Session NN00: Virtual Poster Session III (6:30am-8:00am CST)

Driven Shock in Three Dimensions: Euler Equations Versus Molecular Dynamics, and Navier-Stokes Equations

Isotropic and continuous localised perturbations in a stationary gas, created by an external point source, cause a spherically symmetric shock wave with the energy E(t) increasing in time t as E(t)∽ t^δ, where δ≥0. The analytical solution of the Euler equation providing the spatio-temporal behavior of the shock wave, is a classic problem in gas dynamics. The exact solution shows that the asymptotic behavior of non-dimensionalised thermodynamic quantities obey power law behavior in rescaled distance near the shock center with the exponents independent of δ. However, using Event Driven Molecular Dynamics Simulations, we find that the exact solution does not match with EDMD results, anywhere, mainly in terms of the power law exponents near the shock center. We show that this mismatch is due to ignoring the contribution of heat conduction and viscosity terms, and the mismatch between theory and numerics can be resolved by taking into account the Navier-Stokes equation. We showed that the direct numerical solution of Navier-Stokes equation captures these observed power law exponents in the EDMD simulations indicating the significance of viscosity and heat conduction in shock problems.   

Harmonic Mastery in Time-Modulated Linear Elastic Unit Cells

In a recent scholarly inquiry led by Ghodake (2023), the primary focus was the exploration of nonlinear responses within time-modulated linear materials. This investigation was primarily motivated by the desire to gain a deeper comprehension of the intricate interactions involving power-amplified elastic waves, which hold significant utility in the context of nonlinear ultrasonic testing for applications related to structural health monitoring. This study centers on harnessing the harmonic manipulation capabilities of a novel unit cell, consisting of a time-independent linear material matched in impedance, sandwiched between two time-modulated linear materials. Through numerical experiments employing finite element methods, our investigation reveals the unit cells' versatile harmonic manipulation potential within phononic crystals. The numerical findings vividly depict how changes in time-modulation frequency impact the presence, absence, and distribution of harmonic energies. This intricate phenomenon arises from the interplay between linear and nonlinear elastic wave scattering due to time modulation, offering fresh insights into wave propagation dynamics complexities.   

Effective Viscosity and Mobility of Hot Particles in a Viscous Suspension

Active particles with a temperature distribution ('hot particles') have a distinct effect on viscous fluids. The temperature gradients deems the viscosity spatially dependent, therefore violating the linearity of the problem making a full description of velocity and pressure fields challenging. However, using energy dissipation analysis we show that it is still possible to study global properties of such hot suspensions. 

We calculate the effective viscosity of a dilute hot suspension, correcting Einstein’s formula to include contributions from the particles themselves and from their effect on their vicinity. We go on to present corrections for Faxen's Laws for hot spheres in the case of a linear external flow and discover non-trivial coupling due to the temperature distribution.   

How disorder impacts information content in continuous attractor networks

Attractor networks are a theme with long tradition to model information storage in the brain. Continuous attractor neural networks (CANN), in particular, have been employed to describe the storage of information about space and orientation. However, it stays controversial how useful this paradigm really is to explain actual processes, for example, in mammals, the representation of space in grid and place cells in the entorhinal cortex and the hippocampus, respectively.

 A common criticism is that the disorder present in the connections might deteriorate the system's capability to reliably preserve the information of a certain pattern.

In order to investigate if this criticism is valid, a measure is needed to objectively quantify the information content of a given neural network. Using the replica-trick, we compute the Fisher information for a network receiving space-dependent input whose connections are composed of a distance-dependent and a disordered component. We observe that the decay of the Fisher information is slow for not too large disorder strength, indicating that CANNs have a regime in which information is preserved despite the detrimental influence of disorder. In this regime, a considerable part of this information can be extracted by a linear readout.   

Exploring Phase Transitions in One-Dimensional Diluted Power-Law XY Spin Glass: A Numerical Investigation

For decades, the behavior of finite-dimensional spin glasses at low temperatures has been a subject of ongoing debate. The physics of spin glasses has been described using two primary frameworks: the replica symmetry breaking (RSB) picture and the droplet picture. In this poster presentation, we focus on our recent work investigating the AT line in the 1D power-law diluted XY spin glass model. Initially, we describe the MCMC methods employed, including a specialized heatbath algorithm tailored for XY spins, showcasing its novelty. Our study reveals clear evidence of an AT line for σ=0.6 in the mean-field regime. For σ=0.75, finite-size scaling studies support the presence of an AT transition, but for σ=0.85, there is no evidence of a transition. Furthermore, we investigated these systems at a fixed temperature while varying the field and discovered that at both σ=0.75 and at σ=0.85, there is evidence of an AT transition! Additionally, we studied a new quantity R and its scaling with system size N for different values of σ. We observe an increasing trend in R with increasing N for σ values greater than 2/3, while for σ=0.6, R decreases with N. This shift in the trend of R with N results from the absence of a phase transition for σ>2/3 in the presence of a magnetic field. Combining our simulation results, we argue that even a slight amount of external magnetic field leads to the destruction of the spin glass phase in short-range models, aligning our findings more with the droplet picture than the RSB picture.   

The Bipolator: A Self-Organized Spindle-like Bipolar Microtubule Assembly Exhibiting Oscillatory Behavior

The mitotic spindle, a self-organized bipolar assembly of microtubules and cross-linking motors, is characterized by a fluxing mixed-polarity nematic center and radially polar poles (aster). This study explores the fundamental components and mechanisms necessary to establish such a structure. Using computer simulations, we reveal that dynamical microtubules growing from persistently microtubule-associated nucleating seeds combined with opposing motors, are sufficient to organize microtubules into bipolar assemblies in the absence of any chromosomes, centrosomes or a nucleation gradient. At steady-state, the microtubules within this structure are predominantly transported by plus motors, switching orientation at the poles before transiting towards the opposing pole, hence demonstrating oscillatory behavior. This behavior depends on microtubule dynamic instability, seed size, and the specific type of minus-end motors used. Intriguingly, the pole-to-pole distance varies with the number of minus-end motors, a phenomenon previously observed in spindles in cells. The control of the length of the Bipolator can be explained considering an equilibrium of microtubule flux across the pole. This study illuminates the fundamental dynamics of a bipolar assembly, thereby deepening our understanding of the bipolarity of a mitotic spindle.   

Bacterial operons response dynamics to genome-wide stresses.

Bacterial gene networks rely on operons to coordinate activities involving multiple genes. In Escherichia coli, operons have internal promoters that allow regulating downstream genes, independently from upstream genes. We studied genome-wide stress responses in this organism targeting two global transcription regulators. We show that premature terminations of transcription elongation and internal promoters play a major role in operons, causing differences between gene response strengths to follow sinusoidal patterns that are influenced by positive supercoiling buildup. We further observe the same using data on E. coli cells subject to other stresses, as well as in Bacillus subtilis, Corynebacterium glutamicum, and Helicobacter pylori. Overall, our results suggest that internal promoters assist operons by compensating for premature terminations. This finding further opens new avenues by suggesting a new means to achieve complex dynamical behaviors in synthetic genetic circuits.   

