clusters. The neural network then generates masks for all images which are then used to extract information about the behaviors of the cell clusters over time. Time series graphs of area, perimeter, solidity, and eccentricity are found and show the effect of different macrophages on clusters of MDA-MB-231 cancer cells. An interesting feature was found in the graphs, at a certain time point there is a jump or dip in all the graphs due to an external permutation. The trends revealed in these graphs will be used to learn about how these clusters respond to the macrophages.   

Data Science Techniques for Systems with a Sign Problem

The sign problem stands in the way of advancing our understanding of many quantum materials, making usual numerical methods to study them impossible. This work uses machine learning and other data science techniques to compare different methods of circumventing the sign problem in many-body quantum systems. Data visualization techniques and machine learning have been useful in understanding these stochastic methods, and in identifying bottlenecks and numerical issues in the algorithms. We examine data from both Monte Carlo simulations with analytical continuation and from complex Langevin simulations in order to improve our approaches to studying systems with a sign problem.   

SEABED: A JAX-powered python package for SEquential Analysis and Bayesian Experimental Design

Parameter estimation and experimental design are two critical steps in the scientific process and to accelerate scientific discovery it is key to automate and optimize these processes as much as possible. One of the leading ways to approach these tasks is through Bayesian inference and Bayesian experimental design, but large-scale adaptation of these methods have been hindered due to a lack of compatible tools that can be adapted across scientific domains and scaled to large computational resources. To address this, we have developed SEABED (SEquential Analysis and Bayesian Experimental Design), which implements sequential Monte Carlo, or particle-filtering, methods to perform Bayesian inference and experimental design in a black-box and application-agnostic manner. Because the software leverages JAX, functions and methods are differentiable and computations can be executed and scaled across devices like CPUs, GPUs, and TPUs. Moreover, SEABED can be straightforwardly combined with other powerful libraries in the JAX ecosystem for optimization, machine learning, and physics simulations. Finally, we present two example applications to emphasize the flexibility and utility of the software package.   

Neurally-Inspired Hyperdimensional Computing for Robust and Real-time Learning

In the realm of Applied Physics Science, the contemporary challenges surrounding the efficient execution of learning tasks in computing systems are of paramount concern. Our contribution to this field presents an innovative computing paradigm, inspired by the intricacies of the human brain, designed to address these challenges. This novel computing system not only facilitates various learning and cognitive tasks but also offers a remarkable enhancement in computational efficiency and resilience when compared to existing platforms.

Our platform leverages the concept of HyperDimensional (HD) computing, an unconventional approach to computation that draws inspiration from the fundamental principles underlying brain functionality. HD computing's core objective is to achieve high-efficiency and noise-tolerant computation. It does so by emulating crucial aspects of the human memory model through vector operations. These operations are both computationally feasible and founded on a sound mathematical basis, providing an accurate description of human cognition.

One noteworthy advantage of HD computing lies in its ability to learn from data in one or only a few iterations, often referred to as one-shot or few-shot learning. This means that the system can acquire knowledge from a minimal set of examples and process the training data in a single pass, as opposed to many iterative processes. Furthermore, HD computing exhibits remarkable fault tolerance, as it operates over random hypervectors that are independently and identically distributed. This research presents a compelling avenue for addressing the intricate challenges encountered in modern computing systems, aligning with the objectives and interests of the Applied Physics Science community.   

Transferable Learning on Analog Neural Network Hardware

Analog neural network (NN) accelerators promise tremendous energy and time savings but process-induced random static fabrication errors in each individual analog chip pose a challenging obstacle to widespread analog NN deployment. Neural network models produced by standard training methods for programmable photonic interferometer circuits, a leading analog NN platform, yield poor performance on real chips that have static component fabrication errors. Moreover, existing hardware error-aware training/mitigation techniques either require individual retraining of every analog NN chip (which is impractical in an edge setting with millions of devices to be retrained worldwide), place stringent demands on component quality, or introduce hardware overhead. We solve all three problems by introducing error-aware training techniques that need to be run only once to produce robust neural network models that match the performance of ideal hardware and can be transferred exactly, without any performance loss or additional retraining, to any number of arbitrary highly faulty photonic NNs at the edge with hardware errors up to five times larger than present-day fabrication tolerances.   

Probing Dark Sectors with Gravitational Waves

One of the greatest unsolved mysteries in particle physics is the nature of dark matter. So far no indisputable direct dark matter detection has been made. It might be that the dark matter particle is part of a dark sector which is secluded or extremely weakly coupled to the visible sector, in which case conventional experiments might never detect it. As I will demonstrate, gravitational waves arising from first order phase transitions in the early Universe can be used to look for signatures of such models. Focusing on particular extensions of the Standard Model with dark U(1) and dark SU(2) gauge groups, I will show how such signatures can be searched for in upcoming gravitational wave experiments, such as LISA, SKA, PPTA, EPTA, IPTA, as well as discuss how the recent NANOGrav gravitational wave signal can be accommodated in this scenario. I will also investigate connections of those models to the existing particle physics anomalies, e.g., the neutron lifetime anomaly.   

Gravitational Wave Signatures of Low-Scale Seesaw Mechanism for Neutrinos

Neutrinos are the most elusive particles of the Standard Model. The mechanism responsible for their mass generation remains unknown and requires introducing new hypothetical particles and interactions. Usually, a very high mass scale is considered for this new physics, making it difficult to probe such scenarios in conventional particle physics experiments. Surprisingly, this high-scale seesaw framework can be tested in gravitational wave experiments by searching for a flat spectrum from the dynamics of cosmic strings, however, the signal is rather generic across many high-scale seesaw models. I will consider the possibility of having a low-scale seesaw mechanism generating neutrino masses within a framework of a model with gauged lepton number. In this case the gravitational wave signal arises from a first order phase transition in the early Universe, leading to a peak structure in the gravitational wave spectrum. The results presented are relevant for upcoming gravitational wave experiments, such as LISA, DECIGO, and Big Bang Observer. I will also discuss whether this scenario can explain the recent signal detected by the NANOGrav experiment.   

Using Gravitational Waves to Distinguish between Neutrino Seesaw Mechanisms

Neutrino masses are not explained within the Standard Model of elementary particles. One of the most elegant extensions of the theory addressing this problem is the seesaw mechanism. Its simplest version (type I) requires the existence of new heavy right-handed neutrinos. The other two scenarios involve a new scalar triplet (type II) or new triplet fermions (type III). Focusing on models with gauged lepton number, I will demonstrate how gravitational wave experiments can be used to distinguish between those three seesaw mechanism types through the first order phase transition contributions. I will also discuss cases where a flat spectrum from a high scale seesaw can coexist with a first order phase transition contribution, leading to intriguing signatures which can be searched for in gravitational wave experiments such as Big Bang Observer, DECIGO, Cosmic Explorer, Einstein Telescope, and LISA. I will also touch upon the possibility of explaining the recent NANOGrav signal within this framework.   

Nuclear resonance scattering of synchrotron radiation by K2[187OsO2(OH)4]: hyperfine interaction and lattice dynamics characterization

With nuclear forward scattering (NFS) and nuclear inelastic scattering (NIS) of synchrotron radiation on ¹⁸⁷Os nuclear, the benchmark osmium specific hyperfine interaction and thermodynamic characterization of potassium osmate, K₂[¹⁸⁷OsO₂(OH)₄], is analyzed. Nuclear forward scattering (NFS) and nuclear inelastic scattering (NIS) of synchrotron radiation by the low-lying nuclear level of ¹⁸⁷Os in K₂[¹⁸⁷OsO₂(OH)₄] was investigated. From NFS spectra the isomeric shift, and quadrupole splitting of 12.10 ± 0.05 mm/s were determined. In addition, we performed NIS spectroscopy with a 1-meV resolution and extracted the density of phonon states in the Os (VI) compound, which have been confirmed by first principle theoretical calculations. The results provide strong evidence that NFS is a reliable technique for investigation of hyperfine interactions in osmium (VI) species, and might be potentially applicable for measuring such interactions in osmium complexes of different oxidation states, including those with anticancer activity.   

Role of Dimensionality and Size in Controlling the Drag Seebeck Coefficient of Doped Silicon Nanostructures: A Fundamental Understanding

In this theoretical study, we examine the influence of dimensionality, size reduction, and heat- transport direction on the phonon-drag contribution to the Seebeck coefficient of silicon nanos- tructures. Phonon-drag contribution, which arises from the momentum transfer between out-of- equilibrium phonon populations and charge carriers, significantly enhances the thermoelectric coef- ficient. Our implementation of the phonon drag term accounts for the anisotropy of nanostructures such as thin films and nanowires through the boundary- and momentum-resolved phonon lifetime. Our approach also takes into account the spin-orbit coupling which turns out to be crucial for hole transport. We reliably quantify the phonon drag contribution at various doping levels, temperatures, and nanostructure geometries for both electrons and holes in silicon nanostructures. Our results support the recent experimental findings, showing that a part of phonon drag contribution survives in 100 nm silicon nanostructures.   

Machine Learning-Based Prediction of Optical Activity in Chiral Materials

Chiral systems span a wide range of materials from single molecules to hierarchically assembled nanoparticles and metamaterials. They possess many unique physicochemical features, including circular dichroism, circularly polarized photoluminescence, nonlinear optics, ferroelectricity, and spintronics. However, the origin of their chirality and related optical activity have not been unveiled comprehensively. In this work, we train machine learning algorithms with data sets of chiral ligand-protected metal nano clusters and chiral hybrid organic–inorganic perovskites to characterize and predict the optical activity. Our datasets encompass critical parameters such as crystal structure data, ligand properties, UV-visible absorption spectra, and circular dichroism signatures. The preliminary results reveal a strong consistency within the dataset, demonstrating a notable level of classification among the elements which promise the prediction the optical activity. Our results can facilitate the design and evaluation of chiral materials with intriguing electronic, magnetic, and optical effects.   

Applying Denoising Diffusion Probabilistic Models and Convolutional Neural Networks to Study Magnetic Fields in Molecular Clouds

Machine learning methods such as Denoising Diffusion Probabilistic Models (DDPMs) and Convolutional Neural Networks (CNNs) are powerful tools that allow us to reveal complex structures and generate predictions on large datasets. We have built such models to allow us to study the relationship between polarization and magnetic fields in molecular clouds. An overview of these models is presented in the context of their application to synthetic dust observations and real dust polarization observations. We have trained a CNN to classify polarization data based on alignment mechanism with over 98% validation accuracy. We have also trained an auto-encoder CNN to make pixel-by-pixel predictions of magnetic field strength and angle. Having a similar goal to the auto-encoder CNN, we have built DDPMs to generate images of the magnetic field strength and angle. Finally, we have applied the models to real dust emission observations in order to make predictions about the magnetic fields in actual molecular clouds. Results from the CNNs and DDPMs are presented and a comparison of the models is made.   

Relationships Between Photodegradation Reaction Rate and Structural Properties of Polymer Systems

The development of reusable polymeric materials inspires an attempt to combine renewable biomass with upcycling to form a biorenewable closed system. It has been reported that 2,5-furandicarboxylic acid (FDCA) can be recovered for recycling when incorporated as monomers into photodegradable polymeric systems. Here, we  develop a procedure to better understand the photodegradation reactions combining density functional theory (DFT)  based time-dependent excited-state molecular dynamics (TDESMD) studies with quantitative structure-activity relationships (QSAR) methodology. This procedure allows for the unveiling of hidden structural features between active orbitals that affect the rate of photodegraadtoin and is coined InfoTDESMD. Findings show that electro topological features are influential factors affecting the rate of photodegradation in the differing environments.  Additionally statistical validations and knowledge based analysis of descriptors are conducted to further understand the structural features’ influence the rate of photodegradation of polymeric materials.   

