Session FF00: Virtual Poster Session I (4pm-5:30pm CST)

Characterization of Impact Load Detection of Polymer Encapsulated Mechano-luminescing Particles as a Function of Temperature

Mechano-luminescing materials, typically in the powder form, have been the corner stone of non-destructive remote testing techniques employed for material interrogation in a variety of industries. While the exact mechanism behind tribo-luminescing/mechano-luminescing of some crystals is not fully understood, these organic and inorganic crystals have been incorporated in several different applications intended for structural health monitoring of other monolithic materials that are typically functioning under extreme conditions. Temperature-dependent mechano-luminescence is an area that has not been adequately explored and will be discussed in the work presented here. Furthermore, given that polymer composites may see a change in their modulus of elasticity at different temperatures, we will also probe the effect of temperature-induced change in elasticity, on the load detection performance of mechano-luminescing powders, as a function of placement within the polymer matrix, concentration, and composition.   

Modeling Thermogravimetry Analysis of Polyethylene Oxide Loaded with Fullerenes

Polyethylene oxide-fullerenes (PEO-C60), loaded by various amounts of C60, were obtained from homogenized solutions of water, toluene, and chloroform. Thermal degradation in nitrogen atmosphere at various heating rates ranging from 5 to 50 ^oC/min of PEO, C60 nanocomposites (PEO-C60NC), and molecular dispersions (PEO-C60MD) containing various weight fractions of C60 are reported. The research involves both the standard thermogram analysis and a detailed analysis of the derivatives and integrals of thermograms versus temperature. The coordinates of inflection points (inflection temperatures and inflection residual masses, degradation widths, and amplitudes), and areas of thermograms’ components are reported as a function of heating rate and C60 loading. The components of the thermograms’ spectrum have been deconvoluted by assuming that each main individual degradation process is described by a single sigmoid (or a single Lorentzian in the case of thermograms’ derivatives).

Data analysis is focused on the estimation of the weight fraction of the interphase in PEO-C60 nanocomposites and molecular dispersions and of the thickness of the interphase (assuming a uniform thickness of the interphase around C60). It was concluded that the thermal stability of PEO is improved by the addition of C60.   

The utilization of calcium chloride in combination with gelatin-based hydrogel for the creation of a mechanically accurate brain phantom for concussion analysis and intracranial behavior.

There are presently no mechanically accurate brain phantoms that can model the intracranial behavior of the brain during force application, thus leaving a niche void in the understanding of the brain's movement in a concussive situation. Hydrogel polymers, such as the gelatin-based material used in this project, have mechanical properties that may be adjusted with varying concentrations of calcium chloride solution combined. The cross-linking effect creates a material that can be adjusted in strength and moduli values to mimic that of the native human brain. Replication of the brain has been done through mold-casting, utilizing the ability to 3D print each region/material type of the brain to create molds matching the viscoelastic and mechanical properties exactly.   

Poster: Amplitude dependant control of harmonic waves through topological solitons

In this work, we use analytical, numerical, and experimental methods to investigate the utility of metamaterials in controlling harmonic waves based on both amplitude and frequency. Our metamaterials are composed of free floating disks with embedded permanent magnets confined within a magnetic boundary. By programming the boundary's magnetic field, we can change the energy landscape of the metamaterials and the equilibrium positions of the disks. Both disk position and surrounding magnetic field dictate the stability of the unit cell and its transmission characteristics. By engineering the metamaterials to retain bi-stable configurations (i.e., two stable phases), we elucidate the required conditions for a transition wave ( i.e., a topological soliton) to nucleate causing a phase change within the material. Each of these phases has its own transmission frequency range. We harness this phase change to control harmonic waves based on their amplitude and frequency. We showcase different scenarios with the same metamaterial configuration that can phase change from transmission to attenuation and vice versa. Such material can be utilized as a filter to either high or low amplitude signals. In addition, we show phase transitions taking place while preserving the metamaterial's state of attenuation or transmission. Such materials can continue their functionality (i.e., either attenuation or transmission of waves) while keeping a record of extreme events that can cause their transition. Our metamaterials can open the door for the next generations of advanced and functional acoustic devices.   

Twisting power predictions in a framework of minimalistic atom-atom potentisl approaches.

Chiral molecules dissolved in a nematic phase produce a chiral twisted nematic phase. The ability of a single molecule to twist a nematic phase is quantified by its twisting power. In this presentation, we consider different ways of quantifying the twisting power of chiral molecules by means of calculations based on atom-atom intermolecular potentials that are widely used in quantum chemistry, molecular dynamics calculations, etc. The twisting power calculations are performed in the most minimalistic way but retain the ability to predict the twisting power of real chiral molecules. It is shown that the choice of chiral molecule environment (models for nematic molecules) and averaging of torque exerted on nematic molecules over possible orientations of chiral molecules are crucial for predicting a correct twisting power. The values of twisting power are compared to experimental data for binaphthol molecules and are in good agreement with them. We also consider other chiral "components" of intermolecular interactions (forces, and energies) and discuss their applicability as chirality measures of the chiral molecule. The use of the calculated values as chirality measures of chiral molecules is also considered.   

Manipulating the Resistivity of Molecular Liquid Crystals

Numerous applications of molecular liquid crystals including displays and tunable electro-optical components (filters, waveplates, waveguides, light modulators, etc.) rely on high resistivity mesogenic materials. There are also applications such as privacy windows and light shutters taking advantage of the dynamic light scattering effect where ions are required for proper performance. Therefore, the control over the resistivity of molecular liquid crystals is of utmost importance. While it is relatively easy to change the resistivity of molecular liquid crystals by 2-3 times, a change of several orders of magnitude in the resistivity is not a trivial task. In our research, we discuss the possibility to control (either increase or decrease) the resistivity of molecular liquid crystals by several (2-4) orders of magnitude using nanomaterials. The adsorption effect of nanoparticles can increase or decrease the ion contamination, therefore the resistivity. The use of nano-dopants may improve the performance of liquid crystal devices including LCDs, electrically controlled lenses, and tunable optical elements such as smart windows and microwave devices.  We analyze how the type of nanoparticles, their concentration, their size, and the level of ionic contamination affect the electrical resistivity of molecular liquid crystals in a desirable way.   

QM/MM Molecular Dynamics Run within Quantum and Tensor-Based Algorithms towards Topologically Inspired, Accurate Protein Folding

The most accurate approaches to protein folding require molecular dynamics (MD). However, these methods are both slow and extensively thorough, requiring exacting understanding of the solvent environment and its minute details along with a thorough understanding of the MD software itself to add these parts effectively. We aim to improve upon these methods through the investigation of quantum algorithms for MD approaches, as well as topological mathematics on top of these methodologies for further decreases in computational complexity.