Linking rate based and spiking models: A Quest towards biologically relevant neural systems

The brain is made of billions of neurons connected together to form networks. These networks give rise to various activities reflected in a range of behaviors. The branches of neuroscience have accomplished tremendous feats to explain these behaviors and shed light on how the brain works. However, up until now, neuroscience has been very descriptive. This is unfortunately not enough, and understanding the brain demands more. A multidisciplinary approach combining theoretical and experimental methodologies is used to understand the neurological and computational underpinnings of this wide variety of behaviors. Neural network dynamics is one such approach that deals with understanding how neural circuitry generates complex activity and accounts for most of the specific characteristics of the neuron and its responses. The dynamics of the brain are multiscale, ranging from ion channels and synapses at the molecular level to emergent behavior, like oscillations at the scale of the entire brain. The challenge, therefore, becomes how to create predictions regarding brain dynamics while simultaneously incorporating these various dimensions.
Theorists have proposed many models of neurons and their collective networks. Networks can be of many types depending on neurons, connectivity, external inputs, and synapses. Two main classes of neuron models and their networks are - rate-based and spiking neural networks. Due to the requirement to mimic the dynamics of individual spikes, they can be more computationally intensive, Spike-based neuron models, however, show promise for a wide range of applications where the temporal features of brain processing are crucial. Whereas for rate-based models, local instantaneous firing rates are monitored, individual neural spike dynamics are not. These rate-based methods are substantially less computationally intensive than equivalent research based on the direct computation of single-neuron dynamics. They are excellent for investigating large-scale phenomena and spanning scales. They do not, however, directly incorporate the spiking kinetics of individual neurons.

Neurons mainly communicate via the transfer of spikes. Thus we hypothesized that the brain follows a spiking-based model for information transfer. We aimed to determine under which conditions and parameters a spike-based model could potentially replace rate-based models. Present-day computational advancements allow us to model large networks with considerable detail in individual neurons. As much as rate-based networks are convenient and easily implemented, they lack biological relevance. Therefore we aim to find the parameters and conditions in which a spiking network can behave like a rate-based network and thus favorably replace them.
We have tried to make a comprehensive and general attempt to see if this is possible. To this end, we examined and compared two well-known networks the Brunel Network and the Continuous Attratcor Network.
The Brunel network, a spiking neuronal network, and the continuous attractor network, a rate-based neuronal network are carefully chosen as they have been reported multiple times and show a variety of essential behaviours. The Brunel network is a well-studied network of Leaky Integrated and Fire (LIF) neurons whose network behavior is very close to the theoretical behavior observed in real neurons. It shows a variety of states characterized by synchronous and asynchronous global activity and regular and irregular individual neuron activity which depends on the balance of excitatory and inhibitory connections and the magnitude of external inputs. Continuous attractor networks explain one of the high-level cognitive tasks: path integration for spatial navigation in grid cells. Using these models as a template, a simplistic model was created in which both networks with the same parameters could reproduce similar population activity.
After multiple simulations, it was evident that both rate-based and spiking neural networks explain many important experimentally observed behaviors, thus it is pertinent to ask which model is followed in the brain. Using the studied models as templates, we developed a simplistic model that allowed us to examine the link between spiking and rate-based models. A simplistic model, with minimum parameters, was simulated, and its population activity was observed. This was then scaled up to be able to incorporate the desired parameters. This could potentially pose

as the first step towards bridging the gap between rate-based and spiking neural networks. The next logical step would be to find out the necessary methods to extrapolate similar results for a network with known biological underpinnings.
Despite the fact that there is a lot to be done in the separate modeling of rate-based and spiking neural networks, the more significant question is how to bridge the gap between the two and understand what they tell us about the computations in the brain.
This will help us understand and replicate behavior better and will have a wide impact on neuroscientific research.   

Molecular structure, vibrational spectral assignments, UV-Vis and thermodynamic properties of C62O2H14 based on DFT calculations

Theoretical investigations on the C₆₂O₂H₁₄ including fulleron were done to study the structural, spectroscopic (IR, UV) and thermodynamic properties. The geometry optimization was performed at the B3LYP level using the 6-31G (d) basis set. The vibrational and UV-Vis spectral values were obtained and the data were compared with similiar theoretical values. Molecular electrostatic potential (MEP) analyses were performed to predict the reactive sites of the molecule. The thermodynamic properties of the compound at different temperatures have been determined and correlations between heat capacity, entropy, enthalpy and temperature have been done.   

Completeness of representations in atomistic machine learning

The problem of obtaining a comprehensive and symmetric representation of point particle groups, such as atoms in a molecule, is crucial in machine-learning techniques for physical problems as it underpins the capacity of models to accurately reproduce physical relationships while being consistent with fundamental symmetries and conservation laws.

However, the descriptors that are commonly used to represent point clouds -- most notably those adopted to describe matter at the atomic scale -- are unable to distinguish between special arrangements of particles in three dimensions. This makes it impossible to machine learn their properties. Frameworks that are provably complete exist but are only so in the limit in which they simultaneously describe the mutual relationship between all atoms, which is impractical. I will present a class of descriptors based on finite correlations based on the relative arrangement of particle triplets, which can be employed to create symmetry-adapted models with universal approximation capabilities and provide a solution to the problem of complete descriptors for machine learning   

Transition metal- metal carbide decorated N-doped carbon framework as efficient dual Mott-Schottky electrocatalysts for water splitting

Transition metal carbides (TMCs) have garnered significant attention as effective electrocatalysts for the hydrogen evolution reaction (HER), offering a highly active and stable alternative to precious metals like platinum, because of their d-band electronic structure resembling that of platinum. In this study, we address the challenge of developing a top-tier bifunctional electrocatalyst for efficient water splitting by employing a dual transition metal approach to electronically modify bimetallic carbides. Here, we have designed a composite structure through an in-situ fabrication process, featuring N-doped carbon nanotubes (CNT) and graphene, which serve as anchors for Co/MoC, Co/WC, and Co/VC. This integrated pyrolysis technique promotes synergistic interactions among these components and creates dual Mott-Schottky junctions, resulting in a bifunctional catalyst capable of catalyzing both the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER) with exceptional activity in both acidic and basic environments. Furthermore, it demonstrates excellent performance in water splitting under basic conditions, requiring a relatively low cell voltage of approximately 1.686 V to generate a current of 10 mA/cm² while maintaining good stability. This superior performance is attributed to the cooperative electron transfer between the Co and MoC moieties and the defects induced by nitrogen doping in the graphene/CNT-based conductive network, distinguishing it from other recently reported Mo-based carbide materials.   

Laser protection of Rydberg atoms over the gate operation

Laser-excited Rydberg atoms have shown great potential for various applications in atomic [1-7] and photonic [8-15] quantum technologies. One commonly used method for Rydberg quantum gates is the π-gap-π scheme, where atoms are left in Rydberg states for a gap period of time while other atoms are under laser rotations. However, it has been observed that for highly excited Rydberg atoms, the subsequent de-exciting π pulse cannot fully return the Rydberg population to the qubit basis. This limits the use of Rydberg states with larger interaction to loss ratio.

 

To address this issue, I propose a scheme that operates by relative intensity modulation of two lasers used in Rydberg excitation, as described in [15]. The proposed 2π operation bypasses the conventional π-gap-π schemes [1,8,9] and features continuous laser shielding of the Rydberg atoms from environmental noise. This allows for a more efficient and reliable retrieval of the qubit basis, even for highly excited Rydberg atoms. Overall, our proposed scheme offers a promising approach for improving the performance of Rydberg-based quantum gates and their potential applications in quantum technologies.

 

References:

Theoretical Investigation of fine structure and wavefunctions of Tantalum atom for 5d36s2 and 5d26s26p configurations.

Wave function contains all the information of electrons and defines the probability of a particle to be in various Energy Eigenstates. The ground state wave function of the quantum many-body system is a complicated task to calculate. Tantalum belongs to d block element, and it has open d shell configuration. This study is an attempt to determine two electron shell configurations of Ta I, 5d36s2 and 5d26s26p. Term symbols, fine structure, total angular momenta, coefficient of fractional parentage and coupled wave functions for two configurations of  5d36s2 and 5d26s26p of Ta I have been investigated. Russell-Saunders coupling scheme or LS coupling scheme has been used to obtained 39 term values and 95 fine levels. The minimum value of total angular momentum J is 1/2 and maximum 11/2 for both configurations. Total 120 microstates are determined for configuration 5d36s2.81 coupled wave functions along with their coefficient of fractional parentage are reported for Ta I. These wave functions are important to calculate several spectroscopic quantities i.e., probability density, lifetime, energy, etc.   