Memory-efficient incremental kernel ridge regression with a smart chunking strategy

Kernel ridge regression (KRR) is one of the oldest machine-learning techniques that has been extensively used to model complex systems in both classification and regression problems. It is a very simple algorithm and has recently gained attention in the quantum chemistry community. Despite its extensive use, KRR has memory and scalability issues that limit its full utility in handling large datasets. Several attempts have been made to improve KRR performance including the recent incremental KRR based on iterative inverse of the kernel matrix. However, memory and scalability issues persist especially for big increments. To alleviate this problem, we have developed incremental chunked Cholesky empirical KRR (ICCE-KRR), a memory-efficient incremental KRR using incremental Cholesky factorization with data chunking. With the help of data chunking, we eliminate the problem of exceeding RAM or GPU capacity, thereby making our approach ‘crash-proof’. I will be presenting our preliminary results of using this algorithm in successfully predicting electron transfer couplings in dimer systems using large datasets. We expect the success of our method to inspire more ambitious undertakings in the quantum chemistry community in the future.   

Deep learning potentials for hydration and protonation in biomolecular simulations: bond breaking is the goal and the problem

Biomolecular dynamics has long been known to be influenced by hydration shells. However, first principles calculations of hydration shell structure and dynamics, and the effects on the solvated biomolecule, have been historically out of reach due to computational costs: even the smallest simulations of fully solvated small biomolecular fragments using periodic boundary conditions can require over 500 atoms, and molecular dynamics on these systems are limited to sub-nanosecond simulation times. Using high-performance computing and highly optimized, scalable density functional theory (DFT) programs, we are now able to overcome some of these challenges to discover the effects of the hydration shell on the dynamics of biomolecular systems from a first principles perspective. These simulations still suffer from timescale restrictions, preventing the simulation of timescales relevant to most experimental validation. Recently, advances in deep neural network potentials (DNNPs) promise to extend the accuracy of first principles simulations to much larger systems and can be used to simulate hundreds of nanoseconds. Now the challenge becomes training and retraining the model to avoid incorrect behavior, especially across transition states. For solvated biomolecules, protonation state changes resulting from proton transfers are now accessible to the DNNP, while for classical empirical force fields these are generally not allowed. Unphysical transfer rates must be corrected by sampling transition state regions and teaching the model the correct energetic barriers for each proton, a difficult task. Here we discuss some of our results tackling these challenges for solvated nucleic acids, for which hydration structure plays an important role.   

Reinforcement learning-guided long-timescale simulation of defect diffusion in solids

Atomic diffusion in solids is an important process in various phenomena. However, atomistic simulations of diffusion processes are confronted with the timescale problem: the accessible simulation time is usually far shorter than that of experimental interests. In this work, we developed a long-timescale method using reinforcement learning that extends simulation capability to match the duration of experimental interest. As a testbed, we simulate hydrogen diffusion in pure metals and a medium entropy alloy, CrCoNi. The algorithm can derive hydrogen diffusivity reasonably consistent with previous experiments. The algorithm can also recover counter-intuitive H-V cooperative motion. We also demonstrate that our method can accelerate the sampling of low-energy configurations compared to the Metropolis-Hastings algorithm using hydrogen migration to copper (111) surface sites as an example.   

Deep Learning Functionals based on the Adiabatic Connection

Density functional theory (DFT) is vital for advancing our understanding of molecular and material properties, offering a unique balance between predictive power, versatility, and computational efficiency, despite its challenges in accurately describing strongly correlated systems. The adiabatic connection (AC) formalism offers a unique advantage in density functional approximations (DFAs) construction by allowing for direct and explicit consideration of strong correlation effects, enabling the development of interpolation models that depend on both strongly interacting and non-interacting limits of the AC, providing a more accurate estimation of exchange-correlation energies [1,2]. Our method combines the rigorous principles of the density-fixed AC with the power of deep learning, offering a transformative solution for improved accuracy and efficiency in DFT calculations. By leveraging deep learning techniques in the local interpolation along the AC, we have developed models ensuring size consistency and the accurate capture of strong correlation effects. The results of extensive testing on representative chemical systems are presented, showcasing significant advancements over state-of-the-art DFT.

References

[1] S. Vuckovic, T. J. P. Irons, A. Savin, A. M. Teale, P. Gori-Giorgi, J. Chem. Theory Comput. 2016, 12, 2598–2610.

[2] S. Vuckovic, T. J. P. Irons, L. O. Wagner, A. M. Teale, P. Gori-Giorgi, Phys. Chem. Chem. Phys. 2017, 19, 6169–6183.   

Escape and Retract over Universes

This paper proposes firstly the T-duality Courant algebroid theory, which provides a strong tool for deeply description on the escape and retract phenomenon over many universes. It is known that standard Courant algebraic structure TM+T*M combines complex and symplectic geometry. This new T-duality Courant algebraic theory generalizes and extends the Courant algebroid to the T-duality complex Courant algebraic structure as the TM- T*M, which has an important mirror symmetry : R-> 1/R more precise, U^2 - W^2 = t, which has two topological representations U(1-U)= 1 and U(1-U) = -1. First solution is complex form : U=1/2 +- I*sqrt(3) /2, which is a circle S1 or a torus structure describing motions between two-bodies or universes. Second solution is a pair of golden ration phi= sqrt(5)/2 + 1/2=1.618; phi-1 = 0.618 or phi(phi-1) = 1= Id. It shows that from the escaping point sqrt(5)/2 has two objects: 0.618 and 1.618, which have same probability i.e. 0.5. It means that escape and retract of universes and fundamental particles indeed are a T-duality manifolds. we see the escape mutation orbifolds pass a vacuum line bundle where mass=0, which implies that the escape and retract move behaviour arise by limit light speed 4 rather than our measurements 3x... km/s. It is clear that m=0 and limit light speed are two necessary conditions. This important discovery opens a door of research about the Black-Hole and original source. I assert that all universes are without Origen, also without end point, which are without any birth or a death. The T-duality complex Courant algebraic geometry splits a circle S1 or torus into an elliptic manifold with centre distance d= sqrt(5), which is greater than radius 2 of Universe, then induces escape performance. It is completely different from standard Courant algebraic geometry TM+T*M. The new T-duality theory will be proved it is a robust tool for studying mani-body problems. The Black-Hole is an escaped universe again returning by retract deformation rather than other.   

Anansi: Progress Towards Developing a Highly Extensible High Performance Computing Molecular Dynamics Code Based on Generic Design Patterns

Many High Performance Computing (HPC) molecular dynamics (MD) codes (e.g. LAMMPS, NAMD, GROMACS, etc. ) have origins that are well before the extant programming languages and current Graphics Processing Unit (GPU) architectures. Furthermore, programming languages and computer architectures have substantially changed since these origins and will unabatedly continue to change. Unfortunately, these factors contribute to extreme difficulties in extending HPC MD codes to novel algorithms and computer architectures. The goal of Anansi is to develop a highly extendable MD code that can rapidly adapt to novel algorithms and evolving computer architectures. In this ongoing work, we present Anansi’s software design which makes extensive use of generic software design patterns. Specifically, we present a generic command pattern for limiting function side effects, and the use of the type erasure idiom for replacing traditional inheritance hierarchies. A secondary goal of this work is to serve as a best practice guide for motivating others in designing molecular simulation codes.   

Exact double counting correction schemes from the flat plane condition

Since the inception of quantum embedding methods such as DFT+U and DMFT, numerous double counting correction schemes have been devised including the around mean field and fully localised limit schemes. However, these double counting correction schemes typically lack strong theoretical underpinnings and it is found that the predictive accuracy of DFT+U and DMFT methods depend strongly on the choice of double counting scheme.

We present our recent theoretical developments on the tilted plane condition [1], a generalisation of the well-known flat plane condition, which characterises the total energy curve, E[N,M], of a finite electronic system for all values of electron count N and magnetisation M. Using the tilted plane condition, we reverse engineer an exact double counting correction scheme for DFT+U [2], which may prove useful also in DMFT and DMET methods.

In the case of correlated d-orbital subspaces we furthermore reveal that the structure of the E[N,M] landscape depends strongly on the chemical coordination between the active subspace and its environment, so that for example a unique double counting correction scheme is required for octahedral, tetrahedral and square-planar coordinations. We thus show that our exact double counting correction scheme is necessarily dependent on the symmetry imposed degeneracies of the active subspace.   

Carbon Sequestration Reaction Using Magnesium Silicate – A Quantum Molecular Dynamics Study

With rising greenhouse gas emissions, sustainable energy technologies have become crucial now more than ever. Carbon dioxide being the most important of all greenhouse gases. It was proposed by Seifritz in 1990 [1] that carbon dioxide could be sequestered by silicate minerals resulting in the formation of carbonates. In this study, using quantum molecular dynamics, we show the dynamics of MgCO₃ formation by reaction of hydrated carbon dioxide (H₂CO₃) with MgSiO₃. In addition to the carbonate of magnesium the reaction also produces water and the formation of Si-O-Si bonds. With the available technology today, it is feasible to dig up large quantities of Silicates from the Earth’s surface making this a very efficient method of carbon sequestration.

 

[1]      W Seifritz, CO₂  Disposal by Means of Silicates, Nature 345, 486 (1990).   

Pressure Control of ZrS2 Oxidation dynamics: A Molecular Dynamics Study

Understanding oxidation mechanisms of layered semiconducting transition-metal dichalcogenide (TMDC) plays an important role in controlling the formation of native oxide as well as in synthesis of oxide and oxysulfide products. Here, we perform reactive molecular dynamics simulations with optimized reactive force field and show the influence of oxygen partial pressure on not only the ZrS₂ oxidation rate but also the oxide morphology and quality. As the oxidation progresses, we observe a transition from an oxidation process occurring layer-by-layer to a continuous oxidation mediated by amorphous oxide. We present that different pressure levels selectively reveal distinct oxidation stages within a specific simulation time frame. The conventional Deal-Grove model describes the kinetics of the fast continuous oxidation stage well, while reactive bond-switching mechanisms governs the layer-by-layer oxidation stage. This research provides atomistic insights for the oxidation mechanisms of ZrS₂ and offers a potential foundation for controlled oxidation of a wide range of TMDC materials through the manipulation of pressure.   

Analytical simulations of the resonant transmission of electrons in a closed nanocircuit for terahertz applications where a tunneling junction is shunted by a metallic nanowire

In the CINT program at Los Alamos we focused ultrafast mode-locked lasers on the tip-sample junction of a scanning tunneling microscope to generate currents at hundreds of harmonics of the laser pulse repetition frequency. Each harmonic had a signal-to-noise ratio of 20 dB and a 10-dB linewidth of 3 Hz. Now we model closed quantum nanocircuits with rectangular, triangular, or delta-function barriers shunted by a beryllium filament for quasi-coherent electron transport over mean-free paths as great as 68 nm. The time-independent Schrödinger equation is solved with the boundary conditions that the wavefunction and its derivative are continuous at both connections. These boundary conditions form a four-by-four complex matrix equation with a column of zeros on the right-hand side because of the closed circuit. The dimensions are chosen such that the determinant is zero for a non-trivial solution. Each model has four parameters: (1) barrier length, (2) height and shape of the barrier, (3) length of the pre-barrier, and (4) the electron energy. Any three are specified and the fourth is varied to bring the determinant to zero on lines or surfaces in the space that is defined by the four parameters. This may provide a compact device to extend our earlier work at CINT.     

Half-metallic porphyrin-based molecular junctions for spintronic applications

Molecular spintronics, have become promising paradigms to develop nanoscale electronic circuits such as high-density information and quantum computing. The efficiency and characteristics of molecular spintronics are determined by the intrinsic nature of the molecular magnets placed in the transport pathway. Among the studied molecular magnets, metal porphyrins (MPors where M is a transition metal) as a building block of future molecular spintronics. In this work, computationally we screen the spin-conductance properties of 3d and 4d MPors using the nonequilibrium Green's function formalism. Our results show that MPor-based molecular junctions according to spintronic conductance behavior can be categorized into three groups: type I non-spin-polarized, type II′ minor spin-polarized current, and typeII′′ major spin-polarized current devices. Type-II′ and type-II′′ molecular systems show perfect spin filtering and spin-dependent negative differential resistance. The optimal energy alignment of spin-polarized molecular orbitals with gold electrodes results in one-channel spin transport (minor for type II′ and major for type II′′). The type-II′′ junctions also show a voltage-induced spin switchability at low bias voltages. In this regard, type-II molecular systems are promising candidates for a low-power consumption spin filter, spin switch, and memory. Our results highlight the practical applications of metalloporphyrin for the development of multipurpose miniature spintronics.   