Our approach is three-pronged: 

Tailoring the Photoresponse of Photosynthetic Cyanobacteria (Synechococcus elongatus)

Photosynthesis, especially by Synechococcus elongatus bacteria found in light-exposed freshwater, plays a crucial role in global carbon fixation and bioenergy production. These cyanobacteria, also known as blue-green algae, mainly absorb light in the blue ( 420-450nm) and red (640-680nm) regions but have a “green gap” in the region(500-550nm) of the spectrum. Despite this, their auxiliary phycobilisome pigments (phycoerythrin 570nm, phycocyanin 620nm, allophycocyanin 650nm) absorb light at different wavelengths of the green region making it efficient for photosynthesis. The distribution and dynamics of energy transfer components in cyanobacterial thylakoid membranes govern the regulation of electron transfer pathways in nature, this attracted attention to the exact energy transfer mechanism. To improve our understanding of the mechanism, there have been attempts to genetically modify these pigments. To circumvent this, we explored the binding of these pigments with specific peptides which quenched and enhanced the photo response of pigments by increasing quantum yield using simple extraction, and quantification with response to absorption and emission phenomenon by spectrophysical techniques of nanoscience without genetic alterations. We developed new methods to influence cyanobacteria photosynthesis, offering insights into energy transfer pathways contributing to a sustainable environment and combating global warming.   

Similarity analysis for Serotonin Receptor Networks

Serotonin 5-HT receptors are pivotal for regulating virtually all cerebral functions. Imbalances in serotonin levels within the organism are linked to behavioral and neurological disorders. Understanding how 5-HT receptors contribute to normal brain function is paramount in developing more accurate treatments for conditions such as depression. This study investigates the similarity of complex networks involving 5-HT receptors and serotonin transporters, a vital protein in managing psychiatric disorders. We applied the Jaccard similarity coefficient to measure the similarity of complex networks that map 5-HT receptors and Serotonin Transporters. Our results suggest that the similarity between the networks of 5-HT receptors and serotonin transporters may support the development of methods and drugs capable of reversing pathologies associated with serotonin imbalance in the human body.   

Phosphorus-containing Complex Chalcogenide Glasses: Synthesis and Characterization

Chalcogenide glasses play a crucial role in modern technologies due to their diverse advantageous features, including infrared transparency, large refractive indices, large optical nonlinearity, and phase change memory effect when exposed to elevated temperatures, pressures, electric shock, or photo exposure. The structural, electrical, thermal, and optical properties of complex chalcogenide glasses (Ge-Ga-P-Sb-Se-Te) with varying P concentrations (1-9 at. %) were studied. The X-Ray Powder Diffraction Method was used to confirm the amorphous nature of the prepared bulk samples. Differential Scanning Calorimetry (DSC) was utilized to investigate their glass transition and crystallization behavior. DSC scans were performed at different heating/cooling rates as well as at isothermal conditions to investigate crystallization kinetics in the supercooled liquid regime. Optical spectroscopy revealed that the produced glasses exhibit transparency across the 1-23 µm range and a decreasing band gap as P content is increased in the composition. These characteristics make P-containing complex chalcogenides well-suited for telecommunications and optoelectronic applications.   

Eco-friendly and Bioderived, Biodegradable Polymer for 2D Device Fabrication

Our pursuit of two-dimensional (2D) materials, like graphene and molybdenum disulfide (MoS₂), is driven by their exceptional optical and electronic properties. Often 2D device fabrication requires transferring materials grown via chemical vapor deposition (CVD) onto a target substrate, assisted by polymers. This study pioneers a bio-derived, biodegradable polymer for 2D materials transfer. Optimizing various parameters, we successfully fabricated graphene and MoS₂ based 2D devices using poly angelica lactone. Our polymer was thoroughly characterized using FTIR, GPC, and DSC. We employed SEM and Raman spectroscopy to ensure the quality of transferred materials. Notably, for graphene we achieved strain and carrier concentration level below 0.5% and 0.5 x 10¹² cm^-2 respectively. Disorder in graphene monolayers was quantified by Raman Spectroscopy, revealing our polymer's superiority to conventional and Soxhlet extractor-based methods. In addition, our biodegradable polymer underwent rigorous biodegradability testing, demonstrating efficient removal from graphene films with yeast. This eco-friendly approach opens a significant stride towards sustainable 2D device fabrication.   

Probing ultrafast plasmon-molecule interactions using surface-enhanced femtosecond stimulated Raman spectroscopy

Plasmonic nanomaterials can concentrate electromagnetic fields into nanoscale volumes known as hotspots. These highly energetic hotspot regions can impact a nearby molecule by altering its potential energy surface through energy or electron transfer processes. These processes happen at the sub picosecond timescale of plasmon decay making it difficult to probe the underlying mechanism involved in plasmon-molecule interaction. The lack of mechanistic understanding hinders the optimization of plasmonic nanomaterials on an industrially relevant scale. This work focuses on the development of a time-resolved surface-enhanced femtosecond stimulated Raman spectroscopy (SE-FSRS) technique, with the aim of learning about the plasmon decay process through its impact on the nearby adsorbate molecule. SE-FSRS can take molecular snapshots in the form of vibrational signatures revealing structural changes that the molecules undergo during the process of plasmon decay in femtosecond timescale. We have developed a three-pulse SE-FSRS system and acquired vibrational spectra of molecules evolving in plasmonic hotspots on ultrafast timescales. This approach will allow for a greater understanding of how photoexcited plasmons impact molecular potential energy landscapes on femtosecond timescales, guiding insights into the use of plasmonic materials for catalysis, photothermal therapy, and sensing applications.   

Magneto-optical study of the Effects of Annealing on Superconducting Properties of Niobium Single Crystals

Niobium has a high affinity for hydrogen and can absorb it from solvents and even humid air. Upon cooling below 180 K, niobium hydrides precipitate. These precipitates form defects that decrease the performance of Nb-based devices used for applications in quantum computing and accelerators. In RF cavities, they lead to the so-called Q-disease. Vacuum annealing above 1073 K will remove hydrogen. Here, we use magneto-optical imaging to obtain spatially resolved profiles of the magnetic induction B(r) across the sample surface and deduce the effective critical current density. Although large (tens of micrometers) hydrides no longer appear after annealing at 1073 K when cooling below 180 K, the pinning remains elevated even after 1673 K annealing, implying that some, possibly nanoscale, hydrides still remain in the samples. Only bringing the sample close to the melting point significantly reduces pinning.   

Cuprate coexistence under the superconductive dome

Under the superconductive dome of cuprates, the nature of coexistence with pseudogap order is reassessed.  Experimental data from the literature are analyzed within two threads: the vital superfluid density and the essential momentum dependence, the latter due to the d-wave nature of superconductivity.  For severe underdoping, this analysis suggests superconductivity condenses on the finite density-of-states of the pseudogap at the Fermi level.  For intermediate doping, it suggests nucleation of a coherent phase that embodies both superconductive and pseudogap orders which are not separated in momentum-space.  Such a coherent-phase nucleation resolves eight mysteries in the literature and indicates potential consistency with a theory of nanoscale stripes.     

