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At least 235 records · Page 13

Pseudogap behavior in charge density wave kagome material ScV 6 Sn 6 revealed by magnetotransport measurements

Over the last few years, significant attention has been devoted to studying the kagome materials A V 3 Sb 5 (A = K, Rb, Cs) due to their unconventional superconductivity and charge density wave (CDW) ordering. Recently $ScV_{6}Sn_{6}$ was found to host a CDW below ≈ 90 K, and, like A V 3 Sb 5 , it contains a kagome lattice comprised only of V ions. Here we present a comprehensive magnetotransport study on $ScV_{6}Sn_{6}$. We discovered several anomalous transport phenomena above the CDW ordering temperature, including insulating behavior in interlayer resistivity, a strongly temperature-dependent Hall coefficient, and a violation of Kohler’s rule. All these anomalies can be consistently explained by a progressive decrease in carrier densities with decreasing temperature, suggesting the formation of a pseudogap. Our findings suggest that high-temperature CDW fluctuations play a significant role in determining the normal state electronic properties of $ScV_{6}Sn_{6}$.

36 MATERIALS SCIENCE↗

Sign-tunable anomalous Hall effect induced by two-dimensional symmetry-protected nodal structures in ferromagnetic perovskite thin films

Magnetism and spin-orbit coupling are two quintessential ingredients underlying topological transport phenomena in itinerant ferromagnets. When spin-polarized bands support nodal points/lines with band degeneracy that can be lifted by spin-orbit coupling, the nodal structures become a source of Berry curvature, leading to a large anomalous Hall effect. However, two-dimensional systems can possess stable nodal structures only when proper crystalline symmetry exists. Here, in this study, we show that two-dimensional spin-polarized band structures of perovskite oxides generally support symmetry-protected nodal lines and points that govern both the sign and the magnitude of the anomalous Hall effect. To demonstrate this, we performed angle-resolved photoemission studies of ultrathin films of SrRuO 3 , a representative metallic ferromagnet with spin-orbit coupling. We show that the sign-changing anomalous Hall effect upon variation in the film thickness, magnetization and chemical potential can be well explained by theoretical models. Our work may facilitate new switchable devices based on ferromagnetic ultrathin films.

36 MATERIALS SCIENCE↗

Predicting 3D moisture sorption behavior of materials from 1D investigations

Abstract Moisture in materials can be a source of future outgassing and exacerbate unwanted changes in physical and chemical properties. Here, we investigate the effect of sample size and shape on the moisture transport phenomena through a combined experimental and modeling approach. Several different materials varying in size and shape were investigated over a wide range of relative humidities (0–90%) and temperatures ( $$30{-}70^{\,\circ } \hbox {C}$$ 30 - 70 ∘ C ) using gravimetric type dynamic vapor sorption (DVS). A dynamic triple-mode sorption model, developed previously, was employed to describe the experimental results with good success; the model includes absorption, adsorption, pooling (clustering) of species, and molecular diffusion. Here we show that the full triple-mode sorption model is robust enough to predict the dynamic uptake and outgassing of 3-dimensional (3D) samples using parameters derived from quasi-1D samples. This successful demonstration on three different materials (filled polydimethylsiloxane (PDMS), unfilled PDMS, and ceramic inorganic composite) illustrates that the model is robust at describing the scale-independent physics and chemistry of moisture sorption and diffusion materials. This work demonstrates that while sorption mechanisms manifest in testing of all sample sizes, some of these mechanisms were so subtle that they were overlooked in our initial modeling and assessment, illustrating the importance of multi-scale experiments in the development of robust predictive capabilities. Our study also outlines the challenges and viable solutions for global optimization of a multi-parameter model. The ability to quantify moisture sorption and diffusion, independent of scale, using 1D lab-scale experiments enables prediction of long-term bulk materials behavior in real applications.