Theoretical Study of Thermal Stability of α″–Fe16N2 Against Other Iron Nitrides

α″–Fe₁₆N₂ has been investigated as one of promising candidates for environment friendly magnets.[1] While giant saturation magnetization has previously been experimentally observed in α″–Fe₁₆N₂, its magnetic anisotropy and structural stability leave room for improvement. Recent theoretical studies have considered alloying Fe₁₆N₂with various elements to improve the magnetic properties and/or stability against decomposition.[2] However, estimates of stability in particular are typically restricted to simple ground-state-energy comparisons, i.e. effectively taken near 0 K.

For a more practical measure of stability, we therefore extend ground-state energies, obtained with the plane-wave density-functional theory (DFT) code Quantum ESPRESSO, with appropriate empirical and/or statistical corrections to obtain free energies at arbitrary temperature. We then compare the stability of Fe₁₆N₂ against the neighboring phases in the Fe-N binary system, to estimate the range of temperatures at which it is stable. We compare against experimental observations of the Fe–N phase diagram.[3]

[1] J.-P. Wang, J. Magn. and Magn. Mat. 497, 165962 (2020).

[2] P. Stoeckl, P. W. Swatek, & J.-P. Wang, AIP Advances 11(1), 015039 (2021).

[3] Cf. e.g. M. Hillert & M. Jarl, Metall. Transac. A 6A 553–9 (1975).   

A machine learning strategy for the physics-informed design of nanomaterials using ChIMES

Nanoparticles have an intrinsic ability to self-assemble into materials crucial to various industries spanning catalysis, drug delivery, optics, and environmental remediation. Simulation is a critical tool for exploring and designing new self-assembling nanomaterials, yet developing suitable models can be cumbersome due to the need for a balance of computational efficiency (i.e., to enable many-particle simulations) and accuracy. In this presentation, we explore the application of ChIMES, a generalized many-body machine-learned interatomic model (ML-IAM) and artificial intelligence-driven parameterization capability, to the modeling of nanoparticle systems. We note that ChIMES was originally developed and optimized for modeling condensed phase reacting systems at atomistic resolution. Here, we apply it to the development of models coarse-grained at the resolution of individual nanoparticles, which should, in principle, overcome limitations of commonly applied molecular mechanics functional forms, opening the door to modeling more complex nanoparticle systems (e.g., for which greater-than-2-body interactions cannot be neglected). We explore model sensitivity with respect to the choice of hyperparameters and discuss findings within the context of previously established “best practices” for atomistically-resolved ChIMES models.    

Optical Conductivity in Deformed Flat-Band α-T3 Materials with Finite Band Gaps

We have derived closed-form analytical expressions for the optical conductivity of various types of α-T₃ materials with finite band gaps in their energy dispersion, at both zero and finite temperatures, and with near-zero or nonzero doping. In contrast to the α-T₃ lattice with a flat middle band, gapped α-T₃ materials exhibit several intriguing physical characteristics, including a curved middle band that may be partially or fully doped. The infinite degeneracy of the non-deformed flat band is completely lifted by the curvature, permitting various Fermi energy values within the band. As the flat band transitions into a curved one, two additional branch dispersion relations become nonlinear. This unique band structure emerges when an α-T₃ material is irradiated by an off-resonant, circularly polarized dressing field, interacting with the Dirac electrons. The optical conductivity of gapped α-T₃ materials exhibits all the known features of those with zero gaps, as well as those of silicene with two inequivalent band gaps. This distinguishes them from graphene, where zero-temperature conductivity in the frequency range ω < 2μ is zero, due to Pauli blocking that prevents carrier transfer between two occupied states. We demonstrate an additional Drude peak in the optical conductivity, arising from intraband transitions, which occurs in addition to the two successive steps, resulting from transitions between the valence and middle flat bands, and the valence and conduction bands observed in ungapped α-T₃ materials. These unique properties of the optical conductivity, along with its frequency dependence, hold promise for various device applications, including photodetectors, optical modulators, and metasurfaces.   

Exploring the Crystal-to-Amorphous Transition in NiTi Using Metadynamics

NiTi is an intriguing intermetallic due to its diverse range of phases and their impact on mechanical properties. In addition to the B2 to B19' phase transition, which is responsible for superelasticity, NiTi is susceptible to a crystal-to-amorphous phase transition due to the presence of larger atoms, such as Nb, or heavy deformation. This transition has been attributed to anti-site defects. Understanding the crystal-to-amorphous transition is important, as most applications of NiTi are based on its crystal structure. The present work attempts to elucidate this transition at the atomistic level using metadynamics simulations.   

Characterization of structural, dynamic, optoelectronic, thermodynamic, mechanical and thermoelectric properties of AMgF3 (A = K or Ag) fluoro-perovskites compounds

Born effective charges Z_{(i),β α}^*, dielectric tensors ε_α,β and the dynamic stability for AgMgF₃ and KMgF₃ compounds were treated based on the harmonic and quasi-harmonic theory implemented in phonopy code. The band gap for both compounds, and the effective masses of electrons and holes are calculated at different pressures using the TB-mBJ (GGA) approximation within the framework of the density functional theory. Furthermore, absorption coefficient, refractive index, extinction coefficient, reflectivity, and optical conductivity, for both compounds, were calculated. On the other hand, we studied the nature of atomic bonds by the topological distribution of the charge density as well as computing the effective charge of each atom based on the Quantum Theory of Atoms in Molecules (QTAIM) as implemented in Bader code, therefore the ionic type for bonds was explored. The mechanical stability was verified the elastic behavior at the equilibrium ground-state for both compounds. Thermal properties such as heat capacity at constant volume, entropy, Debye temperature, and thermal expansion coefficient are treated depending on the quasi-harmonic model. They are examined under both pressure and temperature influences. The thermoelectric properties of the compound AgMgF₃ showed a high figure of merit (ZT) reached 0.75 at a temperature of 300 K in the case if it was grafted with a concentration of 10²¹ cm⁻³ of n-type.   

High-Throughput Screening of (100) Metallic Surfaces for Thiophene Hydrodesulfurization

We use density functional theory with self-consistent van der Waal interactions to explore thiophene (C4H4S) absorption over 1200 different single metal and bimetallic surfaces. We employ the BEEF-vdW functional. Based on previous studies, the highest binding energy for thiophene over (100) metal surfaces is a parallel absorption configuration when the molecule is centered over a hollow site with the sulfur atom near an atop site. We report, for now, the adsorption properties, including the adsorption height, adsorption energy, and charge transfer to the S atom, of thiophene in this configuration. We map two of these chemical descriptors, namely adsorption energy and charge transfer to the S atom, to the ability of the sulfurized-version of the metal to desulfurize thiophene, and, based on these results, suggest several interesting candidates for thiophene desulfurization.   

Application of first-principles determination of magnetic structures using magnetic interactions

For systematic prediction of magnetic structures, the ab-initio calculation based on spin-density functional theory is a powerful method. Here, we employ the formulation using the magnetic force theorem based on Wannier-orbital tight-binding model, which evaluates magnetic interactions between spin magnetic moments by assuming a magnetic structure. This formulation does not assure the consistency between the assumed magnetic structure and the resulting magnetic interactions [1]. Therefore, we can determine the ground-state magnetic structures and propagation vectors by calculating magnetic interactions with the assumption of virtual ferromagnetic structure and exploring energy minimum in classical Heisenberg model.

In this presentation, we validate this method with two results. First, we demonstrate the determination of the propagation vectors by calculating eigenvalues of magnetic interactions in reciprocal space. The obtained propagation vectors are consistent with fully ab-initio calculations or neutron diffraction experiments. Second, we show that the obtained ground-state magnetic structures reproduce experimental observations. We apply this method to 44 magnets on experimental database MAGNDATA and get accurate results for 90% of them. This precision is on par with the previous study [2], indicating high potential of this method for predicting magnetic structures.

[1] Nomoto et al., PRL 125, 117204 (2020).

[2] Huebsch et al., PRX 11, 011031 (2021).   

Ab initio Electrical Conductivity Calculations of Ag-Pd Alloy based on Wannier-CPA Method

 In material design, it is important to predict the properties of mixed crystals by continuously changing their compositions. For this purpose, coherent potential approximation (CPA) is a powerful tool. However, due to its formulation, DFT-based CPA has been implemented only in specific electronic-structure-calculation packages, such as those based on the KKR or TB-LMTO methods.

Recently, Wannier-function based CPA (Wannier-CPA) [1] has been developed, which is computationally efficient and can be easily combined with any DFT packages. It was confirmed that this method well reproduces magnetic properties of Fe-based transition metal alloys obtained by KKR-CPA. To apply this method for transport properties, we develop a code to calculate the electrical conductivity of substitutional alloys based on Wannier-CPA. For the analytic continuation of the response function, two numerical analytic continuation methods are employed [2]. We find that the results well reproduce previous experimental and theoretical studies [3,4].

 

[1] N. Ito et al., Phys. Rev. B 105, 125136 (2022).

[2] K. Nogaki and H. Shinaoka, J. Phys. Soc. Jpn. 92, 035001 (2023).

[3] A. M. Guenhault, Phil. Mag. 30, 641, (1974).

[4] P. R. Tulip et al., Phys. Rev. B 77, 165116 (2008).   

Drift Velocity with Elastic Scattering

The drift velocity of a particle under a driving force has its roots in the theory of electrical conduction. Although being studied for over 100 years, it still yields surprises. At the heart of a particle's drift velocity is an interplay of classical, quantum, and statistical mechanics. Irreversibility and energy loss has been assumed as an essential feature of drift velocities and very little effort has been made to isolate the aspects of particle transport that are due to elastic mechanisms alone. In this paper, we remove energy loss and quantum mechanics to investigate the classical and statistical factors which can produce a drift velocity using only elastic scattering. A Monte-Carlo simulation is used to model a particle in a uniform force field, subject to randomly placed scatterers. Time-, space-, and energy-dependent scattering models, with varied ranges of scattering angles are investigated. A constant drift velocity is achieved with the time scattering model, which has a constant average time between scattering events. A decreasing drift velocity is observed for space and energy dependent models. The arrival of a constant drift velocity has to do with a balance of momentum gained between collisions and momentum lost after a collision.   

Study of Hubbard model on triangular lattices using linearlyscaling semi-classical methods

While several computational techniques, such as Quantum MonteCarlo (QMC), have achieved remarkable success in investigatingstrongly correlated lattice models, they often face challenges inobtaining reliable results for systems with itinerant electrons,geometric frustration, or realistic electronic interactions like spin-orbitcoupling. Semiclassical methods have been extensively employed tostudy such systems and have proven to be qualitatively and oftenquantitatively accurate, especially for weakly correlated materials.Previous studies have demonstrated the effectiveness of combiningsemi-classical methods and Monte Carlo methods in the Hubbardmodel on square and cubic lattices, accurately predicting the Neeltemperature and aligning with results from Determinant QuantumMonte Carlo (DQMC) calculations. This study aims to assess the efficiency and accuracy of semi-classical methods in frustrated systems, specifically the Hubbardmodel on a triangular lattice. We utilize the Kernel Polynomial Method(KPM) for efficient Monte Carlo sampling of the auxiliary fieldsintroduced during the Hubbard-Stratonovich transformation of theinteraction terms. The KPM approach allows us to bypass thecomputationally expensive matrix diagonalization, resulting in acomputational cost that scales linearly with the system size. Thisscalability enables us to explore large system sizes, providingvaluable insights into the behavior of frustrated systems.   