Phonon-Mediated Superconductivity near the Lattice Instability in Hole-Doped Hydrogenated Monolayer Hexagonal Boron Nitride

Employing the density-functional theory with local density approximation, we show that the fully hydrogenated monolayer-hexagonal boron nitride H₂BN has a direct-band gap of 2.96 eV in the blue-light region while the pristine h-BN has a wider indirect-band gap of 4.78 eV. The hole-doped H₂BN is stable at low carrier density (n) but becomes dynamically unstable at higher n. We predict that it is a phonon-mediated superconductor with a transition temperature (T_c) which can reach ~31 K at n of 1.5x10¹⁴ holes cm^-2 near the lattice instability. The T_c could be enhanced up to ~82 K by applying a biaxial tensile strain at 6% along with doping at n of 3.4x10¹⁴ holes cm^-2 close to a new lattice instability.   

Quantum Hall effect systems of electrons with an internal source of anisotropy

Two-dimensional system of electrons can now be easily created in semiconductor heterojunctions at the interface between the two materials. Application of a strong perpendicular magnetic under specific quantum conditions leads to the creation of a novel electronic state of matter known as the quantum Hall state of the electrons. The most robust of such states representing the integer and/or fractional quantum Hall phases show the expected characteristic magnetoresistance for such systems. However, signs of anisotropic patterns and features in magneto-transport properties have been observed for a few other peculiar cases. The origin of such anisotropic patterns may have various mechanisms. It may also be due the specific internal details of the system and material such as the isotropic or anisotropic nature of the effective mass of electrons, the nature of the host substrate parameters, the nature of the interaction potentials, as well as other subtler effects. The interplay between all these factors can lead to many outcomes. In this work we consider small quantum Hall states of electrons at an even-denominator filling factor of the lowest Landau level and study the appearance of anisotropic patterns as a result of an internal anisotropy in the interaction potential.

    

First-principle Study of the 4d Transitional Metal Doped Topological Insulator

We study the electronic and magnetic properties of 4d transition-metal (TM) doped Bi₂Se_3. Doping was done separately at 4.0% and 16.6% concentrations using the atomic sphere approximation and the full-potential method to study the magnetic properties as a function of doping. Especially at 4.0% doping of Nb (1.77 µB/atom), Mo (2.98 µB/atom), Tc (3.50 µB/atom), and Ru (0.92 µB/atom), respectively, resulted in finite local magnetic moments. In addition to the magnetic nature of the doped alloys, Nb, Tc, and Ru-doped Bi₂Se₃ became half-metallic. The magnetism in these alloys arises from indirect interaction between magnetic moments mediated by free carriers within the layer and via Se atoms between layers. Using the Heisenberg model, we have observed significant effects of spin-orbit interaction on the exchange-coupling parameters of Nb and Ru-doped alloys. In contrast, at higher doping (16.6%), Bi₂Se₃ exhibited a metallic and non-magnetic nature, as demonstrated by the band structures and the density of states of the doped alloys.   

Predicting Superconductivity via Machine Learning Methods

Superconducting materials present the rare opportunity to revolutionize virtually every aspect of human life, including improved transportation, more efficient energy transfer, and faster computers. With the help of Artificial Intelligence (AI) and Machine Learning (ML) models, we can study what properties influence the superconductivity of a compound and predict what experimental and theoretical compounds will perform as efficient superconductors. Our control substance is the popular YBCO compound. Using experimental data gathered in Adelphi's first comprehensive materials science endeavor, with the aid of encoded, theoretical deep learning models, our project seeks to investigate the Meissner Effect. Our study tackles the question of what makes a superconductor a superconductor, with the ultimate goal of discovering additional high temperature superconductors to be synthesized in the lab.   

Direct growth of graphene on CoCrMo alloy by double-tube chemical vapor deposition

Graphene has attracted significant interest due to its unique properties and potential applications. In particular, graphene has sparked much attention in biomedical field due to its outstanding biocompatibility. Here we report on optimized double-tube chemical vapor deposition (DT-CVD) technique that was employed to facilitate the direct controlled growth of graphene on a cobalt-chromium-molybdenum (CoCrMo) alloy surface and tested its wear and corrosion resistance. In this study, we also explore the propose our hypothesis for the underlying growth mechanism. The number of layers and crystallinity of graphene grown on a CoCrMo alloy substrates were confirmed by Raman spectroscopy. The effect of the DT-CVD process on the microstructure and the morphology of the CoCrMo alloy surface was investigated by atomic force microscopy (AFM), scanning electron microscopy (SEM), X-ray photoelectron microscope (XPS), and X-ray diffraction (XRD). In addition, we verified the mechanical toughness of as-grown graphene on CoCrMo. Our new results demonstrate an alternative and potentially improved coating technology for graphene’s implementation into medical fields such as coating for devices, probes and implants.   

A Simple Method of Growth and Transfer of Bilayer Graphene / Few-Layer Boron Nitride Suspended Heterostructures onto Large 200 µm Etched in Silicon "Trenches".

Two-dimensional heterostructures remain at the forefront of contemporary research. Bilayer graphene (BLGr) and few-layer boron nitride (FLBN) have been studied extensively for their unique electronic and mechanical properties and facile synthesis. Their similar hexagonal crystal structures allow for optimal stacking. Adding more layers has been shown to alter material properties. While others have suspended 2D heterostructures, membranes are often ruptured due to surface tension, limiting their size and yield. In this study, we demonstrate the fabrication of heterostructures using chemical vapor deposition (CVD) grown BLGr and FLBN and a direct transfer method to create suspended stacks. BLGr was transferred directly onto FLBN substrate while overlayed with polymethyl methacrylate (PMMA), and the entire stack was then transferred onto 200 µm wide trenches. Noteworthy is the use of polydimethylsiloxane (PDMS) block assistance to prevent stress-induced rupture during the transfer process, which was very effective. Raman spectroscopy and scanning electron microscopy (SEM) were used to study quality and integrity of the resulting suspended heterostructure. To the best of our knowledge, this is the first demonstration of large-scale suspended heterostructures reported to date.   

Carbon nanostructures as potential candidate for Electromagnetic Interference Shielding in Ka- band of microwave frequency

Carbon nanostructures have found wide-ranging applications in various industries due to their lightweight, and excellent fatigue resistance. This study explores the electromagnetic interference (EMI) shielding efficiency of unidirectional carbon fiber reinforced polymers (CFRPs), which are known for their anisotropic electrical properties. The study measured the EMI shielding efficiency for the frequency range of 26 GHz to 40 GHz in both the plane and perpendicular directions of the CFRP, highlighting how it impacted the samples. Interestingly, the efficiency increased when the CFRP was combined with multiwall carbon nanotubes, placed one inch apart in patterns, providing additional localized sites for electron hopping. This resulted in a significant increase in EMI shielding efficiency.   