36 MATERIALS SCIENCE↗

Variational multiscale reinforcement learning for discovering reduced order closure models of nonlinear spatiotemporal transport systems

Abstract A central challenge in the computational modeling and simulation of a multitude of science applications is to achieve robust and accurate closures for their coarse-grained representations due to underlying highly nonlinear multiscale interactions. These closure models are common in many nonlinear spatiotemporal systems to account for losses due to reduced order representations, including many transport phenomena in fluids. Previous data-driven closure modeling efforts have mostly focused on supervised learning approaches using high fidelity simulation data. On the other hand, reinforcement learning (RL) is a powerful yet relatively uncharted method in spatiotemporally extended systems. In this study, we put forth a modular dynamic closure modeling and discovery framework to stabilize the Galerkin projection based reduced order models that may arise in many nonlinear spatiotemporal dynamical systems with quadratic nonlinearity. However, a key element in creating a robust RL agent is to introduce a feasible reward function, which can be constituted of any difference metrics between the RL model and high fidelity simulation data. First, we introduce a multi-modal RL to discover mode-dependant closure policies that utilize the high fidelity data in rewarding our RL agent. We then formulate a variational multiscale RL (VMRL) approach to discover closure models without requiring access to the high fidelity data in designing the reward function. Specifically, our chief innovation is to leverage variational multiscale formalism to quantify the difference between modal interactions in Galerkin systems. Our results in simulating the viscous Burgers equation indicate that the proposed VMRL method leads to robust and accurate closure parameterizations, and it may potentially be used to discover scale-aware closure models for complex dynamical systems.

97 MATHEMATICS AND COMPUTING↗

Additive roles of antiferromagnetically coupled elements in the magnetic proximity effect in the GdFeCo/Pt system

Abstract Interfacial magnetic interactions between different elements are the origin of various spin-transport phenomena in multi-elemental magnetic systems. We investigate the coupling between the magnetic moments of the rare-earth, transition-metal, and heavy-metal elements across the interface in a GdFeCo/Pt thin film, an archetype system to investigate ferrimagnetic spintronics. The Pt magnetic moments induced by the antiferromagnetically aligned FeCo and Gd moments are measured using element-resolved x-ray measurements. It is revealed that the proximity-induced Pt magnetic moments are always aligned parallel to the FeCo magnetic moments, even below the ferrimagnetic compensation temperature where FeCo has a smaller moment than Gd. This is understood by a theoretical model showing distinct effects of the rare-earth Gd 4 f and transition-metal FeCo 3 d magnetic moments on the Pt electronic states. In particular, the Gd and FeCo work in-phase to align the Pt moment in the same direction, despite their antiferromagnetic configuration. The unexpected additive roles of the two antiferromagnetically coupled elements exemplify the importance of detailed interactions among the constituent elements in understanding magnetic and spintronic properties of thin film systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

In-plane selective area InSb–Al nanowire quantum networks

Abstract Strong spin–orbit semiconductor nanowires coupled to a superconductor are predicted to host Majorana zero modes. Exchange (braiding) operations of Majorana modes form the logical gates of a topological quantum computer and require a network of nanowires. Here, we utilize an in-plane selective area growth technique for InSb–Al semiconductor–superconductor nanowire networks. Transport channels, free from extended defects, in InSb nanowire networks are realized on insulating, but heavily mismatched InP (111)B substrates by full relaxation of the lattice mismatch at the nanowire/substrate interface and nucleation of a complete network from a single nucleation site by optimizing the surface diffusion length of the adatoms. Essential quantum transport phenomena for topological quantum computing are demonstrated in these structures including phase-coherence lengths exceeding several micrometers with Aharonov–Bohm oscillations up to five harmonics and a hard superconducting gap accompanied by 2 e -periodic Coulomb oscillations with an Al-based Cooper pair island integrated in the nanowire network.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

All hard X-ray transient grating spectroscopy

Optical-domain transient grating (TG) spectroscopy is the ideal tool to investigate transport phenomena in gases, liquids and solids, but it is limited to typically micron-size grating periods. Extreme-Ultraviolet TG has represented a major leap forward to access the mesoscopic scales. Hard X-ray TGs open access in principle to the nanoscale. Hard X-ray TGs were recently generated using the Talbot effect and probed by optical pulses, but these hinder exploiting the advantages of the nanoscale gratings. Here, we present an all-X-ray TG study, in which few-femtosecond hard X-ray pulses are used both for excitation and probing. Our experiment was performed on an amorphous film of an FeGd alloy and on a thin silicon single crystal. The results show a manifestation of the TG induced by the X-ray pump and probe pulses in the form of Talbot carpets, as well as temporal evolution of the grating in crystalline silicon showing coherent optical phonons. Ultrafast all-X-ray TG spectroscopy has the potential to study fundamental excitations with femtosecond time resolution and nanometer spatial sensitivity.