The symmetric difference algebroid and escape - shrink back of the Black-Hole

This paper presents the symmetric difference algebroid theory, with which we give exact analytical solutions on escape retract mutation deformation of the Black-Hole.

The classical Courant algebroid associates with the direct sume of tangent and cotangent vector bundle : TM = TM+T^*M. The symmetric difference algebroid T^sd as a T-duality structure of the courant algebroid associates the direct difference form: T^sd = TM - T^*M. Even so the TM algebroid and the T^sd algebroid are an isomorphism, but have deep different mathematical physical means. For example, in a complex torus or circle S¹, two algebroids have completely different geometric realizations as:

TM= 2n ± √3 + 1/(2n ± √3);  T^sd= 2n ± √5 - 1/(2n ± √5). There exists an important relationship: TM(n=1) = 2±√3 + 1/(2±√3) = 4; T^sd(n=1) = 2± √5 - 1/ (2±√5) = 4, i.e. in first period: 

TM= T^sdM = 4. We assert that this is just maximal light speed v_max = 4 rather than c= 3x... km/s. This light speed c only is a transitional speed measured in the earth, which is not the speed at original head (the Sun). This important discovery on the limit light speed will rewrite the relation between mass and velocity of the universe and fundamental particles. the new formula of mass transformation is m = √(1 - v/4) including the case of Tachyon particles. It clearly is that for velocity : v= 4(1 - m²). Then Gmv = 4Gm(1-m²) = Id =1. For the freedom fundamental group, we found there exists a monodromy dimensionless gravitational constant G = 2/3 = 0.666666.....

The symmetric difference algebroid exactly describes the extremel escape retract deformations over the universes. The escape- retract radius are √5 ∼ 1/√5, extremel escape-retract  angle: θ₁=atan(√5)= 65.9^o > 60^o;  θ₂= atan(1/√5) = 24.1^o < 30^o. We asserts that if argument angle is over the stable angle 60^o or mass is over the critical mass √3/2, sub-system is possible to escape from the universe.. At a freedom escape point r_coh= √5/2 = 1.1180 > r=1, there exist two escape directions: √5/2 + 1/2 = 1.6180; √5/2 - 1/2 =0.6180, or φ = 1.6180, φ-1 =0.6180, φ(φ-1) = 1, φ²= 1 + φ, or the escape equation: φ² - φ -1 = 0, its two roots are 1/2 ± √5/2. The Black Hole is a typical escape-retract phenomena, which also is vanishing cycle mutation. We can compute the mass of a BH: m_BH = √(1- (√5)²/4) = √(-1/4) = i/2, it is complex mass as Tachyon. New stars are just retracted BHs. The BH has not earth or death.   

A Structure-Preserving Approach to Maxwell-Vlasov

Geometric integrators preserve aspects of the exact solutions to differential equations. Symplectic integrators, which have discrete flow maps that conserve a canonical 2-form, may be among the most familiar because of their use in classical mechanics; however, numerical methods that follow this general approach have been applied to a variety of equations, including those that describe fluid mechanics and electromagnetism. Suggestively, the Lagrangian which gives rise to the Maxwell-Vlasov equations contains terms that may be naturally interpreted as fluid, electromagnetic, or interaction energies. This decomposition motivates us to construct a type of splitting method for Maxwell-Vlasov, taking advantage of the structures built into its component parts. On the fluid side, we interpret the configuration space as a generalized Lie group, which falls into the framework of Euler-Poincaré reduction. On the electromagnetic side, we view the relationships among the potentials and fields in terms of the de Rham complex. With the goal of a structure-preserving numerical method for plasma dynamics in mind, we write the reduced Maxwell-Vlasov equations in a weak, variational form, then use the approximation spaces suggested by the structures of the Lagrangian's component parts to obtain a semi-discrete form of the equations. We then consider different ways to perform the time discretization and indicate potential refinements to the method.   

Magnetic Reconnection on a Klein Bottle

Magnetic reconnection is a process in plasma physics where magnetic field lines from different regions come together, reconfigure, and release stored magnetic energy. The phenomena is thought to explain solar flares, geomagnetic storms, coronal mass ejections, astrophysical jets, magnetotail dynamics, and more. Currently, computational simulations of magnetic reconnection involving the PIC (particle in cell) method use boundary conditions that come with certain drawbacks. One popular method based on a famous test problem includes hard walls at the top and bottom edges that unnaturally limit the time that the simulation can be run. Another common option with fully periodic boundary conditions effectively requires doubling the size of the simulation domain, hence increasing its computational cost. We investigate a novel periodic boundary condition that topologically maps from a 2-dimensional rectangular sheet to a Klein bottle, or from a 3-D rectangular prism to a 3-D manifold analogous to a higher-dimensional Klein Bottle. We show that these boundary conditions conserve energy and preserve the important properties of magnetic reconnection. Furthermore, these boundary conditions do not involve unnatural hard boundaries and decrease the computational power compared to the double sheet while maintaining the desired periodicity.   

Using Bayesian Machine Learning to Extend the Range of Ab Initio Many-Body Calculations of Infinite Matter Systems

Many-body perturbation theory and coupled cluster theory provide many-body perspectives for studying infinite matter systems (homogeneous electron gas and infinite nuclear matter). However, these calculations can suffer from long computational times due to the complexity of the many-body problem, thus hindering large-scale studies. This work presents several novel algorithms based on Bayesian machine learning, which can drastically decrease the computational time needed to perform these calculations by making accurate predictions of the correlation energies of the system. This work includes predicting the converged (with respect to basis size) correlation energy of an infinite matter system using only calculation at small basis sizes and predicting the correlation energies at all densities in a relevant range using only a few fully converged data points in the region. The accuracy of the predictions and the time saved over performing traditional calculations will be presented as a motivation for using these novel Bayesian algorithms.   

Electron Tunneling in Double Quantum Dot-Quantum Well Complex: Quantum Sensor Simulation

The electron localization of confinement states in double quantum dots (DQDs) is described by the two-level system theory [1]. The spectral distribution of electron localization in DQDs depends on the medium, external fields, geometry, and material mixing and can be used in a quantum sensor. We propose a sensor that combines double quantum dots with molecules of an analyte. By detecting the spectral distribution of electron tunneling in DQDs, we can identify the analyte spectrum and determine the composition of the analyte by comparing it to a reference sample. To investigate electron tunneling in such a complex system, we conducted three-dimensional (3D) computational modeling using the effective potential approach for InAs/GaAs heterostructures. The analyte spectrum was simulated by employing a quantum well with a quasi-discrete spectrum. The calculations demonstrate the significant potential of using this complex as a sensor.   

Development of solid-state quantum diamond microscope in high-pressure, high-temperature environments

In geoscience, researchers study minerals in the Earth's interior that are extremely high in pressure and temperature. The mainstream technique for mimicking such conditions combines a diamond anvil cell (DAC) with a resistive or laser heater. However, to date, no method allows imaging the magnetic field of the inside of a high-temperature DAC with nanometer-scale spatial resolution. The diamond's nitrogen-vacancy (NV) center is a promising quantum sensor to satisfy this need. Recently, researchers demonstrated magnetic and pressure imaging inside the DAC with micrometer-scale resolution by creating a thin layer of NV centers near the surface of a diamond anvil. Here, we present our recent progress on NV-based imaging under high-pressure and high-temperature conditions using an NV-implanted DAC combined with a resistive heater made of a platinum thin wire. Our new sensor device may provide valuable information about the material properties of the Earth's environment.   

An investigation of the structural modifications and structural stability of irradiated Nd2Zr2O7 pyrochlore by synchrotron X-ray techniques

Ordering and disordering mechanism has a substantial effect on the physicochemical properties of complex oxides when they are exposed to harsh conditions like high pressure or ion irradiation. In this work, swift heavy ion (100 MeV I⁷⁺) irradiation-induced pyrochlore to defect fluorite phase transformation with amorphous fraction in Nd₂Zr₂O₇ has been investigated. XRD results indicate that the Nd₂Zr₂O₇ is transformed to a defect fluorite phase with an amorphous fraction on irradiation at the highest fluence of 5×10¹³ ions/cm². By examining the XANES and EXAFS spectra of irradiated materials, it was possible to analyze how the local coordination environment around the absorbing atoms changed at various fluences. The change in the intensities of main edge features and shifting in the energy position of Zr K-edge XANES spectra with ion fluences are also good indicators of the phase transition from pyrochlore to defect fluorite structure, which is supported by the FT modulus of Zr K-edge and Nd L₃ - edge. In-situ thermal annealing investigation was performed in the temperature range of 300 to 1000 ᵒC on pristine and irradiated Nd₂Zr₂O₇ pyrochlore at 5×10¹³ ions/cm² using synchrotron x-ray diffraction. The behavior of isochronal annealing is described in terms of improved defect recovery, which demonstrates that pyrochlore superstructure does not appear even at a high temperature of 1000 ^ᵒC.   

Palm-Top, High Power, Sub-Nanosecond Laser Source for Multi-Platform Spectroscopy and Laser Remote Sensing Optimization

A major difficulty with deploying solid-state laser transmitters on space flight instruments is their overall size and mass, where footprint and cost of deployment are at a premium. Any advancement in miniaturization, or improving the Energy/kg or Energy/cm^2 helps diffuse that issue. We have taken recent advancements of additive 3D printing technologies by creating opto-mechanics, and other photonic parts to create a new step in advancement. A custom pentagonal-shaped Neodymium: Yttrium Ortho-Vanadate gain crystal, (Nd: YVO4) to produce a new diode-pumped gain medium design for high peak power laser pulses in a very small package. The creation of a sub-nanosecond solid-state laser transmitter that is small enough to fit in your hand while producing optimum power outputs has been demonstrated. Optimization of the diode pump was made by testing varying collimators, focal lenses, and other optical devices to optimize the custom gain crystal that would be used. The research was done applying techniques learned when developing NASA's Dragonfly Mass Spectrometer (DraMS) laser. This research reached success, achieving all goals, reaching high peak power lasers, and sustained Q-switch operations. The reduction in size, while maintaining peak performance allows easy applications for use with planetary exploration and remote sensing.   

Nanosecond light-matter interaction with structured targets in ablation regime

Nanosecond laser ablation and plasma generation exhibit rich physics, which finds applications in diverse areas of science and technology. Prior works have focused on controlling laser ablation through shaping laser pulses and via materials selection. Here, we examine the effects of target structure on laser ablation efficiency and plasma formation. We experimentally investigate laser ablation of ultrathin film layered targets using nanosecond (5-20 ns) laser pulses with energies up to 0.7J. With time-resolved plasma plume imaging we study the way thin films influence plasma plume shape evolution. Ultrafast plasma spectroscopy and mass loss measurements allow us to measure plasma temperature and ablation efficiency. We compare our study of layered thin films with bulk materials and underline key differences in ablation dynamics. Our work on controlling laser ablation may find use in such areas as pulsed laser deposition (PLD), plasma based light sources, and micromachining.   

Bridging macroscopic and microscopic nonlinear optics with layered semiconductors

Nonlinear frequency conversion provides essential tools for light generation, photon entanglement, and manipulation. Conventional nonlinear optical crystals display moderate second-order nonlinear susceptibilities and perform well in benchtop setups with discrete optical components. However, such crystals do not easily lend themselves to miniaturization and on-chip integration. Transition metal dichalcogenides (TMDs) possess 10-100x stronger nonlinear susceptibilities and, thanks to their deeply sub-wavelength thickness, offer a unique platform for on-chip nonlinear frequency conversion and light amplification. Recently, such giant nonlinearity has been exploited to demonstrate nonlinear light amplification at the ultimate thickness limit[1]; however, optical gain was still limited by the sub-nm propagation length.