Dissipative-free chiral edge transport in stacked (Al/Ni)10 multilayers

Using the phase-sensitive Josephson interferometry technique, we demonstrate signatures of non-trivial edge modes in stacked multilayers S(NF)₁₀NI(NF)₁₀NS formed by conventional normal (N = Al) and magnetic (F = Ni) nanometer-thick metallic films, an insulating interlayer (I = Al oxide), and two superconducting (S = Nb) electrodes. The main findings are (i) strongly upwardly shifted periodic SQUID-like dependences of the maximum supercurrent on the probing in-plane magnetic field instead of conventional Fraunhofer patterns with nodes and (ii) h/e period of the oscillations rather than the superconducting h/2e flux quanta. Replacing the I layer with a S′IS′ junction (S′ is an ultrathin Nb layer) led to the restoration of Fraunhofer behavior, indicating the transformation of supercurrent into hybrid electron-hole modes upon contact of the superconducting S′ plane with an (NF)₁₀N multilayer. Analyzing the data obtained, we come to the conclusion that the (NF)₁₀N multilayers under study are three-dimensional electronic systems, possessing gapped bulk and side surface states with quasi-one-dimensional backscatter-free in-gap hinge modes propagating unidirectionally and possibly topologically protected. Two probable origins of the observed phenomena are discussed - a fully quantum scenario and that based on non-Hermitian physics in non-conservative systems.   

Topological Phases in Quasi One Dimensional Material TaSe3 under Pressure

TaSe₃ is a quasi 1D material, which is a superconductor at very low temperatures and was recently characterized as a Topological Insulator (TI). The existence of non-trivial topology in an intrinsically superconducting material might make the realisation of Majorana Fermions possible, thus advancing the efforts in the field of quantum computing. We aim to understand the effect of hydrostatic pressure on the electronic and structural properties of TaSe₃, using first principles calculations combined with Raman spectroscopy. Our calculations reveal that TaSe₃ undergoes two topological phase transitions under the application of pressure, around 5 GPa and 7 GPa. The first transition occurs from a weak topological insulator phase to a strong TI phase, while the second transition, around 7GPa, is from a strong to weak topological insulator phase. The weak TI hosts an even number of Dirac cones, which annihilate in the presence of strong disorder, while the strong TI phase hosts an odd number of Dirac cones on all its surfaces, which are protected against disorder by Time Reversal Symmetry. The Dirac cone in the strong insulating phase and the corresponding Fermi arc are also plotted, which shows the linear dispersion of the Dirac fermions. Our study provides a careful analysis of the topological nature of TaSe₃ at ambient pressure and reveals the role of hydrostatic pressure in tuning the electronic bands and the surface spectrum of a Topological Insulator.   

Spin fluctuation observed by 75As NMR relaxation rate in iron-pnictide superconductor Ba0.66K0.34Fe2As2 : Comparison with nematic fluctuation

Spin-echo decay rate 1/T₂ was measured to investigate the low-energy spin fluctuations in the hole-doped iron superconductor Ba_0.66K_0.34Fe₂As₂. In a wide temperature range, the relaxation curves are well-fitted by considering the Lorentzian and the Gaussian decay components, and the relaxation rates 1/T_2L and  1/T_2G were obtained. In general, the 1/T_2L is described by contributions of longitudinal magnetic fluctuations along the applied field and transverse one as the nuclear spin-lattice relaxation rate 1/T₁[1-3]. We elucidated that the 1/T_2L is well-scaled with the 1/T₁ , indicating that the contribution of 1/T₁ is dominant. Both 1/T_2L and 1/T₁ increase on cooling toward the superconducting temperature T_c, implying the development of magnetic fluctuations. The magnetic anisotropy observed both in 1/T_2L and 1/T₁ suggests that the striped magnetic fluctuations develop toward T_c. Below 100 K, the magnetic anisotropy in 1/T_2L is slightly smaller than that in 1/T₁, possibly indicating slight longitudinal magnetic fluctuations. On the contrary, the Gaussian component 1/T_2G is temperature-independent, resulting from the direct dipole interactions between ⁷⁵As nuclear spins. The comparison between the 1/T_2LT monitoring spin fluctuations and the nematic susceptibility suggests a possible coupling between spin and orbital fluctuations, but the coupling is weaker than that in electron-doped systems (e.g. LaFe_1-xCo_xAsO and Ba(Fe_1-xCo_x)₂As₂))[4-6]. The origin of the weaker coupling in a hole-doped system Ba_0.66K_0.34Fe₂As₂ will be discussed.   

Fractional Quantization Interpretation for the Phase-Locking dynamics of driven-Superconductive Josephson ac effect

This report proposes a quantization interpretation on the Macroscopic quantum dynamics of driven ac Jesephson effect. A discussion is made to compare the so-called classical resonance and the Macroscopic dynamics of of Josephson oscillation of the phase difference across the junction. A collective quantum phase locking dynamics, with integer or fractional winding numbers, is proposed to unify the Shapiro steps as a mechanism of quantization. The proposed fractional quantization of macroscopic quantum phase locking may provide a new unifying thinking on the Quantized Hall Effects including IQHE and FQHE.   

Poster:Twist angle monitored inhomogeneous magnetism in a van der Waals itinerant moiré ferromagnet

Abstarct: Two dimensional (2D) van der Waals (vdW) moire magnets are the next generation quantum materials which hold the possibilities to unlock unprecedented properties in the field of twistronics and spintronics on account of their strong electron correlations. Essentially, the strong electron correlations in twisted geometries of vdW layers have a central role in of manifestation of unusual magnetic properties such as skyrmions, noncollinear magnetic textures, moire Zeeman effect and many more. Hence, identification of ideal materials is of great importance for realization of such exotic quantum phenomena. Here, we showcase a new quantum mechanical phenomenon of twist regulated on-site magnetism in vdW bilayer consisting non-magnetic 1T-NbSe₂ and ferromagnetic 1T-VSe₂ monolayers at various twist angles. In particular, we observe appearance of inhomogeneous mixture of quenched and augmented magnetic moments per V and Nb atoms. The inhomogeneity in the magnetic moment per V and Nb atoms is strongly influenced by the twist angles, depicting a significant variation of the variance of the magnetic moments with twist angles. Moreover, we find prominent flat bands emerging at higher twist angles making the system more localizedlike allowing for such inhomogeneous behavior. The studied systems satisfy Stoner criterion for ferromagnetism and the findings reveals that local moments of the system can suitably be tuned with twist angles.   

Edible biomaterial based memristive devices for non-volatile memory design

With the development of technology, electronic waste has become an undesirable burden on our environment due to the extreme usage of perilous materials. Therefore, it is very beneficial to use biomaterials for the fabrication of electronic devices that are biocompatible, environmentally benign, non-toxic, etc. Resistive Random Access Memory(RRAM) is one of the most promising memristive devices due to its simple metal-insulator-metal (MIM) structure, having high speed, ultimate scalability, low power consumption, capability of numerous-bit switching, and CMOS compatibility. Edible biomaterials like egg albumen(sources of protein), eggshell (Calcium carbonate), inner peel of citrus fruits (source of pectin/polysaccharide), Potato (source of starch), crabs, prawns (source of chitosan), etc. are most promising components for the fabrication of Bio-ReRAM. This study foregrounds the extraction and fabrication of Ag/Egg albumen/ITO and Ag/Eggshell powder/ITO devices which work on the principle of resistive switching. Further, we have explored the structural and conduction mechanism differences/similarities between the above two systems. Characterizations like FESEM, FTIR, UV-visible spectroscopy, electrical I-V measurements, I-V log-log plot, and endurance (I_On/I_Off) behavior analysis have been done for both devices. This demonstrates that Egg albumen and Eggshell both are the most promisable, robust as well as eco-friendly candidates for the next-generation memory applications.   