Ferrari, Eugenio [Deutsches Elektronen-Synchrotron↗

Multi-scale physics of bipolar membranes in electrochemical processes

Bipolar membranes (BPMs) enable control of ion concentrations and fluxes in electrochemical cells suitable for a wide range of applications. Here, in this work, we present the multi-scale physics of BPMs in an electrochemical engineering context and articulate design principles to drive the development of advanced BPMs. The chemistry, structure, and physics of BPMs are illustrated and related to the thermodynamics, transport phenomena, and chemical kinetics that dictate ion and species fluxes and selectivity. These interactions give rise to emergent structure–property–performance relationships that yield design criteria for BPMs that achieve high permselectivity, durability, and voltaic efficiency. The resulting performance trade-offs for BPMs are presented in the context of emerging applications in energy conversion or storage, and environmental remediation. By connecting the fundamental physical phenomena in BPMs to device-level performance and engineering, we aim to facilitate the development of next-generation BPMs for sustainable electrochemical processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unraveling membrane electrode assembly design for electrochemical conversion of carbon dioxide to formate/formic acid

This work presents a one-dimensional continuum modeling approach to investigate various cell architectures used for electrochemical conversion of CO 2 to formate/formic acid. Ion transport is simulated by a system of generalized modified Poisson–Nernst–Planck (GMPNP) equations that reflect the reactive transport phenomena including steric effects as the electrolyte solutions become concentrated. In the cathode catalyst layer, ionic current contributions from both the supporting electrolyte and solid-state ionomer are considered. Voltage and CO 2 utilization breakdowns are utilized to deconvolute the impacts of the cell architecture. The origins of (bi)carbonate formation in the cathode are explored, as the subsequent decrease in CO 2 availability is a key reason for low faradaic efficiencies to formate/formic acid. In addition, the role of a supporting electrolyte (KOH) is investigated to understand its tradeoffs: while the K + ions can improve both conductivity and electrochemically active surface area in the cathode, the presence of OH − ions raises the pH and leads to deleterious formation of (bi)carbonates. To this end, we also present parametric studies on the concentration and flow rate of supplied KOH to the cell, to establish a path towards eliminating the need for a supporting electrolyte.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Time reversal symmetry breaking and odd viscosity in active fluids: Green–Kubo and NEMD results

Active fluids, which are driven at the microscale by non-conservative forces, are known to exhibit novel transport phenomena due to the breaking of time reversal symmetry. Recently, Epstein and Mandadapu [arXiv:1907.10041 (2019)] obtained Green-Kubo relations for the full set of viscous coefficients governing isotropic chiral active fluids, including the so-called odd viscosity, invoking Onsager's regression hypothesis for the decay of fluctuations in active non-equilibrium steady states. In this Communication, we test these Green-Kubo relations using molecular dynamics simulations of a canonical model system consisting of actively torqued dumbbells. We find the resulting odd and shear viscosity values from the Green-Kubo relations to be in good agreement with values measured independently through non-equilibrium molecular dynamics flow simulations. This provides a test of the Green-Kubo relations and lends support to the application of the Onsager regression hypothesis in relation to viscous behaviors of active matter systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface chemistry models for GaAs epitaxial growth and hydride cracking using reacting flow simulations

Hydride vapor phase epitaxy (HVPE) is a promising technology that can aid in the cost reduction of III-V materials and devices manufacturing, particularly high-efficiency solar cells for space and terrestrial applications. However, recent demonstrations of ultrafast growth rates (~500 µm/h) via uncracked hydrides are not well described by present models for the growth. Therefore, it is necessary to understand the kinetics of the growth process and its coupling with transport phenomena, so as to enable fast and uniform epitaxial growth. In this work, we derive a kinetic model using experimental data and integrate it into a computational fluid dynamics simulation of an HVPE growth reactor. We also modify an existing hydride cracking model that we validate against numerical simulations and experimental data. Here, we show that the developed growth model and the improved cracking model are able to reproduce experimental growth measurements of GaAs in an existing HVPE system.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS↗