3R-stacked TMDs naturally combine broken inversion symmetry (|χ⁽²⁾| ≠ 0) and aligned layering, representing ideal candidates to boost the nonlinear optical gain with minimal footprint. The nonlinear optical response of 3R-MoS₂ has been explored in some recent pioneering studies[2,3], so far focusing on thinner crystals, reporting the quadratic enhancement with the layer number at the 2D limit. Pushing towards general application, however, requires higher nonlinear enhancements and thus larger layer number, which in turn leads to more intricate interferences and interactions within the crystal.

Here we measure SHG from multilayer 3R-MoS₂. We report the first measurement of the coherence length at telecom wavelengths (~ 530 nm). At such thicknesses, we achieve record nonlinear optical enhancement, i.e., >10⁴ stronger than a monolayer, revealing the intrinsic single-pass upper limits of the material[4]. Further enhancement can then be achieved by engineering larger crystals or waveguides, or by exploiting birefringence.

Our results highlight the potential of 3R-stacked TMDs for integrated photonics, providing critical parameters for designing highly efficient on-chip nonlinear optical devices.

[1] Trovatello, C. et al. Nat. Photonics, 15, 6-10 (2021)

[2] Shi, J. et al., Adv. Mater. 29, 1701486 (2017)

[3] Zhao, M. et al., Light: Sci. Appl. 5, e16131 (2016)

[4] Xu, X., Trovatello, C. et al., Nature Photonics, 16, 698-706 (2022)   

Exploring acoustic strain soliton behavior in materials through numerical simulations and Sagnac interferometry

Ultrafast laser pulses can be used to generate ultrafast acoustic strain pulses that propagate through materials and are detectable using picosecond ultrasonic techniques. With sufficient pulse energy, and due to the nonlinear elastic propagation within a material, strain textures can have solitary features known as solitons, which travel at supersonic speeds without dispersion, in contrast to lower pulse intensity experiments which propagate conventionally according to linear elasticity.

 

We will discuss numerical simulations of solitons generated from the Korteweg-de Vries equation, using a hypothetical opaque negative thermal expansion (NTE) transducer, as may be realized using films of SmYS or ReO₃. This study reveals that the NTE case yields a soliton train with significantly higher spatial frequencies compared to the conventional positive thermal expansion (PTE) transducers.

 

We will also present progress on the development of an apparatus based on a zero-area Sagnac interferometer that uses an ultrafast laser pulse to generate acoustic strain solitons in materials and detects them after macroscopic propagation. Our approach allows for the generation of multiple strain soliton pulses traveling and interacting within a sample, potentially enabling nanoscale sound-sound interactions to be realized in bulk materials.   

Parametric Evaluation of Femtosecond Laser Ablation Utilizing Molecular Dynamics Simulations

While laser ablation using a nanosecond laser is well understood, there remain gaps in our understanding of the ablation process associated with a femtosecond laser. This is a result of the short time scales associated with a femtosecond laser. Here, using molecular dynamics (MD) simulations, we aim to perform a parametric study to understand the physical process associated with femtosecond laser ablation and the consequent shock wave in the surrounding media. Results from the simulations will be compared to various experimental results and analytical models of the ablation process and shockwave propagation. Finally, the physical process associated with the femtosecond laser ablation will be compared to that of a nanosecond laser.   

Poster: Ultrafast Carrier Dynamics at Carrier Densities above Mott Density: Monolayer vs Multilayer MoS2

Molybdenum Disulfide (MoS₂) is an intriguing material with several applications in optoelectronics, spintronics, and valleytronics. Scientific community continues to comprehend its carrier dynamics at different excitation conditions. However, its behavior at excitation densities exceeding Mott density (MD) is not well explored. In this work, we investigate the carrier dynamics of monolayer and multilayer MoS₂ at above MD. We show that despite the similarity in band structure around the K-point and the formation of A-exciton, there is a substantial difference in the dynamics of carriers reflecting the influence of the full band structures. In multilayer, excited carriers live for a longer time in an excited state and shows a saturation in signal, while in monolayer form, it shows quicker relaxation and linear behavior. This result is important for applications of MoS₂ requiring high excitation densities MoS₂ in high power detectors, lasers, and OPA.   

Following Phonon Dynamics in Solids Using High-Harmonic Spectroscopy

Ever since the first observation of high-order harmonic generation (HHG) from zinc-oxide [1], the field of HHG from solids has seen tremendous growth with many reports of HHG from a variety of materials as well as their applications in spectroscopy or potential industrial market [2-5]. HHG from solids has quickly formed a significant sub-field of attosecond science. In this work, we demonstrate the substantial power of high harmonic spectroscopy of solids in investigating carrier-phonon scattering in solids. Utilizing the non-collinear two-color interferometric measurements, we obtain unambiguous ultra-high-order wave mixing in solids, extending from the gas phase experiments [6]. Furthermore, by exercising control over the pump and probe laser pulses as well as their delay and polarization, we can initiate, control, and follow the phonon dynamics in real time with unprecedented capabilities. The experimental results are fully supported by theoretical simulations using different methodologies (two-level model including phenomenological phonon coupling, semi-conductor band model including carrier-phonon interaction). Being coupled with theoretical simulations, our experimental results would help in characterizing the carrier-phonon coupling strength, phonon creation and relaxation, and multiple-phonon dynamics in a solid system. We anticipate our work would help reveal carrier-phonon scattering in a brand-new dimension, extracting in-depth information.   

Ultrafast quantum decoherence in semiconductor

In systems interacting with their environment, applying quantum theory solely to the systems yields different results than when the environment is included. Decoherence, the seemingly inability of a system to maintain its quantumness, is a ubiquitous phenomenon and relies on environmental inclusion for thorough analysis. Although micro spin systems have been extensively investigated, dephasing in real macro systems remains largely unexplored due to its rapid occurrence. Here, we present a near sub-femtosecond decoherence process observed in a crystalline semiconductor using high-order wave-mixing spectroscopy. Our findings indicate that the dephasing time, conventionally considered a fixed preset, can be influenced by our observations, with full quantum theory substantiating this finding. Our research bridges quantum information with strong field physics and contributes to the understanding of system coherence in the real environment.   

Why a magnetoactive quantum wire can act as an optical amplifier

The fundamental issues associated with the magnetoplasmon excitations are investigated in a

quantum wire characterized by a confining harmonic potential and subjected to a perpendicular

magnetic field. Essentially, we embark on the device aspects of the intersubband collective

(magnetoroton) excitation which observes a negative group velocity between the maxon and the

roton. The computation of the gain coefficient suggests an interesting and important application:

the electronic device based on such magnetoroton modes can act as an optical amplifier   

Electron transport under an ultrafast laser pulse: Implication for spin transport

In the electric-field induced transport, a voltage bias is applied

across a device. The chemical potential difference between the drain

and source drives the charge carrier across the device.  So the moving

direction of charge carriers is along the electric field. But in

laser-induced electron transport, both the electric and magnetic

fields are transversal to the ligt propagation, so how the electrons

move along the longitudinal direction is not obvious, but is very

critical to our current understanding of spin transport. In this talk,

we show that a general mechanism is working. Although the magnetic

field B is weak, it is this field that steers the electron

moving along the light propagation direction, besides its strong

transverse motion.  We employ the formalism put forth by Varga and

Toroke and confirm that if we only include E, the electron

only moves transversely with a large velocity, but once including both

B and  E, and using real experimental laser parameters, we

are able to demonstrate that a laser pulse can drive the electron

along the axial direction by 40 to 400 Å, consistent with the

experiments.  The key insight is that  B changes the direction of

the electron and allows the electron to move along the Poynting vector

of light. Our finding has an important consequence.  Because a nonzero

B means a spatially dependent vector potential A(r, t), B =▽×A(r, t), this points out that

the Coulomb gauge, that is, replacing  A(r, t) by a spatially independent A(r) is unable to describe electron and spin

transport under laser excitation.  Our finding is expected to have a

potential impact the investigation of laser-driven spin transport.   

Classical Radiation Damping and Fano Interference in Cyclotron Motion based on Liouvillian Complex Eigenvalue Problem

We study the emission of light due to classical radiation damping of an electron that undergoes cyclotron motion inside an electromagnetic waveguide by solving the Liouville equation. A classical Van Hove singularity appears at the lower bound of each continuum mode (i.e., at each cut-off frequency) that supports light transport in the waveguide. Based on the complex spectral representation of the Liouvillian in terms of classical coherent states, we found a similar structure to the quantum Fano spectrum and Fano gap in the light spectrum in the vicinity of the classical Van Hove singularity.   

Photoluminescence quenching of CsPbBr3 perovskite nanocrystals assisted by ion implanted silver nanoparticles

In this work, we discussed the photoluminescence (PL) of CsPbBr₃ perovskite in the presence of ion implanted silver nanoparticles. Fixed ion beam energy (70 keV) and different ion beam fluences were used for silver nanoparticles synthesis. The change in the chemical composition, concentration and depth profile of ion implanted samples were analyzed by Rutherford Backscattering (RBS) analysis. The existence of silver nanoparticles in the implanted samples was studied using optical absorption spectroscopy. Both steady state and time resolved photoluminescence measurements were carried out to investigate the effect of silver nanoparticles on the photoluminescence of CsPbBr₃ perovskite. The PL quenching of CsPbBr₃ perovskite has been observed with the increased ion beam fluence and increased concentration of silver nanoparticles. The PL quenching was attributed to possible energy transfer from CsPbBr₃ to silver nanoparticles, which was evident by a decrease average lifetime of CsPbBr₃.​     

Characterizing Squeezed Light in the Quest Experiment

Squeezed vacuum states provide a crucial tool for increasing gravitational wave detector precision capabilities beyond the standard quantum limit. The QUEST experiment makes use of the squeezed states of light to increase detector sensitivity, lowering the ’shot noise’ threshold. Squeezing light at 1064 nm using a non-linear crystal, QUEST expects to produce 6dB of squeezing, producing sensitivity to interferometric mirror displacements of ≈ 10-19m/√Hz. We inject squeezed light beam into one of the two twin interferometers in the QUEST experiment, and characterize the squeezed beam. The squeezed beam and coherent beam were maximally overlapped and mode-matched 88%. The power losses of each optic in the squeezed beam injection path are detailed. Though ideal overlap between the coherent and squeezed beams was not achieved, 3 dB of anti-squeezing and ≈ 0.5 dB of squeezing were produced. Next steps for squeezing characterization are also proposed.   

Quantum Control Enhanced Resonant Atom Interferometry by Sharika Saraf and Kefeng Jiang

Resonant atom interferometry is a method by which a multi-loop interferometer signal can be amplified by a factor of twice the loop number at the resonant frequency. As multi-loop interferometers involve the use of repeated mirror pulses, one limiting factor is imperfect mirror pulse efficiencies that deplete population from the main interferometer path. The advantages of a high Rabi frequency mean that we are interested in increasing laser intensity, which lends itself to intensity inhomogeneities that impact pulse efficiency. Thus, we are left with “stray” paths that interfere with one another, resulting in neighboring families of interference patterns as well as that of the main interferometer path. One solution is to engineer multi-pulse mirror sequences by optimizing the phases applied to single pulses, as well as the number of pulses per sequence, to maximize the population in the main interferometer path. This poster will describe the results of our quantum control enhanced resonant atom interferometry apparatus and discuss improvements that can be achieved with optimal control methods.    

Topological quadratic-node semimetal realized in a photonic microring lattice

Graphene, with its two linearly dispersing Dirac points with opposite windings, is the minimal topological nodal configuration in the hexagonal Brillouin zone. Topological semimetals with higher-order nodes beyond the Dirac points have recently attracted considerable interest due to their rich chiral physics and their potential for the design of next-generation integrated devices. Here we report the experimental realization of the topological semimetal with quadratic nodes in a photonic microring lattice. Our structure hosts a robust second-order node at the center of the Brillouin zone and two Dirac points at the Brillouin zone boundary—the second minimal configuration, next to graphene, that satisfies the Nielsen–Ninomiya theorem. The symmetry-protected quadratic nodal point, together with the Dirac points, leads to the coexistence of massive and massless components in a hybrid chiral particle. This gives rise to unique transport properties, which we demonstrate by directly imaging simultaneous Klein and anti-Klein tunnelling in the microring lattice.   