An Effective Supramolecular Zinc Metallohydrogel based RRAM Device for In-memory computing Application

Supramolecular gels are versatile materials that possess smart properties. They are used in various industries such as sensors, cosmetics, foods, nanoelectronics, logic gates.These gels are formed through the combination of hydrogels and supramolecular chemistry. In this work, we have developed a well-organized and efficient method to rapidly synthesize a supramolecular zinc based metallohydrogel. This metallohydrogel is prepared by using pentaethylenehexamine as a low molecular weight gelator in water at room temperature. Here, we have fabricated a zinc metallohydrogel based Schottky diode device in a lateral metal-semiconductor-metal geometry to explore its charge transport behavior^1,2,3. Here, zinc metallogel based RRAM (Resistive random access memory) device have showed a proper bipolar resistive switching behavior⁴. This RRAM device demonstrated exceptional switching endurance with over 5000 switching cycles and a high ON/OFF ratio of 150. Due to its robust resistive switching behavior and enhanced stability, these structures are well-suited for applications in non-volatile memory design, neuromorphic computing. Here,we have also prepared cross bar array to show how this metallohydrogel based RRAM device acts as in memory computing where computation and information storage are carried out at the same circuit level. Thus, by utilising crossbar arrays in memristor-based logic gate circuits, we can investigate various engineering approaches that rely on the concepts of in-memory computing.   

Investigation of magnetic ground state of double perovskite oxide Nd2FeCrO6 using neutron diffraction and muon spin spectroscopy

The transition-metal atoms at B and B’ sites in double perovskite oxide (DPs) having chemical formula A₂BB’O₆ often lead to complex magnetic behaviour and act as a source of intriguing physics. The combined effect of spin, charge and orbital degree of freedom, such as the interaction between the spins at the B/B’ sites, Coulomb interaction, spin-orbit coupling, crystal field effects, etc., give rise to exotic magnetic states. We used neutron diffraction and muon spin spectroscopy techniques [1] together with DC magnetometry and calorimetric measurements to elucidate the magnetic ground state and the origin of a low-temperature anomaly in semiconducting DPs Nd₂FeCrO₆.Structural analysis using X-ray and neutron diffraction techniques confirms the B site-ordered monoclinic phase. While the temperature-dependent neutron diffraction measurement decerns the ferrimagnetic ground state with a net magnetic moment of  ~2μB, arising due to antiferromagnetic interaction between Fe and Cr sub-lattice, muon spin spectroscopy asserts the existence of dynamic long-range commensurate magnetic order below the transition temperature 250 K . Thermal evolution of transverse and longitudinal muon spin relaxation rates reveals that the negative magnetization arises due to the ordering of Nd ion below 20K. Thus, complementary experimental techniques give insight into the microscopic magnetic properties of the system.

References:

 [1] P Dalmas de Réotier and A Yaouanc 1997 J. Phys.: Condens. Matter 9 9113   

A First-Principles Investigation of VClBr2: A Novel van der Waals Ferromagnetic Semiconductor

The discovery of long-range magnetic ordering in two-dimensional (2D) materials has posed both challenges and opportunities, revealing novel physical phenomena. These materials, featuring spin-polarized electrons/holes and atomic layer thickness, underpin advanced information technology with high integration, ultra-fast response, and low power consumption. Monolayer CrI₃, as a demonstrated member of this family [1], displays adjustable interlayer magnetic coupling, rendering it highly favorable for spintronic applications. Similarly, the centrosymmetric structure of Cr₂Ge₃Te₆, functioning as a ferromagnetic semiconductor [2], presents diverse opportunities for the creation of 2D magneto-electric devices and magneto-optic applications. In this study, inspired by recent findings, we conducted a comprehensive investigation into the electronic and magnetic properties of monolayer VClBr₂ [3] using first-principles density functional theory. This material represents a novel form of an intrinsic ferromagnet in the two-dimensional realm, displaying semiconducting traits. Under strain ranging from -1% to 5%, it maintains consistent ferromagnetic (FM) characteristics. A shift to antiferromagnetic (AFM) phase occurs between -5% and -1% strain. When exposed to an electric field (E_z = 2.5 V/nm), VClBr₂ displays FM ordering, transitioning to AFM when the field increases from E_z = 5 V/nm to 10 V/nm.

Remarkably, without any defects or changes in chemical composition, we observed a transition in the material from semiconductor to metal to half-metal based on the ferromagnetic and antiferromagnetic ground states, influenced by strain engineering and an electric field. When an electric field was applied along the z-axis at 2.5 V/nm, the Curie temperature (T_c) drastically increased to approximately 340 K, marking a substantial enhancement of about 6700% from its base value. Additionally, our calculations on magneto anisotropic energy (MAE) confirmed the presence of an in-plane easy axis, with a magnetization of 2.85 µ_B/V atom.   

Twist controlled Spin-transport across Phosphorene/Nickel (111) Spinterfaces

The electron's spin serves as a crucial information carrier in spintronic devices, which is extremely important for the growth of quantum computing applications, high-density data storage, high-frequency devices, magnetoelectrics, etc. Phosphorene [4], a novel 2D semiconductor, offers significant potential for nanoelectronic, optoelectronic, and spintronic applications due to its inherent bandgap, high mobility, excellent spin diffusion and relaxation time [3], and ambipolar nature. In this study, we explored the transmission probability of spin carriers from a Ni electrode into phosphorene using first principles-based density functional theory (DFT) in conjunction with the non-equilibrium Green’s function (NEGF) method. By increasing the number of phosphorene layers (N = 1, 2, 3) and incorporating a twist mechanism, we significantly enhanced the efficiency of spin injection from Ni to the phosphorene layer. We systematically examined the structural, electronic, and magnetic characteristics of the P/Ni(111) junction. On the Ni surface, the mono-, bi-, and tri-layers of phosphorene exhibited metallic behavior. The electronic bands near the Fermi level varied with the twisted angles and observed ohmic contact between phosphorene and the Ni(111) surface. The majority carrier was spin-down at the Fermi level, with an induced magnetic moment of -0.009 μ_B in phosphorene and an enhanced magnetic moment in the Ni atom. Moreover, the current-voltage characteristics displayed negative differential resistance (NDR effects), with peak-to-valley ratio (PVR) and sharpness factor (S_E) varying with the twisted angle. The efficiency of spin injection increased with the number of phosphorene layers, and twisting modified the spin injection efficiency, resulting in an increase of up to 60%. These findings offer valuable theoretical insights into the transmission of spin carriers within phosphorene layers on a magnetic substrate, suggesting a novel approach for designing spintronic devices utilizing phosphorene.   

On Spin Glass and Its Magnetism Dynamics

Spin glasses are complex and disordered magnetic systems that have attracted considerable attention from physicists, mathematicians, and computer scientists over the past few decades. Despite extensive research, many unanswered questions remain about the nature of spin glass systems and their behavior under a magnetic field. Numerically simulating the magnetism dynamics of spin glass models will give us more insights about spin glass systems, rather than waiting for infinite time for the system to equilibrate. In our research we have used a 2D Edward-Anderson Ising spin glass system and on top of the system we have kept ferromagnetic blocks to create locally applied magnetic fields that affect the magnetism dynamics of spin glass local moments. Using numerical simulation employing the Kinetic Monte Carlo sampling method, which helps us sample the rarer events to overcome the longer relaxation time problem, we try to understand how the magnetism dynamics of spin glass is affected by the arrangement and intensity of the locally applied magnetic field.  

    

Investigation of the SnSSe Janus monolayer as the solution for efficient thermoelectric materials

Nowadays, in order to increase the energy efficiency, the use of thermoelectric materials has been suggested as the solution. Thermoelectric materials can convert heat in to electricity. This transformation is described by the Seebeck effect. The ability of thermo-electric materials is measured by ZT parameter.