Deep learning-enabled probing of irradiation-induced defects in time-series micrographs

Modeling time-series data with convolutional neural networks (CNNs) requires building a model to learn in batches as opposed to training sequentially. Coupling CNNs with in situ or operando techniques opens the possibility of accurately segmenting dynamic reactions and mass transport phenomena to understand how materials behave under the conditions in which they are used. In this article, in situ ion irradiation transmission electron microscopy (TEM) images are used as inputs into the CNN to assess the defect generation rate, defect cluster density, and saturation of defects. We then use the output segmentation maps to correlate with conventional TEM micrographs to assess the model’s ability to detail nanoscale interactions. Next, we discuss the implications of preprocessing and hyperparameters on model variability, accuracy when expanded to other datasets, and the role of regularization when controlling model variance. Ultimately, we eliminate human bias when extrapolating physical metrics, speed up analysis time, decouple reactions that happen at 100 ms intervals, and deploy models that are both accurate and transferable to similar experiments.

Burns, Kory (ORCID:0000000158019909)↗

Initial position optimization in molecular dynamics simulations for a Coulomb system

A new algorithm for molecular dynamics (MD) simulations is developed to optimize plasma particle distributions at given initial temperatures. By combining velocity scaling and reassignment, the method effectively eliminates the initial rise and oscillation in temperatures observed with randomly distributed positions. These rises and oscillations are undesired numerical artifacts observed in conventional plasma MD simulations, arising from unoptimized particle positions. The algorithm demonstrates temperature relaxation without initial rises or oscillations, as well as precise flow velocity relaxation, enabling accurate measurement of relaxation times. The code is accelerated using graphics processing units for parallel processing, enhancing the study of plasma dynamics. The proposed method for distributing physically valid particles in MD simulations enables accurate studies of intrinsic collision processes in plasmas, including the dynamics of strongly coupled plasmas, plasma–wave interactions, and transport phenomena in magnetized plasmas. The paper concludes with a discussion of potential applications and future enhancements to the algorithm.

Jo, Jawon (ORCID:0009000924193285)↗

Finite-element-based simulations of electrodes for CO 2 cascade reduction reactions

The multielectron reduction of CO 2 to liquid fuels could be a path to scalable energy storage, but reaching this goal requires major advances in catalysis and systems engineering. Cascade catalysis, which couples sequential reactions without isolating intermediates, has emerged as a promising route to enhance selectivity and efficiency in CO 2 reduction (CO 2 R). In this review, we examine how finite-element-based simulations of continuum model [finite element method (FEM)] approaches are being used to analyze and guide CO 2 R cascade systems. We first outline the fundamentals of cascade catalysis and recent advances in catalytic materials (metallic, molecular, and hybrid architectures). We then focus on FEM developments at the electrode and device scales, emphasizing how these models capture transport phenomena, local microenvironments, and geometry-dependent effects. To clarify design principles, we present case studies of cascade electrodes organized in systems without and with integrated semiconductors. We further emphasize the integration of FEM with multiscale frameworks (density functional theory, molecular dynamics, kinetic Monte Carlo) and its role in bridging atomic-level insights with device-level performance. Finally, we identify current limitations and future prospects, including improved boundary conditions, coupling with operando experiments, and machine learning-accelerated model development. Together, these insights provide design principles for next-generation CO 2 R cascade systems for efficient solar fuel production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum interference in superposed lattices

Charge transport in solids at low temperature reveals a material’s mesoscopic properties and structure. Under a magnetic field, Shubnikov–de Haas (SdH) oscillations inform complex quantum transport phenomena that are not limited by the ground state characteristics and have facilitated extensive explorations of quantum and topological interest in two- and three-dimensional materials. Here, in elemental metal Cr with two incommensurately superposed lattices of ions and a spin-density-wave ground state, we reveal that the phases of several low-frequency SdH oscillations in σ xx (ρ xx ) and σ yy (ρ yy ) are no longer identical but opposite. These relationships contrast with the SdH oscillations from normal cyclotron orbits that maintain identical phases between σ xx (ρ xx ) and σ yy (ρ yy ) . We trace the origin of the low-frequency SdH oscillations to quantum interference effects arising from the incommensurate orbits of Cr’s superposed reciprocal lattices and explain the observed π-phase shift by the reconnection of anisotropic joint open and closed orbits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Multiphenomenology explosion monitoring (MultiPEM): a general framework for data interpretation and yield estimation

