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At least 325 records · Page 18

Fractional Quantum Hall Effect in Weyl Semimetals

Weyl semimetal may be thought of as a gapless topological phase protected by the chiral anomaly, where the symmetries involved in the anomaly are the U(1) charge conservation and the crystal translational symmetry. The absence of a band gap in a weakly interacting Weyl semimetal is mandated by the electronic structure topology and is guaranteed as long as the symmetries and the anomaly are intact. The nontrivial topology also manifests in the Fermi arc surface states and topological response, in particular taking the form of an anomalous Hall effect in magnetic Weyl semimetals, whose magnitude is only determined by the location of the Weyl nodes in the Brillouin zone. In this work, we consider the situation when the interactions are not weak and ask whether it is possible to open a gap in a magnetic Weyl semimetal while preserving its nontrivial electronic structure topology along with the translational and the charge conservation symmetries. Surprisingly, the answer turns out to be yes. The resulting topologically ordered state provides a nontrivial realization of the fractional quantum Hall effect in three spatial dimensions in the absence of an external magnetic field, which cannot be viewed as a stack of two dimensional states. Our state contains loop excitations with nontrivial braiding statistics when linked with lattice dislocations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Correlating Macro and Atomic Structure with Elastic Properties and Ionic Transport of Glassy Li 2 S‐P 2 S 5 (LPS) Solid Electrolyte for Solid‐State Li Metal Batteries

Abstract A combination of high ionic conductivity and facile processing suggest that sulfide‐based materials are promising solid electrolytes that have the potential to enable Li metal batteries. Although the Li 2 S‐P 2 S 5 (LPS) family of compounds exhibit desirable characteristics, it is known that Li metal preferentially propagates through microstructural defects, such as particle boundaries and/or pores. Herein, it is demonstrated that a near theoretical density (98% relative density) LPS 75‐25 glassy electrolyte exhibiting high ionic conductivity can be achieved by optimizing the molding pressure and temperature. The optimal molding pressure reduces porosity and particle boundaries while preserving the preferred amorphous structure. Moreover, molecular rearrangements and favorable Li coordination environments for conduction are attained. Consequently, the Young's Modulus approximately doubles (30 GPa) and the ionic conductivity increases by a factor of five (1.1 mS cm −1 ) compared to conventional room temperature molding conditions. It is believed that this study can provide mechanistic insight into processing‐structure‐property relationships that can be used as a guide to tune microstructural defects/properties that have been identified to have an effect on the maximum charging current that a solid electrolyte can withstand during cycling without short‐circuiting.

Garcia‐Mendez, Regina↗

Learning Nonlinear Reduced Models from Data with Operator Inference

This review discusses Operator Inference, a nonintrusive reduced modeling approach that incorporates physical governing equations by defining a structured polynomial form for the reduced model, and then learns the corresponding reduced operators from simulated training data. The polynomial model form of Operator Inference is sufficiently expressive to cover a wide range of nonlinear dynamics found in fluid mechanics and other fields of science and engineering, while still providing efficient reduced model computations. The learning steps of Operator Inference are rooted in classical projection-based model reduction; thus, some of the rich theory of model reduction can be applied to models learned with Operator Inference. This connection to projection-based model reduction theory offers a pathway toward deriving error estimates and gaining insights to improve predictions. Furthermore, through formulations of Operator Inference that preserve Hamiltonian and other structures, important physical properties such as energy conservation can be guaranteed in the predictions of the reduced model beyond the training horizon. This review illustrates key computational steps of Operator Inference through a large-scale combustion example.

Mechanics↗

A divergent synthetic route to functional copolymer libraries via modular polymers

High-throughput polymer synthesis enables rapid exploration of chemical space but remains limited by batch-to-batch inconsistencies that can obscure structure–property relationship trends. To address this challenge, we developed a synthetic approach to produce multifunctional copolymers using post-polymerization modification of activated ester modular polymers with commercially available amines. Easily derivitized parent polymers—poly(tetrafluorophenyl acrylate) and poly(tetrafluorophenyl styrene sulfonate)—were synthesized by RAFT polymerization to yield single polymer batches containing highly reactive tetrafluorophenyl esters or sulfonate esters on each repeat unit. Tuning post-polymerization modification reaction conditions enabled the addition of sub-stoichiometric amounts of amines (relative to the repeat unit) to yield partially functionalized intermediates that could then be further derivatized. Reaction monitoring by 19 F NMR spectroscopy confirmed good control over these sequential post-polymerization modifications. This synthetic route produced a variety of copolymers with defined comonomer ratios while preserving the underlying polymer structure (degree of polymerization, dispersity, tacticity) for both the acrylate and styrene sulfonate backbones. We further applied this approach in a divergent manner to create a small library of structurally distinct copolymers from a single parent batch in three synthetic steps. This modular, divergent synthesis demonstrates a general route to structurally consistent copolymer libraries that enable systematic studies of structure–property relationships and can accelerate functional materials discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A hybrid porous model for full reactor core scale CFD investigation of a prismatic HTGR