Thermo-optical bistability of micro-cantilevers

The attenuation length of visible light in silicon is of the order a few µm, which is comparable to the thickness of the µ-cantilevers used for Atomic Force Microscopy (AFM). The light beam used to measure the deflection is therefore often not zero on the bottom face of the lever, where it can be reflected and interferes with the incident wave. Concretely, the lever is for the light field an absorbing Fabry-Pérot cavity, which interference state is a function of the cantilever thickness, the wavelength, and the optical index of silicon. This interference state drives the value of the reflectance, absorbance and transmittance of the lever. The reflectivity may for example vary by a factor of 2 for very weak variations (less than 100nm) of the thickness.

The absorbed fraction of the light radiation corresponds to a heat source at the extremity of the lever, and in the stationary state this heat flux is dissipated by convection in the surrounding fluid, thermal conduction along the lever toward its support, and thermal radiation. In vacuum, thermal conduction is the dominant process, and quickly end up in very high temperatures (several hundreds of degrees for a few mW of incident power).

The optical index of silicon depending on temperature, so does the interference state of the light field in the cantilever thickness. This interference state driving itself the absorption of light, it retroacts on the heat flux, hence on temperature. We thus have a closed loop between absorption and temperature, that may induce a non-monotonic, or even instable, behavior: when the absorption is a steep increasing function of temperature, if the light power raises, the heat flux follows, so does the temperature, increasing the absorption, thus the heat flux, and so on. We observe in some cases a hysteretic behavior between high and low temperature branches when the input power is cycled. Temperature jumps of few hundred degrees can be measured during the hysteresis cycle. We will detail the mechanism of this thermo-optical bistability.    

ESR with Radiation Damping

We present an expansion of coherent control in the field of Electron Spin Resonance (ESR) for long T1 samples, achieved through the engineering of radiation damping. This advance enables efficient spectroscopy in cases with long T1 relaxation times. Our exploration of ESR dynamics involves the utilization of high quality factor, small magnetic mode volume superconducting resonators (Nb or YBCO). Our system is capable of operating at 0.45 K using a custom He-3 refrigerator. We demonstrate long-lived transient response induced by radiation damping, achieved through appropriate design of spin-cavity system parameters. This study is a step toward controlling cavity-mediated spin-spin interactions.   

Cavity magnonics with easy-axis ferromagnet: critically enhanced magnon squeezing and light-matter interaction

Generating and probing the magnon squeezing is an important challenge in the field of quantum magnonics. In this work, we propose a cavity magnonics setup with an easy-axis ferromagnet to address this challenge. To this end, we first establish a mechanism for the generation of magnon squeezing in the easy-axis ferromagnet and show that the magnon squeezing can be critically enhanced by tuning an external magnetic field near the Ising phase transition point. When the magnet is coupled to the cavity field, the effective cavity-magnon interaction becomes proportional to the magnon squeezing, allowing one to enhance the cavity-magnon coupling strength using a static field. We demonstrate that the magnon squeezing can be probed by measuring the frequency shift of the cavity field. Moreover, a magnonic superradiant phase transition can be observed in our setup by tuning the static magnetic field, overcoming the challenge that the magnetic interaction between the cavity and the magnet is typically too weak to drive the superradiant transition. Our work paves the way to develop unique capabilities of cavity magnonics that goes beyond the conventional cavity QED physics by harnessing the intrinsic property of a magnet.   

Squeezed Light in a Cryogenic Optomechanical System

Frequency-dependent squeezed states are quantum states of light that allow measurements to beat the Standard Quantum Limit, providing sensitivity improvements to gravitational wave interferometers and improving optomechanics and quantum computing experiments. A tabletop optics frequency-dependent squeezed light (FDSL) generator and phononic crystal membrane experiment at the Kastler Brossel Laboratory (LKB) in Paris were optimized, with the goal of eventually combining the two experiments into a larger FDSL cryogenic optomechanical system. In the squeezed light generator, devices were designed to improve the crystal positioning in the SHG and OPO in order to ease mode matching. The SHG was aligned and mode-matched, with an optimized conversion efficiency of 54.3%, superb for squeezing purposes. Future work involves optimizing the OPO, mode cleaner, and filter cavity before making a final measurement of FDSL, which is expected to be an improvement from LKB's previous tabletop squeezer. In the membrane experiment, a Q factor of 56,793 was obtained for a square SiN membrane at room temperature and atmospheric pressure, comparable to values in the literature. Two novel phononic crystal membranes—the Lotus and Dahlia—were designed and the first wafers were fabricated in the clean room. Future work involves testing phononic crystal membranes in cavities of various sizes and under cryogenic vacuum conditions as well as comparing the two designs to determine the optimal design for the final cryogenic optomechanics experiment.   

Calculation of spin-rotation coupling and hyperfine structure of chiral molecules for parity violation measurements

Understanding parity violation in molecules is of great significance in the realm of modern physics and chemistry. It tests the Standard Model and probes links between molecular chirality and the weak force. To achieve this goal, we need to perform precision measurements of the energy levels of chiral molecules using quantum logic spectroscopy (QLS). Here, we provide theoretical insight to determine the molecular level structure and transition matrix element. We report calculations evaluating the rotational levels of the molecule. Specifically, we calculate the rotational constant, g-tensor, and spin-rotation constant, and construct the Hamiltonian that describes rotation of the molecule, and coupling of the rotational angular momentum, nuclear spin, and external magnetic field. These calculations are expected to guide experimental design and precision measurements.   

Impact of dephasing probes on incommensurate lattices.

We investigate open quantum dynamics for a one-dimensional incommensurate Aubry-Andre-Harper lattice chain, a part of which is initially filled with electrons and is further connected to dephasing probes at the filled lattice sites. This setup is akin to a step-initial configuration where the non-zero part of the step is subjected to dephasing. We investigate the quantum dynamics of local electron density, the scaling of the density front as a function of time both inside and outside of the initial step, and the growth of the total number of electrons outside the step. We analyze these quantities in all three regimes, namely, the de-localized, critical, and localized phases of the underlying lattice. Outside the initial step, we observe that the density front spreads according to the underlying nature of single-particle states of the lattice, for both the de-localized and critical phases. For the localized phase, the spread of the density front hints at a logarithmic behaviour in time that has no parallel in the isolated case (i.e. in the absence of probes). Inside the initial step, due to the presence of the probes, the density front spreads in a diffusive manner for all the phases. This combination of rich and different dynamical behaviour, outside and inside the initial step, results in the emergence of mixed dynamical phases. While the total occupation of electrons remains conserved, the value outside or inside the initial step turns out to have a rich dynamical behaviour. Our work is widely adaptable and has interesting consequences when disordered/quasi-disordered systems are subjected to a thermodynamically large number of probes.   

Interaction of a qubit with a transistor-like material

We theoretically study a system that consists of a two-level system interacting with the two-dimensional transistor-like optical platform introduced in [1]. The optical response of the two-dimensional material is tailored by a static electric field through a non-Hermitian linear electro-optic effect rooted on a Berry curvature dipole. The dynamical response of the material mimics that of a transistor but in a distributed area. Here, we use a quasi-static approximation to describe the interactions of an elementary qubit with the transistor-like material. We obtain a quantum (Lindblad-type) master equation written in terms of the system Green’s function, taking into account that the considered platform may provide optical gain. We analyze the time-evolution of the qubit state, showing how the optical gain tailors the light-matter interactions and gives rise to rather peculiar and exotic effects such as negative spontaneous emission and time-crystal like oscillations in the ground state.

[1] T. G. Rappoport, T. A. Morgado, S. Lannebère, M. G. Silveirinha, “Engineering transistor-like optical gain in two-dimensional materials with Berry curvature dipoles”, Phys. Rev. Lett., 130, 076901, 2023.   

Transport and integrability-breaking in non-Hermitian many-body quantum systems

The effective description of open quantum systems in terms of non-Hermitian Hamiltonians gives rise to non-unitary time evolution. Here, we study how non-unitary dynamics affects the emergent hydrodynamics in systems with a globally conserved quantity. To this end, we show how dynamical correlation functions can be generalized to the non-Hermititan case. Moreover, we demonstrate that the concept of dynamical quantum typicality provides a useful numerical approach to evaluate such correlation functions, albeit with non-unitary time evolution leading to certain subtleties compared to the usual Hermitian setting. As a convenient starting point for our numerical investigation, we consider the Hermitian spin-1/2 XXZ chain, whose high-temperature transport properties have been studied extensively in recent years. We add different non-Hermitian perturbations to the XXZ chain and explore their effect on the resulting hydrodynamics. In this context, we also discuss the role of integrability by studying the complex energy-level statistics of the non-Hermitian quantum models.   

Limitations of a large momentum atom interferometer acceleration sensor due to spontaneous emission

Atom interferometry has been a successful quantum sensing application. Recently ways to increase the sensitivity has become a current topic of interest. One way to increase the sensitivity is an increase in the momentum of the atom cloud. This has been done through increasing the number of Raman π - pulses. In this approach, a longer stay in the intermediate high energy state, which is often neglected through adiabatic elimination due to large optical detuning, causes a higher chance of undesired spontaneous decay. Another way is by implementing Bragg scattering pulses which also can bring in spontaneous emission due to increased interaction time. The loss of quantum information of the atomic states due to this undesired spontaneous decay will add an additional error to the atom interferometer. In this work, we use the Lindblad master equation to devise a model for the atomic state dynamics that incorporates the undesired spontaneous decay. We determine an error figure of merit to analyze the error in the measurement of local acceleration. Our theoretical results show the noise will be dominated by the inverse square dependence on the number of Raman or Bragg pulses in low numbers of pulses, while the measurement error in the high numbers of pulses will be dominated by the loss of quantum information through the undesired spontaneous decay. Our figure of merit reaches a minimum at a specific pulse number depending on the Raman or Bragg pulses used before the error starts to increase.   

Non-reciprocal solitary waves in the parity-broken Ablowitz-Ladik model

The Nelson-Ninomiya (NN) theorem precludes the existence of states with unidirectional propagation in 1D crystals. In this work, we show that, upon breaking parity symmetry, certain types of nonlinear lattices circumvent the limitations of the NN theorem, enabling self-induced non-reciprocal dynamics. Specifically, we study the Ablowitz-Ladic (AL) model, an integrable discretization of the nonlinear Schrodinger equation. In its standard form, the AL equation supports stable nonlinear localized eigenstates, i.e., solitons. We demonstrate that breaking parity in this model can either generate non-reciprocal linear instabilities on its static soliton states or drive them into a fully non-reciprocal regime, in which the static soliton solutions cease to exist but, although still localized, nidirectionally accelerate and amplify towards one end of the lattice.    

Two-step Bose-Einstein condensation coming from a temperature dependent energy gap.

Regardless of the microscopic mechanism that generates it, electron pairing is fundamental to observe superconductivity where Cooper pairs show a temperature dependent energy gap (TDEG) which abruptly disappears at the superconducting critical temperature.

Here we explore the effects of a TDEG on the properties of a Bose gas whose energy spectrum is that of an ideal Bose gas (IBG) with a BCS TDEG at its lower edge.  

The first thing we observe is that the Bose-Einstein condensation (BEC) critical temperature T_c of our gas is equal to the BEC critical temperature T₀ of the IBG if the temperature T_B at which the gap dissapears is lower than T₀; If T_B ≥ T₀, T_c ≥T₀. Secondly, for T_B  < T₀, the condensed fraction as a function of temperature presents two different rates to populate the ground state: one at T₀ and a higher one at T_B, generating a kind of two-step BEC. Third, the specific heat as a function of temperature exhibits a finite jump as when the gap is temperature independent [1] but also an infinite jump at the temperature T_B where the BCS gap abruptly disappears with an infinite slope [2]. We discuss possible connections of our model results with what has been observed in superconductivity.