SUMMARY An underground nuclear explosion (UNE) couples mechanical energy into crustal rock, which propagates as seismic and acoustic waves. These different physical phenomena transport, by different pathways, to standoff detectors at varying distances. The transport pathways attenuate the original signal but in different ways. Enabled by correct statistical weighting, signal attenuation models can be used to combine these disparate sensor data to estimate the yield of an UNE. Contemporaneous statistical models, used in yield estimation, can be improved with an advanced partition of error for these physical signal propagation models. We present an advanced multivariate approach to error modelling of multiphenomenology physical signatures. In addition to measurement error, our error model represents physical model biases as random with a physics-based covariance structure. To illustrate this proposed framework, we demonstrate the estimation of explosion yield using openly available seismic and acoustic data from chemical single-point explosions.

Williams, Brian J.↗

Kinetics of solid–liquid interface motion in molecular dynamics and phase-field models: crystallization of chromium and silicon

The results of molecular dynamics (MD) simulations of the crystallization process in one-component materials and solid solution alloys reveal a complex temperature dependence of the velocity of the crystal–liquid interface featuring an increase up to a maximum at 10–30% undercooling below the equilibrium melting temperature followed by a gradual decrease of the velocity at deeper levels of undercooling. At the qualitative level, such non-monotonous behaviour of the crystallization front velocity is consistent with the diffusion-controlled crystallization process described by the Wilson–Frenkel model, where the almost linear increase of the interface velocity in the vicinity of melting temperature is defined by the growth of the thermodynamic driving force for the phase transformation, while the decrease in atomic mobility with further increase of the undercooling drives the velocity through the maximum and into a gradual decrease at lower temperatures. At the quantitative level, however, the diffusional model fails to describe the results of MD simulations in the whole range of temperatures with a single set of parameters for some of the model materials. The limited ability of the existing theoretical models to adequately describe the MD results is illustrated in the present work for two materials, chromium and silicon. It is also demonstrated that the MD results can be well described by the solution following from the hodograph equation, previously found from the kinetic phase-field model (kinetic PFM) in the sharp interface limit. The ability of the hodograph equation to describe the predictions of MD simulation in the whole range of temperatures is related to the introduction of slow (phase field) and fast (gradient flow) variables into the original kinetic PFM from which the hodograph equation is obtained. The slow phase-field variable is responsible for the description of data at small undercoolings and the fast gradient flow variable accounts for local non-equilibrium effects at high undercoolings. The introduction of these two types of variables makes the solution of the hodograph equation sufficiently flexible for a reliable description of all nonlinearities of the kinetic curves predicted in MD simulations of Cr and Si. This article is part of the theme issue ‘Transport phenomena in complex systems (part 1)’.

Science & Technology - Other Topics↗

Electronic structure complexity and extremely large magnetoresistance in antiferromagnetic semimetal SmAgSb 2

SmAgSb 2 , a layered magnetic semimetal in the tetragonal 𝑅⁢𝑇⁢ Sb 2 family (𝑅 = Y, Sc, rare earth; 𝑇 = transition metal), is known to exhibit extremely large magnetoresistance (XMR) below its antiferromagnetic (AFM) transition temperature. Here, in this work, we present a comprehensive investigation combining magnetotransport measurements, density functional theory calculations accounting for electron correlation, and angle-resolved photoemission spectroscopy. Our results reveal a complex electronic structure characterized by a multiband Fermi surface and intricate magnetic ground states. We demonstrate that simple two-band models, previously employed in the literature, fail to consistently describe the observed transport phenomena. Notably, we report an XMR of approximately 25200% at 2 K under a 14 T magnetic field, significantly exceeding earlier reports for this material family and rivaling the performance of prominent nonmagnetic XMR systems. This pronounced enhancement below 𝑇 𝑁 suggests that the XMR originates from a combination of multiband electron-hole compensation and enhanced magnetic scattering in this correlated AFM semimetal.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