Three-dimensional (3-D) Computational Fluid Dynamics (CFD) analysis of a whole nuclear reactor core is a tremendous challenge due to the large geometric volume and complex structures. Here, this research presents a hybrid porous (HP) model to simplify a prismatic High Temperature Gas-cooled Reactor (HTGR) core, so 3-D CFD investigation can be performed on a full reactor core scale. In the HP model, the prototypic small coolant channels in the nuclear fuel blocks are lumped together to form multiple equivalent large coolant channels, and then the porous medium flow model is applied to each of them. Therefore, heat transfer in fuel blocks is computed by a hybrid combination of solid energy and porous flow energy equations. The similarity between the HP model and prototypic model is achieved by deriving the porous flow permeability, inertial resistance factor, and artificial thermophysical properties. Compared with the widely used whole porous (WP) flow model, the HP model preserves more realistic geometric structures, and therefore more accurate physical processes. The General Atomics' Modular High Temperature Gas-cooled Reactor (MHTGR) design was chosen as a prototype to demonstrate the methodology. Simulations were performed using the prototypic CFD model and HP model at steady-state forced circulation, steady-state natural circulation, and transient conditions that correspond to normal operation, extended period of pressurized cool down, and short-term transients after reactor shutdown, respectively. The comparison shows good agreement between the HP model and prototypic model in the maximum fuel temperature, average solid temperature, and helium flow rate, which demonstrates the potential applicability of the HP model for a full reactor core scale simulation in the future. As a benefit, the HP model reduces the mesh quantity by a factor of 50 from a prototypic model. Correspondingly, the computation time was reduced by a factor of at least 30.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Variable-moment fluid closures with Hamiltonian structure

Abstract Based on ideas due to Scovel–Weinstein, I present a general framework for constructing fluid moment closures of the Vlasov–Poisson system that exactly preserve that system’s Hamiltonian structure. Notably, the technique applies in any space dimension and produces closures involving arbitrarily-large finite collections of moments. After selecting a desired collection of moments, the Poisson bracket for the closure is uniquely determined. Therefore data-driven fluid closures can be constructed by adjusting the closure Hamiltonian for compatibility with kinetic simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Inputs to GCAM-USA: IM3 Phase 2 Experiments

Overview This dataset contains XML input files for the IM3 Phase 2 version of GCAM-USA. The files are organized into two categories: Scenario-specific inputs represent hydroclimate and socioeconomic effects on water availability, heating and cooling degree-hours, and agricultural productivity. They support eight IM3 canonical scenarios: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 Model-improvement inputs extend GCAM-USA v5.3 with updated representations of coal and nuclear power plant retirements, electricity trade among U.S. interconnections, offshore carbon storage costs, and groundwater depletion constraints. Data structure Scenario-specific inputs rcp45_runoff/ and rcp85_runoff/XML files describing water availability by HUC2 basin under the RCP 4.5 and RCP 8.5 scenarios. rcp45_hdcd/ and rcp85_hdcd/XML files containing monthly-day and monthly-night heating and cooling degree-hours at the U.S. state level for different RCP-SSP combinations. rcp45_agyields/ and rcp85_agyields/XML files describing changes in agricultural productivity at the intersection of GCAM regions and HUC2 water basins for different RCP-SSP combinations. rcp45_emissions_pathway/The emissions-constraint XML file used to represent the RCP 4.5 pathway. Model-improvement inputs core_retire/Updates coal-fired power plant retirement schedules based on New England ISO. GCAMUSA_IM3_elec_trade_interconnect.xmlRestricts electricity trade to occur within the ERCOT, WECC, and IE interconnections. nuclear_USA.xmlUpdates the retirement schedules of the Diablo Canyon and Palisades nuclear power plants. high_cost_offshore_carbon.xmlUpdates the assumed cost of offshore carbon storage. water_supply_constrained_gleeson_5pct.xmlReplaces WaterGAP historical groundwater-depletion estimates with data from the Gleeson dataset and limits groundwater extraction to 5% of the available groundwater in each Superwell grid cell. How to use the data This dataset is designed for use with the IM3 version of GCAM-USA. Download or clone GCAM-USA from the IM3 GCAM GitHub repository at https://github.com/IMMM-SFA/gcam-core and check out the gcam-usa-im3 branch. Place the downloaded folder im3scenarios in the gcam-core/input directory while preserving the provided folder structure.

Energy↗

Popigai Impact Structure Modeling: Morphology and Worldwide Ejecta

The approx. 100 km in diameter, 35.7 0.2 Ma old Popigai structure [1], northern Siberia (Russia), is the best-preserved of the large terrestrial complex crater structures containing a central-peak ring [2- 4]. Although remotely located, the excellent outcrops, large number of drill cores, and wealth of geochemical data make Popigai ideal for the general study of the cratering processes. It is most famous for its impact-diamonds [2,5]. Popigai is the best candidate for the source crater of the worldwide late Eocene ejecta [6,7].