[1]   J.G. Martinez-Herrera et al., Phys. Scri. 94 (2019) 075002.

[2] J.J. Valencia and M.A. Solís, Two-step Bose-Einstein condensation coming from a temperature dependent energy gap, to be published.   

In-Operando Study of Ferroelectric Domains Using Bragg Coherent Diffraction Imaging

Strain can greatly effect a materials properties, especially in ferroelectrics. Using in-operando x-ray Bragg Coherent Diffraction Imaging (BCDI), we can investigate the strain field in materials in response to real time stimuli. With continued improvements in coherence from next generation light sources and advanced phase retrieval algorithms, BCDI allows for full volume visualization of the electron density distributions and displacement fields in nanoparticles with nanometer resolution. Using this technique, we have identified 3D vortex structures within ferroelectric BaTiO₃ nanoparticles and studied their evolution under applied electrical fields [1]. Currently we are extending BCDI to probe other classes of functional materials with unusual ferroelectric polarization structures. We hope this research will provide insight into domain structure control and switching in ferroelectric nanomaterials, with potentially promising applications in next generation electronic devices.   

Both Classical and Quantum Obitals may be a Subgroup of the Mobius and Higher dimensional Mobius like Orbitals

When one Twin heads to say "Alpha Centauri" near the speed of light, and the other twin remains on Earth, the traveling Twin returns to the Earth younger than the Twin that remained. This situation can be remedied if the stationary Twin travels to Alpha Centauri at the same velocity using the same orbital and returns. Kepler discovered three types of Obitals, the Parabolic, the Elliptical and the Hyperbolic. If one takes the Earth and Alpha Centauri as a single system and the Twins as both using an Elliptical orbit about some point in the center, then one can clearly see that the entire orbital to restore the system to its original situation as having 720 degrees. It is a mobius. Minkowski surmised the Relativity is in Hyperbolic Space, due to its velocity, but it can be surmised that the three types of Orbitals are Subgroups of the Mobius, and that there may be higher dimensional orbitals that make this type of Mobius a subgroup. This author would like to point out that most of the energy of Quark systems is in the orbitals and would like to conjecture that what an observer actually measures in Particle Physics are these orbitals. So the "Group" structure seen in particle physics comes from the type of orbitals the particles can make. Of course wilder conclusions can be made regarding the nature of time and it's relation to orbitals. This author will save the wilder conclusions until later, as this situation has not been proven, but would like to delve into the many types of orbitals seen in Classical Physics, Atomic Physics and the Physics of fundamental particles.   

Harnessing Quantumness of States using Discrete Wigner Functions and Protecting it using Weak Measurement from Non-Markovian Quantum Noise

The negativity of the discrete Wigner functions (DWFs) is a measure of non-classicality and is often used to quantify the degree of quantum coherence in a system. Studying Wigner's negativity and its evolution under different noisy non-Markovian quantum channels provides insight into the stability and robustness of quantum states. The variation of DWF negativity of qubit, qutrit, and two-qubit systems under the action of (non)-Markovian random telegraph noise and amplitude damping noise is investigated. Different negative quantum states that can be used as a resource for quantum computation and quantum teleportation are constructed. Quantum computation and teleportation success is estimated for these states under (non)-Markovian evolutions. Weak measurement (WM) and quantum measurement reversal (QMR) protect against quantum states' collapse and are used to preserve and enhance quantum correlations and universal quantum teleportation protocol.

We study the quantum correlations, maximal fidelity, and fidelity deviation of the two-qubit negative quantum states developed using DWFs with (without) WM and QMR. We evolve the states via the above-mentioned non-Markovian channels to consider the effect of the noisy environment. To benchmark the performance of negative quantum states, we compare our results with the two-qubit maximally entangled Bell state. Interestingly, we observe that some negative quantum states perform better with WM and QMR than the Bell state for different cases under evolution via noisy quantum channels.   

Single-Photon Emission due to non-Hermitian Anharmonicity

Single-photon sources play a vital role in light-based quantum-information systems [Nature Photonics 3, 687 (2009)]. One well-known design for such sources is a coupled emitter-cavity system in the strong-coupling regime. Single-photon emission is then achieved through the photon blockade phenomenon, where the absorption of one photon induces large enough energy shifts in the system to prevent the absorption of subsequent photons [Nature 436, 87 (2005), Nature 454, 315 (2008)]. We propose a novel non-Hermitian photon blockade mechanism that works in the weak-coupling regime and does not require strong coupling [Phys. Rev. Lett. 130, 243601 (2023)]. This mechanism does not rely on changes in the absorption energy, but on changes in the absorption bandwidth of the states and can be understood as the detuning of the effective non-Hermitian energies in the complex plane. We demonstrate an implementation of this idea using hybrid metallodielectric cavities that incorporate photon modes with different loss rates and show that high-purity single-photon emission at high repetition rates could be achievable in such systems [Phys. Rev. Lett. 130, 243601 (2023)].   

Dynamical Polarization, Plasmon and Energy Loss of Kekule-distorted Graphene Under Circularly Polarized Irradiation

The high frequency electromagnetic irradiation within the off-resonance regime significantly changes the electronic transport and optical properties of Dirac systems. Here, we have studied the effect of circularly polarized irradiation on the energy band, dynamical polarization and the plasmon excitations of Kek-Y phases of graphene. It is found that the large gap is induced between two bands and between two concentric Dirac cones which considerably modifies the polarization function and consequently the plasmon dispersion. The plasmon damping rate and the rate of loss of energy of a charge particle moving parallel to the 2D sheet is calculated numerically. To further explore the electronic transport properties of Kek-Y graphene, the analytical solution for the transmission and reflection coefficients are also derived. It is observed  that both the reflection and transmission of electrons conserve the energy, and therefore have the finite probability for the particle to transfer from one band to another.   

Silicon-Vacancy Centers in Nanodiamonds for Applications in Quantum Networks

Combining conventional photonic systems with the good optical and spin properties of group IV defects in diamond puts a platform for quantum technologies into reach. Here, we present measurements of characteristic optical and spin properties of negatively-charged Silicon-vacancy centers (SiV) in diamond [1]. At liquid Helium temperatures latter properties are strongly degraded due to interaction with the surrounding phonon bath leading to fast spin dephasing [2]. In our approach, we use nanodiamonds as a host which modifies the aforementioned characteristic features of SiV [3], thereby revealing key benefits with regards to spin coherence compared to conventional bulk diamonds while simultaneously enabling future hybridization with photonic structures, e.g. photonic crystal or open micro-cavities [4,5].   

Optoelectronic transduction of Cavity Optomechanics

Cavity optomechanics studies the interaction between light and mechanical vibrations . It has its roots in gravitational wave interferometers and has matured as a separate field. One research direction in cavity optomechanics is quantum systems and science , On the classical side, nano-optomechanical systems are promising as sensors. While there have been many demonstrations of cavity nano-opto-mechanical devices (NOMS) , a sensing application requires the NOMS to self-oscillate and extractability of the oscillation signal within the chip. We demonstrate such a system using a cavity NOMS integrated with metal-semiconductor-metal (MSM) photodetector. the mechanical signal is imprinted on the light via dispersive coupling of optical cavity with mechanics. Finally, the light is detected through the MSM photodetector.  

Serving as a proof-of-concept, the device utilizes simple to fabricate elements and highlights this architecture for applications of cavity optomechanical devices as Oscillators.    

Poster: A Computational Study of Extreme Ultraviolet High Harmonic Generation

Frequency combs are highly coherent light sources that transmit equally spaced, mutually coherent spectral lines, therefore pushing the boundaries of metrology, spectroscopy, and atomic clocks. Specifically, extreme ultraviolet frequency combs are a compelling candidate for precise optical measurements of distance, time, and molecular composition of interstellar fingerprints. High-harmonic generation (HHG) is the most prominent method for generating frequency comb light transfer into the extreme ultraviolet range of the electromagnetic spectrum. We present a design for a HHG light source optimized for precision spectroscopy across a wide wavelength range from 100 to 200 nm. Using a density functional theory framework simulation, we explore HHG in a Xe gas scheme and in promising solid-state materials to determine the best medium for HHG with high power per tooth for precision measurements.   

Loss-induced Purcell enhancement in PT-broken whispering gallery microcavities

Parity-time (PT)-symmetry brings various opportunities for electromagnetic field manipulation and light–matter interaction, such as modification of spontaneous emission. However, previous works mainly focused on the behavior of spontaneous emission at exceptional points or in the PT-symmetry situation. Here, we theoretically demonstrate loss-induced Purcell enhancement in PT-broken whispering gallery microcavities. In the PT-broken phase, one of the supermodes decays slowly thereby playing a leading role in spontaneous emission. As the loss increases, the quality factor of this supermode is higher and the mode volume is smaller, so that the Purcell factors will be larger if the emitter is placed near the lossless cavity. Our findings indicate that loss can enhance the interaction between light and matter, which could be applied to single photon emission, non-Hermitian photonic devices, etc.   

Polaron-Depleton Transition in the Yrast Excitations of a One-Dimensional Bose Gas with a Mobile Impurity

We present exact numerical data for the lowest-energy momentum eigenstates (yrast states) of a repulsive spin impurity in a one-dimensional Bose gas using full configuration interaction quantum Monte Carlo (FCIQMC). As a stochastic extension of exact diagonalization, it is well suited for the study of yrast states of a lattice-renormalized model for a quantum gas. Yrast states carry valuable information about the dynamic properties of slow-moving mobile impurities immersed in a many-body system. Based on the energies and the first and second-order correlation functions of yrast states, we identify different dynamical regimes and the transitions between them: The polaron regime, where the impurity's motion is affected by the Bose gas through a renormalized effective mass; a regime of a gray soliton that is weakly correlated with a stationary impurity, and the depleton regime, where the impurity occupies a dark or gray soliton. Extracting the depleton effective mass reveals a super heavy regime where the magnitude of the (negative) depleton mass exceeds the mass of the finite Bose gas.   

Non-adiabatic transitions in parabolic and super-parabolic $mathcal{PT}$-symmetric non-Hermitian systems in one-dimensional optical waveguides

Exceptional points, which are spectral degeneracy points in the complex parameter space, are fundamental to non-Hermitian quantum systems. The dynamics of non-Hermitian systems in the presence of exceptional points differ significantly from those of Hermitian ones. Here we investigate non-adiabatic transitions in non-Hermitian $mathcal{P}mathcal{T}$-symmetric systems, in which the exceptional points are driven through at finite speeds which are quadratic or cubic functions of time. We identity different transmission dynamics separated by exceptional points, and derive analytical approximate formulas for the non-adiabatic transmission probabilities. We discuss possible experimental realizations with a $mathcal{P}mathcal{T}$-symmetric non-Hermitian one-dimensional tight-binding optical waveguide lattice, through non-Hermitian Bloch oscillations between different bands.   

Towards Ultracold Fermions in the Optical Kagome Lattice

Our efforts are focused on producing a degenerate fermi gas of ⁴⁰K atoms and loading it into an optical kagome lattice. This special lattice geometry is geometrically frustrated and exhibits a flat band that enhances interaction effects. Our system allows us to easily study many-body effects such as flat band ferromagnetism. We utilize a specific lattice setup that allows us to arbitrarily translate the lattice allowing for Floquet-type dynamics and wide-range manipulation of the quasimomentum. We describe experimental progress towards creating degenerate fermi gases of ⁴⁰K using sympathetic cooling with ⁸⁷Rb, loading a degenerate fermi gas into the optical kagome lattice and generating arbitrary lattice potentials. In addition, future directions of research are presented.   