In thermoelectric materials, we look for materials that have higher ZT. This means, that we want to choose a material that has lower thermal conductivity to give us a higher ZT. Here, two materials of SnSSe as a newly proposed thermoelectrically efficient janus monolayer and SnS₂ are investigated. We investigated the temperature profile of both materials by using Monte Carlo simulation of the non-Fourier phonon Boltzmann equation. As the temperature distribution is calculated, the ZT values of both materials according to peak temperature that they experience at different times, are obtained using the Seebek formula. It is obtained that the janus material of SnSSe shows a much higher ZT value compared to that of the SnS₂. This fact is true while the figure of merit for the studied janus layer is almost three times larger than the one for SnS_2. This confirms that the janus monolayer, SnSSe, is much better choice for being used as the thermoelectric material in the thermoelectric generators.   

UV-Vis absorption spectra using semi-empirical Hamiltonian plus a machine learning model

Machine learning (ML) is becoming a powerful tool for obtaining accurate properties of materials at a reduced computational cost. This work shows that semi-empirical Hamiltonian, INDO/s + machine learning models (INDO/s+ML) could give high-level first principle results. The machine learning models were used to add corrections to INDO/s absorption spectra to produce TDDFT absorption spectra. Excitation energy and oscillator strength corrections for 16k+ organic molecules were learned using the Kernel Ridge Regression (KRR) and Neural Network (NN) models. The INDO/s+ML predicts TDDFT excitation energies and oscillator strengths within MAE/RMSE of 0.15/0.23 eV and 0.04/0.11, respectively, for 3600 organic molecules not included in the training. The calculated spectra for these molecules with INDO/s+ML agree well with those from TDDFT.   

Nonlocal heat transport in Silicon MOSFETs

-abstract-

  Heat transport study in micro/nanoscale structures, particularly within the context of Nano-electronics, stands as an intriguing area of study. To put it differently, accurately simulating temperature distributions within the transistors is crucial for the design of more efficient devices which have lower threshold temperatures. Here, a phenomenological non-local framework for the study of micro/nanoscale heat transport, aiming to get precise temperature and heat flux profiles with minimal computational expenses have been developed. Moreover, the non-dimensional parameter $gamma$ [1], representing the degree of non-locality, is employed through nonlocal DPL modeling (NDPL). In addition to determining the non-locality coefficient, various factors inherent in DPL, such as temperature jump and phase lagging ratio, are reassessed. The parameter $gamma$ is determined to exhibit a linear dependency on the Knudsen (Kn) number, being 3.5 for Kn=10 and 0.035 for Kn=0.1. Considering the non-locality term in calculations, has been obtained to be important for systems with low or high Knudsen numbers. Further, the achieved results present very good consistency with what have been previously reported solving the phonon Boltzmann Equation [2]. 

[1] D. Y. Tzou, and Z. Y. Guo, Nonlocal behavior in thermal lagging, International Journal of Thermal Sciences 49(7) (2010) 1133. 

[2] R. Baratifarimani, and Z. Shomali, Implementation of nonlocal non-Fourier heat transfer for semiconductor nanostructures. arXiv preprint arXiv:2307.00665 (2023).   

Unsupervised detection of quantum phases and their local order parameters from projective measurements

Recently, machine learning has become a powerful tool for detecting quantum phases. While the sole information about the presence of transition is valuable, the lack of interpretability and knowledge on the detected order parameter prevents this tool from becoming a customary element of a physicist's toolbox. Here, we report designing a special convolutional neural network with adaptive kernels, which allows for fully interpretable and unsupervised detection of local order parameters out of spin configurations measured in arbitrary bases. With the proposed architecture, we detect relevant and simplest order parameters for the one-dimensional transverse-field Ising model from any combination of projective measurements in the x, y, or z basis. Moreover, we successfully tackle the bilinear-biquadratic spin-1 model with a nontrivial nematic order. We also consider extending the proposed approach to different lattice geometries and detecting topological order parameters. This work can lead to integrating ML methods with quantum simulators studying new exotic phases of matter.   

Rydberg Parity Measurement

The combination of atom-light interaction coupling and Rydberg interaction has revolutionized the field of quantum technology, leading to a wide range of applications [1-13]. One such application is the non-destructive parity measurement of collective qubit states in multiple atoms with applications on Quantum computation, simulation, and optimization. In this talk, we propose a robust and high-fidelity scheme for constructing a non-destructive Rydberg parity meter. With this meter, we can determine the parity information of a bipartite state without destroying it, allowing us to utilize the output bipartite state for further quantum information processing tasks. Specifically, an auxiliary atom can sense the state of the plaquette spins and change its state only based on the parity of the central atom [12-13]. We then measure the state of the auxiliary atom to reveal the parity of the plaquette. We also analyze the performance of the Non-destructive Rydberg Parity Meter (NRPM) under realistic experimental parameters and consider the impact of decoherence sources.

References:

1-    M. Khazali, K. Mølmer, Phys. Rev. X 10, 021054 (2020).

2-    M. Khazali, Phys. Rev. A 98, 043836 (2018)

3-    M. Khazali, H. W. Lau, A. Humeniuk, C. Simon, Phys. Rev. A 94, 023408 (2016) 

4-    M. Khazali, K. Heshami, C. Simon, Phys. Rev. A 91, 030301 (2015)

5-    M. Khazali, C. Murry, T. Pohl, Phys. Rev. Lett. 123, 113605 (2019)

6-    M. Khazali, K. Heshami, C. Simon J. Phys.  B, 50, 21 (2017)

7-    M. Khazali, Optics Express 31(9), 13970-13980 (2023)

8-    M. Khazali, IJAP 10, 19 (2021)

9-    Khazali, M. (2023). arXiv preprint arXiv:2301.04450.

10-    M Khazali, Phys. Rev. Research 3, L032033 (2021)

11-    M. Khazali, Quantum 6, 664 (2022).

12-    Khazali, M., & Lechner, W. Communications Physics 6, 57 (2023).

13-    Khazali, M. (2022). Photonic interface for long-distance entanglement of logical-qubits. arXiv preprint arXiv:2204.08522.   

High-fidelity, multi-qubit generalized measurements with dynamic circuits

Generalized measurements, also called positive operator-valued measures (POVMs), can offer advantages over projective measurements in various quantum information tasks. Here, we realize a generalized measurement of one and two superconducting qubits with high fidelity and in a single experimental setting. To do so, we propose a hybrid method, the "Naimark-terminated binary tree," based on a hybridization of Naimark's dilation and binary tree techniques that leverages emerging hardware capabilities for mid-circuit measurements and feed-forward control. Furthermore, we showcase a highly effective use of approximate compiling to enhance POVM fidelity in noisy conditions. We argue that our hybrid method scales better toward larger system sizes than its constituent methods and demonstrate its advantage by performing detector tomography of symmetric, informationally complete POVM (SIC-POVM). Detector fidelity is further improved through a composite error mitigation strategy that incorporates twirling and a newly devised conditional readout error mitigation. Looking forward, we expect improvements in approximate compilation and hardware noise for dynamic circuits to enable generalized measurements of larger multi-qubit POVMs on superconducting qubits.   

Extended Keldysh formalism for entropy evaluation

The Keldysh formalism is a key approach for calculating Green's functions out of equilibrium. We present a scheme to utilize the main part of the formalism, the closed time contour, for entropy production calculations in open quantum systems. To this end, we apply the formalism not to Green's functions, but to density matrices. By extending the Keldysh contour to multiple connected contours for copies of the density matrix, we use it to represent flows of Rényi entropies, and determine symmetries in perturbative calculations. This scheme is applied to simplify calculations of von Neumann entropy production.   