Atomic scale analysis of Kagome Mn 3 Ge surfaces: effect of defects on their stability and magnetic arrangement

Mn3Ge crystallizes in a hexagonal phase that belongs to the spatial group P63/mmc. It is a non-collinear antiferromagnetic material with a triangle-like magnetic arrangement. It is also a topological material that has attracted the attention of the scientific community. In order to reach applications in real devices, surface effects must be carefully analyzed at an atomic scale. Upon surface relaxation, the first surface layer gets shifted in the c-direction, contracting the interlayer distance with the second monolayer, which increases the magnetic moment by 20% while maintaining the Kagome ordering. The pristine surface is thermodynamically stable. Upon creating vacancies, the stability is diminished. In the case of Ge vacancies, the magnetic moment’s ordering remains; however, it is disrupted if Mn vacancies are induced. This is an expected result since Mn vacancies break the triangle like magnetic arrangement that is the fingerprint of Kagome materials. Our results demonstrate that Kagome Mn3Ge surfaces are robust and keep their magnetic properties even with Ge Vacancies. Also, our stability analysis points to a low probability of intrinsic defects or low index reconstructions, making it ideal to look for exchange-biased devices with other ferromagnetic Kagome materials.

Acknowledgments

We thank the projects DGAPA-UNAM IG101124 and IA100624. The calculations were carried out at the supercomputing center UNAM project LANCAD-UNAM-DGTIC-368 and -422, LNS-BUAP project 202201042N, and THUBAT KAAL IPICYT project TKII-JGSA001.   

A Spin Field Effect Transistor Based on a Strained Two-Dimensional Weyl Semimetal

Spin field effect transistors (SpinFET) are an iconic device in spintronics and typically function by employing a gate-induced electric field to tune the spin-orbit interaction in a semiconductor channel flanked by ferromagnetic source and drain contacts. We have proposed and analyzed a very different type of SpinEFT employing a channel made of a Weyl semimetal integrated with a piezoelectric layer where the gate voltage strains the channel and alters the energy dispersion relations. This modifies the interference between the two eigenspinors in the channel, leading to a modulation of the source to drain conductance The channel conductance shows oscillatory dependence on the channel length at zero gate voltage, which is a unique feature that can be harnessed to implement a complementary device like CMOS by connecting two SpinFETs with two different channel lengths in series. Such a device is also very energy-efficient.   

Magnetic field driven dynamics in twisted bilayer artificial spin ice at superlattice angles

Geometrical designs of interacting nanomagnets have been studied extensively in

the form of two-dimensional arrays called artificial spin ice. These systems are usually

designed to create geometrical frustration and are of interest for the unusual and

often surprising phenomena that can emerge. Advanced lithographic and element

growth techniques have enabled the realization of complex designs that can involve

elements arranged in three dimensions. Using numerical simulations employing the

dumbbell approximation, we examine possible magnetic behaviours for bilayer artificial

spin ice (BASI) in which the individual layers are rotated with respect to

one another. The goal is to understand how magnetization dynamics are affected

by long-range dipolar coupling that can be modified by varying the layer separation

and layer alignment through rotation. We consider bilayers where the layers are

both either square or pinwheel arrangements of islands. Magnetic reversal processes

are studied and discussed in terms of domain and domain wall configurations of the

magnetic islands. Unusual magnetic ordering is predicted for special angles which

define lateral spin superlattices for the bilayer systems.   

Future Directions in QuantumGEP Research and Development

QuantumGEP (*) is a free and open source computer program for the generation of quantum circuits, circuits that in turn can generate the quantum mechanical ground state of a given molecular or solid-state Hamiltonian. This talk will discuss a roadmap for improving the convergence of the current implementation (**) by adding a side agent, following the theory behind reinforcement learning with either Q-Learning or prioritized sweeping. Moreover, this talk will discuss plans for better quantum hardware simulation by (i) considering error mitigation in QuantumGEP, and (ii) simulating noisy gates by using a density matrix evaluator instead of a vector-based one.

(*) https://dl.acm.org/doi/10.1145/3617691

(**) https://code.ornl.gov/gonzalo_3/evendim   

Quantum Classifier with Iterative Re-Uploading for Universal Classification: Performance Evaluation and Insights

In this work, we leverage the capabilities of an existing quantum classifier known for its ability to perform multi-class classification of multi-dimensional data using a few qubits. Our approach involves the iterative re-uploading of classical data into the quantum circuit, punctuated with parametrized rotation gates acting as processing units. We evaluated our implementation across various classification tasks of differing complexity levels. In our experiments, we employed several minimization methods, including SLSQP, CG, and Nelder-Mead, to observe variations in accuracy for each problem. We also experimented with random datasets in addition to fixed ones and introduced an additional cost function, trace distance. Furthermore, we added a ‘line’ problem. For the linear problem, we achieved high accuracy (around 0.92) for the fidelity cost function using both random and fixed datasets with SLSQP and CG methods. For the non-linear classification problem, we observed the highest accuracy for fidelity and fixed dataset (0.97). We also achieved good accuracy (up to 0.91) for trace distance for linear problems using the SLSQP method and random data set. Remarkably, all these accuracies were achieved with only 50 training data points.   

Coherency and Ant-Crossing Low-lying Levels in 12C Nucleus

The 3-alpha phenomenological model describes the structure of the carbon-12 nucleus as a cluster of three alpha particles. This model incorporates both alpha-alpha interactions and a three-body force. To determine the parameters of the three-body potential, we utilize data from ¹²C, while ensuring that the pair potential accurately reproduces alpha-alpha scattering data.

 Alternatively, the mass-energy compensation (MEC) effect can be employed to approximate the influence of the three-body potential by adjusting the effective mass of the alpha particle. We demonstrate the MEC effect for the 3-alpha ground state by numerically solving the differential Faddeev equation, in which the alpha-alpha interaction is described using the Ali-Bodmer potential. We assess the effective masses of alpha particles for the ground state, as well as the excited 0⁺ and bound 2⁺ states. We observe a coupling (coherency) between the ground and first excited 0⁺ states, as indicated by an anti-crossing of their energy levels in the energy-mass coordinates.   