Controlling Anderson localization of a Bose-Einstein condensate via spin-orbit coupling and Rabi fields in bichromatic lattices

We perform theoretical studies of the interplay between disorder, spin-orbit coupling (SOC), and Rabi fields, and show that both SOC and Rabi fields can be used to dramatically control the degree of Anderson localization of a Bose-Einstein condensate in bichromatic lattices. We obtain ground-state phase diagrams in the SOC and Rabi field plane for different values of disorder strength and use realistic experimental parameters compatible with 39K. We find cases of fixed disorder and SOC (Rabi field), where the Rabi field (SOC) reduces the threshold for localization and controls the localization length. We also show regimes of fixed disorder and Rabi field, where the extent of the ground-state wave function is periodic in the SOC, leading to alternating regions of stronger and weaker localization as SOC changes. Lastly, we describe examples of fixed disorder and SOC, where tuning the Rabi field leads to a strong localization peak.   

Enhancing Image Quality: Design and Aberration Control in a 5X Mechanically Compensated Imaging System

In this work, we introduce a 5X zoom camera system. A mechanically compensated zooming lens system with only two moving lenses was designed, with the capability to vary zoom ratios from 5X to 2X and 1X. All configurations were modeled and simulated with Zemax ray-tracing code. Image quality was optimized using aberration coefficients to improve the resulting image, intensive work was dedicated to minimizing image aberrations. During the optimization process, we prioritized eliminating chromatic and spherical aberrations as much as possible. Many challenges had to be addressed, such as stray light, spherical aberration, field of view, etc. Stray light was controlled by a series of apertures. A comparative study of all system configurations was conducted. We evaluated varied methods to improve image quality and compared aberration coefficients between the original and optimized optical system. Future work will be aimed at improving zoom while maintaining image quality and making the system more compact and portable.   

Algol Research and West Point Observatory Improvement Project

The purpose of this project is to verify the eclipsing period of the binary star system Algol, to calculate the mass and radius of the component stars utilizing data from external sources, conduct a literature search of historical data on Algol, and to add additional hardware to the West Point observatory that will allow overnight imaging to take place. To observe the orbital period of Algol, we plan to use the West Point observatory to capture images of the star system during a predicted eclipse. We then plan to measure the change in brightness of the star system by comparing it to neighboring stars. After that we plan to graph these values to get a light curve. Due to the duration of Algol’s eclipse, the observatory needs additional instruments so it will be able to close in the event of potentially damaging weather without the need for human intervention. It is necessary that we install this hardware prior to imaging the 10-hour eclipse of Algol. In addition to this, we intend on keeping a lookout for small-bodies that may pass by or occult Algol using NASA’s Small-Body Identification Tool.

    

Evolution of Excitonic Species of Nano-Interfaces in MoxW1-xS2 Monolayer Heterostructures

Here, a Mo_xW_1-xS₂ is synthesized using A liquid-phase precursor-assisted synthesis approach which results in Mo_xW_1-xS₂ in-plane heterostructures possessing a Mo-rich center and a W-rich edge region, with an alloyed 2D interface of ~100 nm width. According to the detailed spectral analysis of the photoluminescence spectra as a function of temperature (4K-300K) and laser excitation intensities, the evolution of the A exciton, B exciton, and Trion of different regions in the Mo_xW_1-xS₂ in-plane heterostructures are comparable with the reported values for the pristine MoS₂ and WS₂. And, the sharp interface region combines both excitonic specious of the MoS₂ and WS₂. Besides, first-principles calculations is performed to address the effect of the spin-orbit interaction in Mo_xW_1-xS₂ to understand the evolution of the A and B excitons. Our research underscores the possibility of concurrently engineering optical properties to create innovative devices utilizing these 2D monolayers and opens up significant potential for various practical applications.   

Optical, Electrical, and Magnetic Studies of Gd-Doped ITO Thin Films

This work investigates the optical, electrical, and magnetic properties of Gadolinium-doped Indium Tin Oxide (ITO) thin films. ITO is a well-known example of a transparent conducting oxide (TCO). Vast developments in flat panel displays, solar cells, LEDs and wearable electronics are outcomes of heavy research on TCOs. These materials are electrically conductive, yet optically transparent due to their large energy band gap. On the other hand, advances in spintronic devices require the introduction of good dilute magnetic semiconductors (DMS). In an effort to produce transparent DMS, Gd-doped ITO films were prepared by simultaneous dc magnetron sputtering from ITO and gadolinium targets. Samples prepared for this investigation were deposited in the absence of excess oxygen to establish conditions that are more favorable for high electrical conductivity. For substrates we used fused silica, silicon, and sapphire. Thin films of ITO doped with various Gd concentrations are then investigated by low temperature photoluminescence, transmission measurements, ellipsometry, SQUID magnetometry and x-ray diffraction. Preliminary results suggest the possibility of fabricating a transparent, conductive, and magnetic thin film of Gd-doped ITO.   

Controlling the nuclear spin of NV centers in random orientations toward memory-enhanced quantum sensing

In medicine and industry, there is a high demand for measuring magnetic field vectors with high spatial resolution and sensitivity under ambient conditions. Due to limited spatial resolution and particular working temperatures, existing magnetic sensors such as SQUID are only sometimes available. One of the promising candidate platforms for such high-performance magnetometers is the nitrogen-vacancy (NV) center, hosting an electronic spin accompanied by a ¹⁴N nuclear spin in diamond. The efficient method to improve the signal-to-noise ratio is to use a nitrogen nuclear spin as a memory. However, controlling the nuclear spin has been demonstrated only in the case of the static magnetic field along the NV axis. Here, we present our novel idea of polarizing the nuclear spin and suppressing the modulation under a static magnetic field with an arbitrary orientation. Our approach may pave the way toward enhanced sensitivity of vector magnetometry by NV center.   

Compact, configurable laser systems for deployable quantum applications

With inherent precision, sensitivity, and traceability afforded by the atomic systems at their heart, advanced quantum sensors are poised to become integral parts of otherwise everyday platforms. The full potential of state-of-the-art atomic clocks, magnetometers, electric field sensors, and inertial sensors will be realized when these technologies are advanced from their development in research labs to deployment in field applications on moving platforms. The size, weight, power, and cost (SWaP-C) of required laser systems must be reduced, and robustness to environmental perturbations must be improved, to meet the challenging requirements of deployed applications. Vescent, being a lead manufacturer of systems for deployable quantum, is actively developing modular laser and control systems that are not currently commercially. Optical frequency combs, MOT and Raman lasers, and ultranarrow linewidth lasers will be reviewed for performance in both laboratory and harsh environments. Vescent has developed these systems for fielded next-generation quantum applications, such as cold atom microwave and optical atomic clocks that are intended as improvements to existing GPS timing systems. Frequency instability, optical power, relative intensity noise, and overall power consumption will be reviewed. Discussions on the impact that these laser systems would have on real-world quantum applications will be estimated.   

Effect of vibration on the crystallizaion of ZBLAN.

ZBLAN (ZrF4-BaF2-LaF3-AlF3-NaF) a fluorozirconate glass exhibits the capacity for optical transmission from 0.3μm in the UV to 7μm in the IR region. However, the formation of crystalline structures during the fiber drawing process hinders the glass from achieving its minimal signal attenuation. This research is centered on understanding the role of vibration in the crystallization behavior of ZBLAN under terrestrial gravitational conditions. With a series of controlled experiments with varying vibration frequencies and temperatures, the effects of these parameters were examined on the kinetics and morphology of ZBLAN glasses. Results suggest that there is a significant correlation between specific vibration frequencies, temperature, and the resulting crystalline structures. By elucidating the underlying mechanisms governing the impact of vibration of ZBLAN crystallization, this research aims to contribute to the development of optimized manufacturing processes, ultimately enhancing the optical performance of ZBLAN glasses. The insights gained from this study hold potential implications for the enhancement of the design and manufacture of advanced optical materials for various practical applications like, telecommunication systems, medical devices, and so on.   

Newton’s (1/m) Catastrophe: Newton’s 2nd Law of Nature is Fatally Wrong, But Fixable

A century of work focused on (1/m) as variable mass increases become zero.  For example, the photon should travel at infinity speed with zero mass.  This poster follows the logic that an inverse must coordinate, as in a₁a₂=K.  That is as one object slows the zero, by Newton’s (1/m) catastrophe, the corresponding object must accelerate to infinity!

The challenge is similar to the Rayleigh-Jeans ultraviolet catastrophe.  That logic was fixed by a new equation, Planck’s.  This approach is very similar.

Newton’s 2^nd Law of Nature is fatally wrong, But Fixable by an acceleration allocation segment that follows directly from localization and LDA in DFT at scale 1/(d/dBase)^3/4.  By current use of (1/m), we are introducing errors and the many error-correction techniques including:

Observation of photon sphere modes in black hole microcavity laser

One of interesting phenomena of a black hole (BH) in its vicinity due to its extreme curvature of spacetime is called a photon sphere (PS), a closed trajectory where photons get trapped and orbit. In this work, we design novel 3D microcavities and investigate lasing on modes localized on a PS, induced by attractive nature of BH. We explore these eigenmodes by conformally transforming a Schwarzschild BH metric into a 2D plane with varying refractive index. We analytically confirm the existence of PS modes by extending our previous theory of conformal transformations [PNAS 119, e2112052119 (2022)] into open systems, and solving the wave equation under a WKB framework. To numerically induce lasing of PS modes, we selectively pump the 2D cavity above the vicinity of the PS. The lasing process is revealed by a 3D finite-difference time-domain simulation coupled to the atomic population of a four-level atomic structure. A lasing mode localizing on PS is observed in its emission spectrum. Experimentally, the corresponding 3D curved surface, which is parabola-like, is fabricated by direct laser writing of dye-doped resin. The microcavity is selectively pumped on its waist by shaping the pump intensity profile, using a spatial light modulator. The effect of stability of ray trajectories on lasing properties of modes is still under investigation. The notion of BH microcavities inspires engineering of effective potential in microcavities and paves a new way to design modes with desired lasing characteristics.     

Investigation of Structural, Optical & Electrical properties of LiCoO2 thin films Grown by Pulsed Laser Deposition.

To fulfill the increasing demand for clean and green power, energy storage systems have been shaped by high energy density materials. In this regard, polycrystalline LiCoO₂ thin film has been prepared at the deposition temperatures of 400°C, and 650°C, & 700°C by pulsed laser deposition (PLD) on quartz substrate at high and (97 mTorr) low oxygen pressure (9.7mtorr). The phase evolution and surface morphology have been studied using X-ray diffraction (XRD) and Scanning electron microscopy (SEM). XRD data confirm the correspondence to the trigonal crystal lattice with the R3m space group where the LiCoO₂ film grown at 9.7 mTorr shows a significant amount of Co₃O₄ formation. Raman spectroscopy has been used to obtain information about the structural fingerprint of the prepared films by identifying the vibrational modes and it confirms the XRD analysis. UV-VIS reveals that samples grown at higher oxygen pressure has lower bandgap (2.23 eV) of about 2.24 % than the films grown at lower oxygen pressure (2.28) and electrical characteristics (conductivity measurement) demonstrate that films grown at high oxygen pressure are more electrically conductive. These findings imply that LiCoO₂ films produced by PLD hold promise for use in the production of solid-state batteries, and semiconductors.   

Dynamics of driven atom-molecule condensates

At ultracold temperatures, atoms and molecules can coherently interconvert. Recent experiments have studied this phenomenon with unprecedented detail, observing slowly damped oscillations in an atomic/molecular Bose-Einstein condensate, and how periodically modulating the coupling leads to short-time enhancement of the oscillations. Based on a coherent state variational ansatz, we present a quantitive description of these observations which includes the contributions from excited states. We show that the dominant source of damping is the molecular decay into non-condensed pairs, with a pair kinetic energy that is in resonance with the condensate oscillation frequency. Periodically driving the system enhances the oscillations at short times. However, it also leads to an accelerated decay, rapidly cutting off the initial oscillation growth.