Towards quantum control of an ultracoherent mechanical resonator with a fluxonium qubit

Beyond their applications in quantum computing, superconducting qubits are a powerful platform to probe various quantum phenomena in the context of hybrid quantum systems [1].  However, most of them are confined to the GHz frequency domain, limiting the class of systems they can interact with. Building upon the heavy fluxonium architecture introduced by [2], we have developed a superconducting qubit with an unprecedentedly low transition frequency of 1.8 MHz [3]. Notably, we have demonstrated a qubit with a coherence time exceeding 30 μs, a sideband cooling scheme to prepare the qubit in a pure state with 97.7% fidelity, and single-shot readout capability. Moreover, by detecting a weak charge modulation by repeated qubit interrogation, we demonstrate the high-sensitivity of this qubit architecture to a nearly resonant AC-charge drive, proving its potential in a hybrid circuit scenario. We will finally present our recent efforts to achieve the strong coupling regime between this qubit and an ultra-coherent softly-clamped mechanical membrane.

[1] Y. Chu et al. Nature 563, 666 (2018).

[2] H. Zhang et al. Physical Review X 11, 011010 (2021).

[3] Najera et al. arXiv:2307.14329 (2023). In review at PRX.   

High pressure-temperature superionic states of P-3 brucite [Mg(OH)2] promoting enhanced protonic conductivity

Brucite is an archetype dense hydroxide mineral, belonging to ternary MgO-SiO₂-H₂O system, which can host a significant amount of water in the form of OH^-. The consideration of brucite in H-circulation is thus of crucial importance as the dense hydrous silicates¹ cannot account for the observed mantle conductivity. Using ab initio molecular dynamics simulations, we investigate the diffusion of H⁺(proton) in high-pressure P-3 polymorph of brucite in a combined high pressure (p)–temperature (T) range of 10-85 GPa and 1250-2000K. We observe vigorous proton diffusion at elevated p-T resulting in a liquid state of the H-sublattice, within solid Mg-O sublattice, generating the superionic states in brucite. This study also reveals an unusual pressure-dependent proton migration characterized by maximum H⁺-diffusion in the pressure range of 72-76 GPa along the isotherms. The mobility of H⁺ is found to be strongly anisotropic, allowing no transport across the MgO₆-octahedral layers i.e. along c-axis. The liquid state of the protonic sublattice yields a quasi-2D layer of fast H⁺ causing a drastic enhancement in the electrical conductivity of P-3 brucite. Comparison of our calculated conductivity with ex-situ geophysical data^2,3 indicates the possible brucite abundance to explain high-conductive zones in the deep mantle of earth.

¹Hirschmann & Kohlstedt Phys. Today 65 40–5 2012

²Constable & Constable, Geochem. Geophys. Geosystems 5 1–15 2004

³Civet et al., Geophys. Res. Lett. 42 3338–46 2015   

Investigating the role of compression rates in pressure induced polymerization of crystalline acrylamide using ab-initio molecular dynamics

Pressure-induced transformations in molecular crystals with varying pressure increase rates (PIRs) can enable the kinetic control of the obtained phase. Herein, we investigate the dependence of PIR on the pressure-induced polymerization of acrylamide. 0 K optimizations and room temperature molecular dynamics simulations at two different PIRs are used to characterize the structural evolutions and transformation mechanisms. Quasi-static compression at 0 K suggests polymerization to a 3-dimensional polymer, whereas rapid compression indicates the existence of multiple metastable polymers with lower activation barriers for polymerization. Room temperature ab initio MD simulations led to different structural evolutions based on the applied PIR. Although both compression pathways eventually yield the same metastable polymer, rapid compression results in disordered polymers. The mechanism of formation as well as the structural and electronic properties of the various polymers obtained are characterized. Our results suggest a hierarchical route towards the thermodynamic polymer through other metastable polymers.   

Bulk nanobubble generation by gas supersaturation method.

For the past decade, nanobubbles have been shown to have numerous applications due to their unique properties. Despite its potential in enhancing gas-liquid operations, limited to no studies have been conducted on nanobubble generation in pure organic solvents with strong scientific evidence . Furthermore, there is no direct evidence that explains the generation of nanobubbles by gas supersaturation mechanism. Since there is a strong dependence of gas solubility over temperature, therefore, a solvent at a high temperature, when, mixed with the same solvent at a low temperature releases the excess gas that may nucleate to form nanobubbles. The nanobubble generation was carried out with the variation in the temperature difference between hot and cold solvents ranging from 10°C to 80°C  in the alcohols i.e., butanol, propanol, ethanol, methanol, and water. The nanobubbles are characterized by NTA (Nanoparticle Tracking Analysis) and DLS (Dynamic Light Scattering) in terms of bubble diameter, population and zeta potential. The results reported the formation of nanobubbles to be higher with maximum concentration in the range of  <!--[if gte msEquation 12]> style='mso-bidi-font-style:normal'>7.78× style='font-size:12.0pt;mso-ansi-font-size:12.0pt;mso-bidi-font-size:12.0pt;
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Two-Dimensional Janus VSeTe monolayer with ultra-low lattice thermal conductivity for Thermoelectric Application

Janus 2D materials have shown tremendous potential for thermoelectric applications [1]. In this work, we have calculated the electronic and thermoelectric properties of VSeTe monolayer with the help of Density functional theory and Boltzmann transport equation [2,3].  The electronic band structure revealed the semiconducting nature of VSeTe, with an indirect band gap of 0.28eV. The phonon dispersion curve established the dynamic stability of the proposed structure. Morever, to confirm the thermal stability of the system,  Ab initio molecular dynamics (AIMD) simulations were performed at 300K. We have also calculated the elastic constant to check the mechanical stability of the structure. The thermoelectric parameters such as Seebeck coefficient, power factor, and electrical conductivity have been calculated under constant relaxation time approximation at temperatures of 300K, 600K, and 800K. The lattice thermal conductivity (K_l ) at room temperature has been found to be very low in VSeTe monolayer as compared to other Janus monolayers [1]. An ultralow value of K_l of 0.19 W/mK at room temperature was observed in the Janus monolayer VSeTe, primarily due to  very low group velocity and short phonon lifetime in VSeTe. This ultralow lattice thermal conductivity and high power factor, result in a high thermoelectric figure of merit close to the value of 1 at room temperature. Our finding indicates the potential application of VSeTe monolayer for thermoelectric devices in energy harvesting at room temperature.   

Poster: Boosting thermoelectric efficiency via cationic sites in spinel oxides

Decoupling electronic and thermal transport properties remains the biggest challenge in finding efficient thermoelectric materials. We demonstrate an approach to decoupling the complex interdependence among electrical conductivity, Seebeck coefficient, and lattice thermal conductivity in spinel oxides. Utilizing the effects of tetrahedral and octahedral coordination on bonding characteristics, we demonstrate tuning the electronic and thermal transport properties of cobalt-based spinel oxides ACo₂O₄. Tetrahedrally coordinated cation A (Zn/Cd) controls the electronic transport, while thermal transport has been controlled by octahedrally coordinated cation B (Co). The combination of heavy bands and contribution of the tetrahedrally coordinated environment of Co near valence band maxima (VBM) and conduction band minima (CBM) results in an enhanced power factor. Additionally, the substitution of Cd for Zn on an octahedrally coordinated cation site leads to one order of magnitude reduction in the lattice thermal conductivity. This reduction is attributed to the significant mass difference, phonon modes, phonon lifetime, and remarkably strong anharmonic scattering introduced by Cd. Simultaneously achieved high power factor and low lattice thermal conductivity resulting in an enhanced figure of merit value of 1.68 for Cd-spinel. The approach of decoupling atomic contributions utilizing various cationic sites demonstrates a potential route to enhance thermoelectric performance.    