How Bohr Specifically Adapted the Psychologist William James's "Complementarity" for Physics Many Years After Bohr First Read James's "Complementarity": Setting the Historical Record Straight in Order That James's Complementarity Can Be Properly Evaluated on Its Own Merits for Quantum Measurement

It is important to see James's original complementarity in 1890 independently of Bohr's discussions on complementarity in order that James's conception can be properly evaluated as the correct model for quantum measurement. On the basis of new evidence and a deeper analysis of previous evidence presented here, it is very reasonable to conclude that Bohr read James's complementarity between approximately 1908 and 1912. How Bohr specifically adapted James's complementarity to physics is presented. It is also made clear here that Bohr was aware that he had a choice to adopt complementarity for physics along the lines of James's complementarity and that he rejected this possibility. Instead, in his complementarity for physics, Bohr adopted a very different approach fundamentally based on the necessity of a physical interaction between a physical system and a physical measuring apparatus with an uncontrolled aspect to obtain a specific measurement result. Bohr's detour with the necessity of a physical interaction in the measuring process with an uncontrolled aspect in quantum mechanics has distracted attention away from the possible significance of James's original complementarity in psychology to quantum measurement, including its evaluation on its own merits as to whether it provides the correct conceptual framework for this measurement.   

Decoupling contributions to spontaneous polarization in Hybrid formate perovskites

The quest for flexible, lead-free, low temperature synthesizable alternatives to the tradition ferroelectric oxides has instigated the search for ferroelectrics in metal-organic frameworks (MOFs). One of the sub-classes of MOFs, the hybrid formate perovskites (HFPs), habors materials which have been proven experimentally and computationally to be ferroelectric. However, the values of polarization recorded so far for HFPs are rather low, like ten orders of magnitude lower than those of traditional perovskite oxides. Therefore, it is essential to dissect the polarization contributions from the structural entities of HFPs, majorly the framework and molecules, in an attempt to identify the major driver of ferroelectricity. Thus, in this work, we have identified contributions to the total spontaneous polarization from seven ferroelectric members of hybrid formate perovskites.   

Studying the effectiveness of MnO2 in super capacitor applications in an electrochemical cell with varying amounts of carbon nanotubes introduced during the synthesis procedure

For many years now, investigations in the field of condensed matter physics have often been targeted towards energy storage technologies, such as batteries and in the case of this work, super capacitors. In this line of inquiry there has been a distinct interest in finding affordable materials for use in energy storage devices. Materials like Manganese, which fit the bill for affordability and availability is the focus of our study in the form of MnO2. The focus of this work is to study the behavior that additives, such as carbon nanotubes, can have on the specific capacitance of MnO2 when used as an electrode in an electrochemical cell and mark the improvements to specific capacitance gained by the introduction of varying concentrations of carbon nanotubes into the synthesis procedure   

Impact of Long-term cycling (>7500 cycles) on laminar Li4Ti5O12 (LTO) Anode for its Application in Sodium-ion Batteries.

Sodium-ion batteries (SIBs) have emerged as a promising alternative to lithium-ion batteries (LIBs) for large-scale energy storage applications, primarily due to the abundance of sodium resources and their electrochemical performance similar to LIBs. In this study, LTO is synthesized using a surfactant-free solution process route and followed by its investigation under its long-term cycling behaviour to evaluate its suitability as an anode in SIBs. The synthesized LTO exhibited a cubic phase with an Fd3m space group [1], as Powder X-ray diffraction (PXRD) was revealed using Rigaku Ultima. The calculated band gap was approximately 3.87 eV. Cyclic voltammogram (CV) tests conducted under a lower scan rate of 0.1 mV/s showed two anodic peaks at 0.903 and 1.091 V and one cathodic peak at 0.693 V, indicating a three-phase Na⁺ storage mechanism in LTO [2]. The LTO electrode was cycled under a potential window of 3-0.2 V at a 0.1 C rate, delivering an initial discharge capacity of approximately 138.9 mAh/g at an intercalation potential of around 0.709 V. Under periodic rate capability (RC), the test cell delivered a 124.8 mAh/g capacity at a 0.2 C rate. The cell was cycled up to 10 C, and even after subsequent cycling, it could still deliver 137.5 mAh/g (0.1 C repeat), representing only a 1.079 % decrease in capacity. As part of the study, the LTO electrode underwent a galvanostatic charge-discharge (GCD) test for over 7500 cycles at a 5 C rate. During the first cycle, the cell delivered a capacity of 45.5 mAh/g, and at the end, it gave 40.65 mAh/g, with a capacity retention (CR) of 89.3 %. This suggests that the laminar morphology of the LTO anode, due to continuous cycling under high-stress conditions, leads to the formation of gaps between the sheets, which makes it easier for Na⁺ to interact with the material. The cycle count results are the highest reported cycle count compared to existing literature.

Moreover, ex-situ transmission electron microscopy (TEM) was conducted to understand sodium intercalation's phase boundary and any changes in the existing morphology. Additionally, time-of-flight secondary ion mass spectrometry (TOFSIMS) and X-ray photoelectron spectroscopy (XPS) were performed to study the cycled electrode's top surface at the charged and discharged state, providing valuable insights into the electrode's performance.   

Design of Tunneling diodes with 2D Insulators for Switching at THz and Beyond

The key components of a conventional rectifying circuit are semiconductor PN junction diodes. The electron transfers across a PN junction via diffusion with a typical time interval of 1-100ns. It is applicable for processing the signal at radio frequencies. However, for the signal processing at THz and higher, the time interval for electron to transmit across a junction must be faster than 1ps which can be overcome by tunneling. Metal/insulator/metal (MIM) junction is a simple and yet very effective structure for a tunneling diode. The tunneling time is defined by barrier profile U_x and bias, reaching femtosecond.

The conventional MIM diodes use bulk materials as the insulators in which the thickness cannot be fine-tuned and the surface defects negatively affect tunneling efficiency. In this work, we applied density function theory (DFT) method to study MIM junctions with two-dimensional (2D) materials as the insulators. We have studied the band structures of 1-3 layers of TiO₂, TaO₂ and SnO₂ which can be obtained by oxidizing the corresponding 2D metal-sulfur materials. The Au/monolayer TiO₂/Al junction was found to have the best rectifying performance. There is not a significant effect for up to ±0.6% of strain. In addition, the simulated current-voltage characteristics were fed through a rectifier in Pspice which showed excellent signal rectifying for frequencies at THz and beyond. Such a diode is very attractive for THz medical devices and rectenna solar cells.   

On a density criterion for universal interlaced unitary photonic architectures

Programmable photonic integrated circuits represent an emerging technology for light-based information processing at high speeds and low power consumption, providing a flexible and reconfigurable platform to perform multiple tasks, thereby holding great promise for revolutionizing future optical networks. Indeed, matrix-vector multiplication is one of the most fundamental information-processing operations. Unitary matrices are particularly interesting since they describe lossless processes and serve as the building blocks of more general operations.

 

This talk focuses on a universal unitary architecture based on layers of diagonal matrices and specific interlacing unitary matrices. Numerical evidence brings evidence that such an interlacing matrix can have a random pattern as long as it fulfills the required density properties. In this regard, Haar-generated random matrices are suitable candidates that lead to suitable interlacing matrices in most outcomes. To distinguish the efficacy of the random matrix in question, a density criterion has been introduced as an a priori condition to ensure the validity of the interlacing matrix in question, reducing the computational workload due to heavy numerical optimization to classify them.

 

This approach is beneficial for two reasons. Firstly, it allows for more possibilities for further interlacing matrices beyond particular waveguide arrays. Secondly, the random nature of the interlacing matrix provides resilience due to manufacturing defects. These results are illustrated by means of some realistic photonic realizable examples.   

The Influence of Particle Size and Volume Fraction on Hybrid Ferrite Microwave Absorbers

As 5G technology becomes ubiquitous and the internet of things expands, sources of microwave EMI are rapidly increasing, and the threat of coupling EM energy into susceptible electronic circuits.  Mitigating this threat requires compact, lightweight broadband absorbers to protect sensitive electronics.  Magnetite, MnZn ferrite, and NiZn ferrite, alone and in conjunction, have the potential to meet the energy density and EM attenuation performance needs.  However, optimizing the absorption loss requires improved understanding of the role of particle size and volume fraction on the complex permittivity and permeability of these materials.  This presentation discusses experimental investigation of the particle size and volume fraction on the absorption losses of these ferrites.  Complex permeability and permittivity measurements were conducted to identify the absorption mechanisms.  We present a possible explanation of these results in the context of Snoek’s limit and the Landau-Lifshitz theory of permeability.

This work was supported by the Laboratory Directed Research and Development program at Sandia National Laboratories, a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.   

Plasmonic Effects of ZnO-coated Ag Nanowire Top Electrodes on Photovoltaic Performance in NiO/ZnO-Heterojunctions

Transparent photovoltaic (TPV) devices with Ag nanowire top electrodes can be installed in windows, producing electricity from solar radiation while remaining invisible to human eyes. In this work, we pay special attention to the contributions of surface plasmon (SP) excitation in ZnO-coated Ag nanowires (AgNWs) to the photovoltaic performance of NiO/ZnO TPV devices. The optical measurements and calculations showed a localized SP excitation in AgNWs. The spatial redistribution and transport of photo-generated charge carriers were analyzed using Kelvin probe force microscopy and current-sensing atomic force microscopy. The results revealed a strong dependence on both the polarization and the wavelength of the incident light. The nanoscopic characterizations showed the beneficial roles of ZnO-AgNWs top electrodes in the collection and generation of photo-carriers in TPV devices.   

A Breakthrough in Inverse Design for Materials Discovery through Advanced Generative Models

In the field of materials science, the pursuit of discovering innovative materials with specific attributes has been markedly expedited through the application of inverse design methodologies. Traditional approaches, reliant on empirical trial-and-error methods employing density functional theory (DFT) or machine learning in forward modeling, are now being surpassed by a groundbreaking generative model. This model, founded on advanced Generative Adversarial Network (GAN) technology, excels not only in introducing but also in optimizing crystal structures based on desired properties. Addressing the intricate challenge of encoding crystals within a latent space, the model employs a pioneering invertible representation technique. The efficacy of this model is rigorously validated in the binary crystal system under predefined conditions, showcasing the generation of diverse crystal structures that precisely fulfill desired property requirements. The study signifies substantial progress in the domain of inverse design through the integration of an enhanced GAN iteration and a distinctive crystal representation approach. This marks a significant stride forward, promising transformative advancements in the realm of materials science.   

Efficient Brain-Inspired Control Strategies: Cloud-Based Online Supervised Learning for Spiking Neural Networks in Dynamical Systems

This study addresses the challenges of implementing control policies in dynamical systems using brain-inspired computing tools, focusing on efficiency, reliability, and robustness. Spiking Neural Networks (SNNs), inspired by biological neural circuits, are known for their efficiency and scalability. However, the lack of efficient local learning rules hinders their application in online learning for dynamical systems control. The study proposes a cloud-based supervised online training strategy for recurrent SNNs in the control of dynamical systems. SNN communicates with a cloud-based model-based control system, updating its weights using a biologically plausible learning strategy until a desired threshold is reached. Notably, SNN learns the control signal independently of underlying dynamics and implemented controllers, making it versatile for arbitrary plants and control methods. Simulation results demonstrate acceptable performance in terms of network convergence and control accuracy. The proposed strategy, with only five neurons, achieves control tasks with constrained weight updates, using approximately 5% of possible spikes compared to traditional neural networks, without a significant impact on control accuracy.   

Adversarial attacks on hybrid classical-quantum Deep Learning models for Histopathological Cancer Detection

We present an effective application of quantum machine learning in histopathological cancer detection. The study here emphasizes two primary applications of hybrid classical-quantum Deep Learning models. The first application is to build a classification model for histopathological cancer detection using the quantum transfer learning strategy. The second application is to test the performance of this model for various adversarial attacks. Rather than using a single transfer learning model, the hybrid classical-quantum models are tested using multiple transfer learning models, especially ResNet18, VGG-16, Inception-v3, and AlexNet as feature extractors and integrate it with several quantum circuit-based variational quantum circuits (VQC) with high expressibility. As a result, we provide a comparative analysis of classical models and hybrid classical-quantum transfer learning models for histopathological cancer detection under several adversarial attacks. We compared the performance accuracy of the classical model with the hybrid classical-quantum model using pennylane default quantum simulator. We also observed that for histopathological cancer detection under several adversarial attacks, Hybrid Classical-Quantum (HCQ) models provided better accuracy than classical image classification models.   

Evaluating and Enhancing Image Caption Generation: A Comparative Study of LSTM and GRU Models with Object and Feature Recognition Strategies

The combination of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) has significantly transformed the domain of image caption generation in recent times. The objective of this study is to assess the effectiveness of different combinations of Convolutional Neural Networks (CNNs) and language models, such as Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU), in producing detailed and precise captions for images. The results of our study demonstrate that models based on Long Short-Term Memory (LSTM) show a higher level of performance in terms of the quality of captions. Conversely, GRU models showcase the benefit of decreased computing time. In order to improve the quality of the captions produced, we suggest implementing a three-pronged approach. Initially, the present framework might be enhanced by integrating object detection techniques to accurately recognise and isolate distinct things within an image. Furthermore, the process of feature extraction could be enhanced by incorporating attributes such as colour, position, and other prominent qualities of each identified object. Furthermore, sophisticated language models can be utilised to effortlessly connect these characteristics and entities, thereby generating captions that are not just descriptive but also contextually pertinent. This research aims to establish a foundation for the development of image captioning systems that are more sophisticated and effective. We emphasise the trade-offs between LSTM and GRU models and provide a comprehensive strategy for future research to enhance the quality of captions. This has major implications for various domains, including computer vision and natural language processing.   