A Photo-rechargeable Supercapacitor using CsPbBr3-Activated Carbon Composite

The need for renewable and sustainable energy resources is increasing exponentially. Due to their high specific power, capacitance, and cyclic stability Supercapacitors (SC) emerge a promising alternative for renewable energy storage device and have drawn tremendous attention over the past decade. Hybrid halide perovskite materials, exhibiting mixed electronic-ionic conductivity and outstanding optical properties, hold great promise as potential candidates for advancing this field. In the current study, CsPbBr₃ nanoparticles were synthesized using the hot injection method under a nitrogen gas environment, and their potential for Photo-rechargeable Supercapacitor applications was explored. To enhance the energy and power density of the CsPbBr₃ supercapacitors, composites of CsPbBr₃ and Activated carbon (AC) were fabricated. The AC was prepared through the solvothermal method, followed by activation using KOH at 750 ºC in an argon atmosphere. The CsPbBr₃-AC composites were synthesized by introducing the desired amount of AC (powder) into a three-neck flask containing all the necessary precursors, using the similar reaction conditions used for the synthesis of pristine CsPbBr₃. Detailed structural and spectroscopic characterizations were performed, confirming the formation of CsPbBr₃-AC composites. Supercapacitors were realized using CsPbBr₃-AC composites as the working electrode, Platinum as the counter electrode, and Ag/AgCl as the reference electrode. Electrochemical measurements were carried out using cyclic voltammetry (CV) and galvanostatic charging/discharging (GCD) under both dark and illuminated conditions. These devices exhibited high capacitance and excellent capacitive retention, demonstrating their significance in Photo-rechargeable Supercapacitor applications.   

Excellent Supercapacitive Response of Microwave-synthesized Two-Dimensional Transitional Metal Oxide Using Metal Chloride Precursor

 

In the past decade, many 2D materials beyond graphene, such as 2D Transition Metal Dichalcogenides (TMDs), Transition Metal Carbides as well as Nitrides, and group V elements like phosphorene, arsenene etc., have been investigated. However, the layered metal oxides 2D materials have gained intermittent attention for their unique electronic, photocatalytic, sensing, and magnetic properties. Their ultrathin structure gives rise to novel characteristics and potential applications compared to their bulk counterparts. Hematene, a 2D ultrathin layer of iron oxide (Fe₂O₃), was synthesized upon microwave irradiation. Their chemical identification is done with the help of Raman and X-ray photo spectroscopy. Hematene is an n-type semiconductor and negative photoconductivity has been observed, with green excitation showing the highest sensitivity. Electrochemical measurements performed at an open circuit voltage of 0.58V on the as-prepared sample, as an electrode active component, showed excellent supercapacitive characteristics with capacitive retention of ~80% even after 10000 cycles at a current density of 5mA/cm².

References:

Epitaxial nanostructure derived robust energy storage performance in symmetric and asymmetric ultracapacitors

Epitaxial nanostructure derived robust energy storage performance in symmetric and asymmetric ultracapacitors

Monika Sharma, and Pritam Deb*

Advanced Functional Material Laboratory (AFML), Department of Physics, Tezpur University (Central University), Tezpur 784028, India.

*E-mail: pdeb@tezu.ernet.in

 

Tungsten disulphides are kind of intriguing electrode materials for supercapacitors, however due to their propensity for agglomeration and substantial volume variations during repetitive charged-discharge cycles; they are indeed constrained by cyclic instability and poor energy storage performances. In this study, nanoflakes-on-nanosheets WS₂/N doped reduced graphene oxide (N-rGO) epitaxial nanostructure were developed wherein intertwined N-rGO nanosheets serve as supports and effectively spread WS₂ nanoflakes over the N-rGO surface, supplying a large number of electroactive sites. Significantly, the C−O−W bonds that connect the flakes and sheet together form a highly coupled interface that efficiently facilitates interface charge transport and mechanically strengthens it to withstand volume variations. In the current study, supercapacitors based on WS₂/N-rGO electrode exhibit very high specific capacitance, cyclability, and distinctive structural modifications throughout electrochemical cycling, demonstrating the electrode's significant potential for energy storage. It has a remarkable specific and cyclic stability for symmetric supercapacitor. The asymmetric supercapacitor exhibits higher specific capacitance, maximum energy density and power density. The research should pave the way for the investigation of further TMDs-based electrode materials in the near future for the construction of improved energy storage devices.

    

Super Moiré of Controlled Stacked Monolayers

Moiré lattices have recently emerged as a highly promising platform for the exploration of quantum states and correlated physics.[1,2] The introduction of periodic Moiré potential within superlattices has the profound effect of modifying their electronic band structures, giving rise to novel quantum phenomena, notably Moiré excitons and Moiré phonons. In this study, a deeper Moiré potential is realized by controlled stacking of monolayers of transition metal dichalcogenides (TMDs) via chemical vapor deposition (CVD).

Our experimental findings have revealed the presence of multiple split super Moiré excitons within the twisted configuration at a high temperature of 120 K. This discovery not only offers an efficient approach to scalable Moiré studies but also unveils the potential for deeper Moiré phenomena, promising exciting prospects for the future exploration of quantum physics.

 

1.     Du, Luojun, et al. "Moiré photonics and optoelectronics." Science 379.6639 (2023): eadg0014.

2.     Huang, Di, et al. "Excitons in semiconductor moiré superlattices." Nature Nanotechnology 17.3 (2022): 227-238.   

Comparative study of mechanical, electronic, and optoelectronic properties of all inorganic CsPbX3 (X = Cl, Br, I) perovskite by DFT approach

The organic and inorganic hybrid Pb-halide perovskites with formula ABX₃ (A is a monovalent organic cation, B is a lead cation and X is a halide anion) have emerged as a revolutionary semiconductor in various applications. But the long-term stability and Pb toxicity of these perovskites attract more and more attention, therefore, all inorganic perovskites became an alternative perovskite for optoelectronic applications. To this point of view, in this research work, we theoretically study the mechanical, electronic and optoelectronic properties of CsPbX₃ (X = Cl, Br, I) perovskites for potential optoelectronic and solar cell applications. The first principles calculations were performed based on the density functional theory (DFT) in the framework of generalized gradient approximation (GGA) in CASTEP code software. The electronic properties calculation shows that CsPbI₃, CsPbBr₃ and CsPbCl₃ direct band gap nature with the band gap lying between 1.47 eV and 2.20 eV. The lattice parameters and volume strongly depend on the halide components. The mechanical stability is higher for Cl-based halides than the rest halides. It is also seen that the optical properties such as reflectivity, dielectric constants, refractive index, optical conductivity and absorption coefficient can be tuned by varying the halide component which may pave the way to develop optoelectronic and advanced electronic devices.

    

Synthesis and study of Manganese(Mn) doped Molybdenite(MoS2) wafer shape sample by using spark plasma Sintering technique in conjunction with master curve analysis

Molybdenite(MoS₂) as a mineral with semiconducting characteristics might be an intriguing substitute for silicon within (opto)electronic industry in future. In bulk, it is indirect gap semiconductor(Eg=1.3 eV) with high dielectric constant. We have made wafer shape Manganese(Mn) doped (14%) Molybdenite by using spark plasma Sintering at high vacuum reaching high temperature (T~2200 K). The wafer has 1 inch diameter and 1•5 mm thickness with gray color. The temperature and pressure profile implemented during Sintering process were in such a manner to keep polycrystalline nature of the processed powder (through master curve analysis) confirmed by PXRD analysis. Optical study of sample proved semiconducting properties of sample with Eg=1.28 eV. Temperature study of magnetic succeptibility have shown para to ferromagnetic phase transition at curie temperature of 240K. In all, bulk magnetically doped Molybdenite sample with relevant semiconducting properties have been made through Sintering technique and studied through structural, optical and magnetic characterization techniques with promising results. We plan to present our findings at aps march meeting.   