Narrowband Surface Grating (NSG) Mirrors for Wavelength and Polarization Selection, Locking, and Tuning of Vertical Cavity Surface Emitting Lasers

VCSELs (vertical cavity surface emitting lasers) have many advantages over EELs (edge-emitting lasers), such as single-longitudinal mode operation, circular beam, better beam quality (low divergence), low threshold, on-wafer testing and packaging, easiness in making laser arrays, etc. However, to have high output power while keeping all those inherent advantages is a challenge for VCSELs. Furthermore, both wavelength and polarization selection and locking for VCSELs (and any laser) are crucial for many applications, for instance, applications that require highly coherent laser beams. VECSELs (Vertical Extended Cavity Surface Emitting Lasers) can be one solution to achieve high output power while keeping all the inherent advantages of the VCSELs. However, the wavelength and polarization selection and locking could be even more challenging for VECSLEs compared to VCSELs. We propose to use a narrow band surface grating waveguide resonant filter (NSG) as an external cavity feedback mirror to select and lock both the wavelength and polarization of the VCSELs.   

Electro - optical modulator based on exciton-polaritons

One of the main issues in quantum computing is absence of scalable quantum communication. 

We propose a novel approach, which utilizes properties of exciton-polaritons. Due to an extremely small effective mass and the dual quantum nature of polaritons they are extremely sensitive to electric fields and can be easily controlled by them. In the proposed design an optical signal is dragged from the take-in point to read-out point via the channel using exciton polaritons that are generated in the adjacent layer. 

 

Via numerical simulations we showed that for the purpose of getting a strong read-out signal, a wedge-shaped potential should be applied to the channel. Then we apply pulsed voltage generating drag force. This resulted in formation of the polariton pulses propagating in the channel and reaching the optical read-out area in the device. If multiple voltage pulses are applied, then multiple polariton pulses propagated in the system. To obtain same response to identical drag pulses, a channel needs to undergo relaxation and return to the initial state between the pulses. When time between two drag pulses is shorter than critical, the response pulses will overlap and become indistinguishable. Even though this imposes a limitation on the operational frequency of the devise, the frequency is measured in GHz, which coincides with operation frequency of quantum computers. Therefore, the system performs conversion of input electric signals into optical signals and back, maintaining the desired operation frequency.    

Python GPU Accelerated Geometric Gamma Index Calculation

The gamma index is a widely adopted tool for dose distribution comparison and quality assurance in radiotherapy. The algorithm for calculating this index searches for the closest Euclidean distance, producing an easy-to-use metric for comparing dose distributions. However, this becomes computationally expensive for high-resolution images. Implementing gamma index algorithms on graphical processing units (GPUs) using C++ and MATLAB can speed up this calculation, but these existing methods are less user-friendly and modifiable, and in the case of MATLAB, expensive. This study designed a novel and efficient GPU-accelerated gamma index framework that is built on Python CUDA and Numba instead of C++. An interpolation-free geometric calculation was implemented on an NVIDIA GTX 1080 GPU with 2560 CUDA cores. The technique identifies the closest geometric distance between two distributions that can be calculated via matrix operations. The technique was modified to be GPU friendly and 3 methods were compared: non-accelerated, CUDA JIT-complied, and custom CUDA Kernel. Low-, medium-, and high-resolution image datasets were generated for benchmarking. The CUDA kernel achieved calculation speeds under 2 seconds for high-resolution 2D distributions, presenting an easy-to-modify alternative to existing GPU acceleration methods.   

Kitchen Table Astronauts

This project involves developing digital science lessons for hands-on experiments that showcase a wide range of applications for the physical sciences, from the science of the kitchen to the science of space. We will do this by designing activities that use food to demonstrate different principles from chemistry and physics aligned with the Next Generation Science Standards (NGSS) for middle school. The activities will also include information on how these principles are important in NASA's explorations of space. We have produced videos demonstrating the activity and giving background information about the science involved. Teacher feedback on the activity and potential for student learning will inform improvements in the next iteration of the curriculum.   

Experiences of Teaching and Learning of Physics and Astronomy Courses at Community Colleges: Challenges and Opportunities in Fully Online, Hybrid, and In-Person Methods

A significant number of students in community colleges may be nontraditional, in addition to being first-generation college students. Affordability and commute can play vital roles in students' decision to take courses at community colleges. Since COVID-19, fully online and hybrid courses have become more popular at community colleges. In this presentation, I will also share my experiences and data on the similarities and differences between three teaching modes (in-person, fully online, and hybrid) for physics and astronomy courses, in terms of (i) student satisfaction with learning, (ii) student perceptions of these teaching modes, and (iii) student success in the courses. Although my findings are based on limited data, the initial analysis showed that self-motivated, hardworking students benefit most from any teaching approach. However, students from low-income groups may face some challenges in fully online and hybrid classes due to the digital divide and work schedules. I will also discuss student retention rates in the class and compare student success in terms of course grade, considering factors such as class attendance and assessment completion. The challenges faced by the instructor in each teaching mode are also different. At the end of my presentation, I will compare my results and conclusions with available data-driven scientific publications.   

Designing a Chemostat and Cell Culture Measurement Device for Undergraduate Labs

Commercial chemostats are a useful tool in biophysics and systems biology research. Continuous culture environment controls the growth and behavior of microorganisms, and provides applications to drug discovery and testing, antibiotic resistance, and bioengineering. In addition to academic and industry research, the chemostat is an excellent device for undergraduate education in microbiology. Multiplexed chemostat arrays and commercial products available are intended for graduate use and above. However, there is no chemostat product accessible for undergraduate use in a lab setting. During the 2023 Vanderbilt REU in Physics, my research partner Ella Cereghino and I have constructed a low-resource model of a chemostat with built-in optical density (OD) measurements. This design includes a single-channel chemostat and OD device powered by simple arduino electronics. The model can operate a steady state culture of Escherichia Coli for at least 12 hours and records cell density at any given time. Cell density is measured by the signal a photodiode pin records from light passing through a culture vial. The device is connected to a desktop computer to display measurements every minute. This model is ideal as an educational tool to introduce undergraduate students to microbiology and continuous culture. Potential experiments with E. coli include studying antibiotic resistance, and cell growth and substrate uptake rates under four different substrates.   

Identifying public policy indicators to reduce educational, scientific-technological, racial, gender and socioeconomic inequalities during pandemic periods through scientific research and extension activities with interdisciplinary tools from complex dynamic systems, human and applied social sciences

This work analyzes the impact of the pandemic on education and teaching-learning methods, as well as the experiences of students and teachers, both outside and within the educational environment. Research and extension activities with several scientific experiments, including physics, were carried out at some public schools from a region in the northeast of Brazil, and used to seek indicators that can reduce educational, scientific-technological, racial, gender and socioeconomic inequalities, aiming for a better quality of life and development, aligned with the Sustainable Development Goals (SDGs). The work was able to obtain informations about pandemic, education, science and technology, and emotional, socioeconomic issues of students and teachers by using theoretical basis of complex dynamic systems, and quali-quantitative data analysis. The reports highlighted inequalities worsened by the isolation due to precarious access to technology, education, health and by difficulties in adapting to remote teaching caused by the lack of evaluation methods, technologies, teaching materials and teacher training really appropriated, effective and standardized. The analyzes point to the need of improvements of public policies that ensure better quality of education and the well-being of students and teachers.   