An Investigation of Structural and I-V characteristics of (1-x)LaMnO3.(x)rGO Nanocomposite Samples

The study focused on (1-x)LaMnO3 (LSMO).(x)rGO nanocomposites, exploring their structure and electrical behavior. Using XRD, FESEM, and Raman spectroscopy, dual phases were observed. Distinctive bipolar resistive switching behavior in I-V profiles indicated potential electronic applications. Increasing rGO led to an oxygen-deficient region, confirmed by XPS. Oxygen vacancies and ions were identified as pivotal in resistive switching. Sample x = 0.001 exhibited superior characteristics. HRTEM validated distinct lattice spacings. Conduction primarily followed Ohmic and Schottky emission phenomena. The research offers insights for engineering nanocomposites in electronics.   

A comparative analysis of frequency-doubling in type-II quasi-phase-matched KTP crystals

Second harmonic generation (SHG) is a widely used nonlinear three-wave mixing process to characterize different bulk nonlinear crystals/waveguides e.g., beta barium borate (BBO), potassium titanyl phosphate (KTP), Lithium niobate (LN), etc. for its implementation in nonclassical experiments utilizing spontaneous parametric down-conversion (SPDC) for the generation of entangled-photon pair sources. Such sources are useful candidates for applications in Optical Quantum technology e.g., quantum key distribution (QKD) and quantum computing. As a characterization tool for the SPDC source, we experimentally investigated the variation of second harmonic (SH) power by tuning the crystal temperature for three (10mm, 20mm, and 30mm) periodically poled KTP (ppKTP) crystals, phase-matched for the type-II process (H+V→H). We observed an increment in the conversion efficiency of SHG from 2.96 to 12.6 (P_SH/P_pump*10⁶) and a decrement in the temperature bandwidth from 2.80°C to 1.50°C with an increase in crystal length, respectively, validated by our theoretical calculations. Moreover, the focusing of the pump beam reveals the emergence of asymmetry in the SH power for different crystal lengths due to a competition between the confocal parameter attaining the crystal length, indicating the need for an optimization of the focusing parameters. Such thorough optimization of different parameters e.g., pump focusing, and crystal temperature is crucial for its utilization in different quantum applications.    

Simmulated Annealing for Global Search

Global search over black box functions describes much of computational physics, typically for determining critical points on energy surfaces. As surrogate (machine learned) models have come of age and taken center stage, global search of optimal parameters (or "hyper parameters") for these models have become concomitantly more important. For most systems (including neural networks) finding optimal hyper parameters is far from easy. Most implementations focus on using first order search methods (e.g. batch stochastic gradient methods). We demonstrate the applicability of simulated annealing (via a new, high performance anneal python package) to the problem of finding minima in both hyper parameter surfaces and standard energy systems. Our approach is unique in that it demonstrates the coupling (at a computational implementation level) of the related concept of Metropolis Hasting sampling and its connections to simulated annealing. We will introduce several standard paradigms and demonstrate how these can be "lifted" into a unified framework using object-oriented programming in Python. We demonstrate how clean, inter operable, reproducible programming libraries can be used to access and rapidly iterate on variants of Simulated Annealing in a manner which can be extended to serve as a best practices blueprint or design pattern for a data-driven optimization library.   

Evaluating YOLO Object Detection Models Under Adverse Lighting Conditions

This research looks at the problems that You Only Look Once (YOLO) object recognition models have when they have to work in adverse lighting. Even though YOLO models are generally very good at finding items, they have shown that they are not very good at identifying things when the lighting is bright or changes. Most of the study that has been done so far has focused on finding the best conditions for object detection algorithms, which has left a major knowledge gap. In order to fill this gap, the main goal of this study is to carefully look at how well YOLO models work when lighting conditions aren't ideal. It is very important to understand these limits because they have big effects on real-world situations, like how safe self-driving cars are when the lighting changes and how well security systems work. The main objective of the study is to make object detection algorithms like YOLO more reliable and robust in a wide range of environmental situations.   

Training Convolutional Neural Networks with the Forward-Forward algorithm

The recent successes in analyzing images with deep neural networks are almost exclusively achieved with Convolutional Neural Networks (CNNs). The training of these CNNs, and in fact of all deep neural network architectures, uses the backpropagation algorithm where the output of the network is compared with the desired result and the difference is then used to move the weights of the network towards the desired outcome. In a 2022 preprint, Geoffrey Hinton suggested an alternative way of training which passes the desired results together with the images at the input of the network. This so called Forward Forward (FF) algorithm has up to now only been used in fully connected networks. In this paper, we show how the FF paradigm can be extended to CNNs. Our FF-trained CNN achieves a classification accuracy of 99.0% on the MNIST hand-written digits dataset. We show how different hyperparameters affect the performance of the proposed algorithm and compare the results with the standard backpropagation approach. Furthermore, we use Class Activation Maps to investigate which type of features are learnt by the FF algorithm.   

Flexural modes at the photon sphere of a black hole

The spacetime curvature in the vicinity of massive black holes induces the bending of ray trajectories and the trapping of light in a specific region of space called the photon sphere. We mimic in the laboratory the behavior of waves near a black hole by investigating the modes of vibration on a 3D curved surface corresponding to a particular metric of the black hole. This surface can be transformed to a flat disk with non-uniform distribution of refractive index. Here, we consider elastic waves guided in a thin plate with non-uniform thickness, which corresponds to a varying velocity. Selective laser melting has been used to 3D-print our model with an aluminum alloy. A short pulse is propagated, and the spatiotemporal profile of the velocity-field is recorded by scanning a laser vibrometer. The quasimodes of the system are obtained by modal analysis in the Fourier domain. We find two different classes of modes: (1) Modes similar to the eigensolutions of a uniform disk, including whispering gallery modes; (2) Modes strongly confined within the plate, along a circle with radius corresponding to the photon sphere. Interestingly, this radius is frequency dependent, which is supported by our theory in the regime of wave optics. These observations are supported by full 3D numerical simulations. This work reveals a new type of high-Q modes scared on the stable or unstable orbits, which offers interesting perspective for laser design, inspired from celestial objects.   

Climate network analysis of extreme events: Tropical Cyclones

We construct climate networks based on surface air temperature data to identify distinct signatures of tropical cyclones in the region of the Indian Ocean, which have serious economic and ecological consequences. The climate network shows a discontinuous phase transition in the size of the normalised largest cluster and the susceptibility during cyclonic events. We analyze these quantities for a year (2016) which had three successive cyclones, viz. Cyclone Kyant, cyclone Nada and cyclone Vardah, and compare these with a year  (2017) where a single cyclone, cyclone Okhi was seen. The microtransitions in these two cases show distinct patterns. The signatures of the cyclones can be seen in other quantities like the degree distributions and other network characterizers. The distribution of teleconnections show a distinct behaviour in the cyclonic periods. Similarly, the distribution of nodes of high degree shows distinct behaviour in cyclonic and recyclonic periods. These three cyclones were seen in the Bay of Bengal. We also compare these with a cyclone, cyclone Ashoba (2015), seen in the Arabian sea where cyclones are rarer. We discuss the implications  of these results for further analysis.

Work done in collaboration with Rupali Sonone   

Discovering the True Nature of Forces and Energies (The Unity of All of Them)

There are four fundamental forces that are shaping the universe that we live in it. In this paper we are going to show that the basis of them are photon.

1. Gravitational force

If we want to imagine this force, we can say that the gravitational force is the same chained photons that are moving between two objects and it causes the effect between these two objects.

2. Magnetic force

If we intend to explain the structure of the magnetic force, we have to say that the magnetic force is the same invisible chained photons that go from pole N to S.

3. Coulomb force

The electrons are made up of photons, it can be said that this source of charge is the same photons that make up electrons. Considering that charge is the number of electrons, and the electrons are composed of photons, then it can be said that the electric charge force is the same effect of the displacement of photons.

4. Nuclear force

According to what has already been said about the structure of the nucleus, the nucleus is composed of neutrons and protons that are arranged in a special way next to each other by the Coulomb force. It is clear that the nuclear force (weak and strong) is the same Coulomb force between neutrons and protons of the nucleus, which are rotating at a speed near to the speed of light, and these neutrons and protons themselves are also composed of photons.