First step towards the derivation of Klein-Gordon-Fock equation from first principles

Models, unlike theories, are based on axioms, which hinder their physical meanings in many cases. This is one of the reasons why the discussions of the physical foundations of quantum mechanics have been going on unsatisfactorily for decades. To rebuild the theories on more rigorous foundations, physicists ought to go as far back as possible to write out the basic equations of quantum physics. In this work, as an example, the Klein-Gordon-Fock equation is obtained from first principles. An adiabatically varying manifold described locally by the time-dependent Robertson-Walker metric is considered. Under these conditions, the eigenfunctions of the Sturm-Liouville problem are series expansions of the functions of free electromagnetic field, and, instead of being introduced axiomatically, the wave function appears naturally with its probabilistic interpretation. Some consequences and applications are presented.   

Phenomenological Validation of String Theory via Quantum Impedance Networks of Wavefunction Interactions

Mass is quantized. All rest mass particles have easily calculated Quantum Impedance Networks (QINs) ofwavefunction interactions, easily converted to QED. Conversion units are (m/coul)², inverse square of the string line charge density. This is important. Impedance matching governs amplitude and phase of energy flow, of information transmission. The concept has been lost in quantum physics.

Interactions are modeled by dimension-changing geometric Clifford products, sum of dot and wedge products. Product of two 1D vectors is 0D scalar and 2D bivector, WZ = Higgs + top, a minimally complete 2D Clifford algebra - 1 scalar, 2 vectors, and 1 bivector (1,2,1). Minimally complete 3D Clifford algebra vacuum wavefunction is 1 scalar, 3 vectors (orientations), 3 bivectors, and 1 trivector (1,3,3,1), the same at all scales.

Combinations of constants defining α = e²/2ε₀hc permit assigning geometrically and topologically appropriateelectric and magnetic flux quanta to wavefunction components, increasing degrees of freedom from 8 to 10 of physically manifested strings, and calculation of string QINs, the 6D phase space, three each space and corresponding phase. Time emerges from interactions, the integral of phase, generating the 4D S-matrix of observables in flat Minkowski spacetime.

Different physics at different scales arises from scale to which flux quanta are confined by reflections from impedance mismatches. We present data at all scales, Planck to cosmological, that connects string theory with experiment.   

Revisiting Einstein's Formula to Shed Light on the Mass and Charge Distributions of Slow Electrons

Considering Einstein’s equation as a quantum mechanics wave equation, W²/c² = p² + m₀²c², Dirac concluded that electrons possess oscillatory motions so that the instantaneous speed would be always equal to c. Based on his results, several models of the electron trajectory were proposed. One of the goals was to shed light on the mass and electric charge distributions of the electron. However, most of the findings failed to fit together with fundamental quantities such as the magnetic moment. As Einstein’s energy equation mirrors the Pythagorean Theorem, a simple point of view suggests that (pc) and (m_oc²) could be thought of as the two orthogonal energy-axes of a plane. According to de Broglie's hypothesis, the pc-axis is related to the wave properties, whereas the other axis, containing the mass, is connected to the particle properties such as moment of inertia. By embracing the wave-particle duality, the aforementioned equation is very helpful for considering possible models of the electron in a quantum setting. We suggest that the two axes are quantized because, on one side, wave properties may lead to quantization and, on the other side, the moment of inertia is a quantity connected to the spin. Intuitively, Pythagorean triples, which are three positive integers satisfying the Pythagorean theorem, constitute sets of solutions, also effectively quantized. We determine the possible charge and mass distributions and study the agreement with the oscillatory motion and Dirac's prediction of the magnetic moment.   

Electro-magnetic capacitor for high-density energy storage

In this work, we consider the possibility of energy storage enhancement in electrostatic capacitors using the compensational method. The essence of the proposed approach is the use of inductive voltage  to partially compensate the electrostatic voltage  produced by the electric charges on the capacitor plates.  We hypothesize that it may be possible to increase the amount of charge stored on the plates before the breakdown and increase the energy stored in the capacitor using the compensational inductive voltage. There are several possible scenarios of manipulating the inductive voltage to increase the amount of energy released via the discharge. We also consider several electro-magnetic capacitors for practical utilization. Potentially, the energy per volume stored in a simple parallel plate capacitor may exceed the one of gasoline. The physical limits and technological shortcomings of the proposed approach are also discussed.   

Sr3LiIrO6: a potential quantum spin liquid candidate in the quasi-1-D d4 iridate family

Spin-orbit coupling (SOC) offers a large variety of novel and extraordinary magnetic and electronic properties in otherwise ‘ordinary pool’ of heavy ion oxides. Here we present a detailed study on an apparently isolated hexagonal 2H spin-chain d4 iridate Sr₃LiIrO₆ (SLIO) with geometric frustration. Our structural studies clearly reveal perfect Li-Ir chemical order with desired stoichiometry in this compound, while x-ray absorption together with x-ray photoemission spectroscopic characterizations establish pure 5+ valence of Ir. We have established

a magnetic ground state with finite Ir⁵⁺ magnetic moments in this compound, contrary to the anticipated non-magnetic J_eff = 0 state, through combined dc susceptibility, ⁷Li nuclear magnetic resonance (NMR), muon spin relaxation (μSR) and ab-initio electronic structure studies. These investigations together with ac magnetic susceptibility and specific heat measurements unravel that despite having noticeable antiferromagnetic correlation among the Ir⁵⁺ local moments, the SLIO system evades magnetic ordering down to at least 0.05 K, due to geometrical frustration, arising from the comparable nearest- and next-nearest-neighbor interchain Ir-O-O-Ir superexchange interaction strengths with opposite signs. On top of it, the zero-field (ZF) μSR analysis shows emergence of a considerable proportion of frozen spin dynamics within the background of an overall fluctuating highly correlated liquid-like magnetic state down to the lowest measured temperature of 1.7 K, possibly due to large differences in the intra- and inter-column Ir-Ir magnetic exchange interaction strengths. The linear temperature dependence of the magnetic specific heat (CM ) in the 0.05-4 K range in both zero and applied magnetic fields, plus the power-law behavior of the NMR spin-lattice relaxation rate suggest a gapless spinon density of states in this charge gapped quantum spin liquid-like ground state of Sr₃LiIrO₆.