Ivanov, B. A.↗

Nanocone-Modified Surface Facilitates Gas Bubble Detachment for High-Rate Alkaline Water Splitting

The significant amount of gas bubbles generated during high-rate alkaline water splitting (AWS) can be detrimental to the process. The accumulation of bubbles will block the active catalytic sites and hinder the ion and electrolyte diffusion, limiting the maximum current density. Furthermore, the detachment of large bubbles can also damage the electrode's surface layer. Here, a general strategy for facilitating bubble detachment is demonstrated by modifying the nickel electrode surface with nickel nanocone nanostructures, which turns the surface into underwater superaerophobic. Simulation and experimental data show that bubbles take a considerably shorter time to detach from the nanocone-modified nickel foil than the unmodified foil. As a result, these bubbles also have a smaller detachment size and less chance for bubble coalescence. The nanocone-modified electrodes, including nickel foil, nickel foam, and 3D-printed nickel lattice, all show substantially reduced overpotentials at 1000 mA cm -2 compared to their pristine counterpart. The electrolyzer assembled with two nanocone-modified nickel lattice electrodes retains >95% of the performance after testing at ≈900 mA cm -2 for 100 h. In conclusion, the surface NC structure is also well preserved. The findings offer an exciting and simple strategy for enhancing the bubble detachment and, thus, the electrode activity for high-rate AWS.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Origin of Electrochemical Activation Leading to Enhanced Cycling Stability of Li‐ and Mn‐Rich Cathodes

Electrochemical activation is a critical step for optimal functioning of Li- and Mn-rich (LMR) cathodes, yet the underlying mechanism for such activation remains elusive. Here, by using scanning/transmission electron microscopy (S/TEM) combined with the associated energy-dispersive x-ray spectroscopy (EDS) and electron energy-loss spectroscopy (EELS), we decipher the origin of the activation enhanced electrochemical properties. We reveal that activation induces the formation of a spinel-like phase within the C2/m domains of the LMR cathode, where the transition-metal ions partially occupy both the tetrahedral (8a) and octahedral (16c) sites of the $Fd\bar{3}m$ spinel lattice, distinguishing the spinel-like phase from the conventional high-voltage spinel. Systematic varying the cycling voltage reveals a critical activation voltage above which this spinel-like phase forms, while lower voltages preserve the layered bulk structure. As the spinel-like phase is a stable structure for electrochemical cycling, the present findings provide direct mechanistic insight into the voltage-dependent activation process and explain how the C2/m to spinel-like transformation upon activation contributes to the electrochemical performance of LMR cathodes, providing guidance for the rational design of Li-rich cathodes with enhanced cycling durability.

Li-rich and Mn-rich cathode↗

Biocompatible organosolv fractionation via a novel alkaline lignin-first strategy towards lignocellulose valorization

Simultaneous valorization of both carbohydrate and lignin fractions in lignocellulose remains a great challenge. Herein, a novel lignin-first strategy using triethylene glycol (TEG) under alkaline conditions for effective biomass fractionation producing highly digestible carbohydrates and reactive lignin was developed. Delignification was over 80% and fermentable sugar yields were close to 90% after pretreatment at 90°C. The biocompatibility of TEG allowed direct enzymatic hydrolysis of the solid residue without washing, thus minimizing wastewater generation. Furthermore, the obtained lignin (TEGL) had an uncondensed structure with well-preserved β-O-4 linkage, leading to near-equal aromatic monomer yields compared to cellulolytic enzyme lignin after catalytic-free pyrolysis, demonstrating high valorization potential. Finally, the proposed TEG solvent system is promising for a green and sustainable biorefinery process to achieve the complete utilization of lignocellulose.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Low rank approximation in simulations of quantum algorithms

Simulating quantum algorithms on classical computers is challenging when the system size, i.e., the number of qubits used in the quantum algorithm, is moderately large. However, some quantum algorithms and the corresponding quantum circuits can be simulated efficiently on a classical computer if the input quantum state is a low rank tensor and all intermediate states of the quantum algorithm can be represented or approximated by low rank tensors. Here, in this paper, we examine the possibility of simulating a few quantum algorithms by using low-rank canonical polyadic (CP) decomposition to represent the input and all intermediate states of these algorithms. Two rank reduction algorithms are used to enable efficient simulation. We show that some of the algorithms preserve the low rank structure of the input state and can thus be efficiently simulated on a classical computer. However, the rank of the intermediate states in other quantum algorithms can increase rapidly, making efficient simulation more difficult. To some extent, such difficulty reflects the advantage or superiority of a quantum computer over a classical computer. As a result, understanding the low rank structure of a quantum algorithm allows us to identify algorithms that can benefit significantly from quantum computers.

97 MATHEMATICS AND COMPUTING↗

Site-Selective Modification of Lanthanum Oxychloride to Modulate Halide-Ion Conduction

Design principles for solid-state halide-ion conduction remain poorly defined despite the increasing importance of halide ions as charge carriers in a variety of energy storage and electrochemical computing technologies. Here, we employ a siteselective modification strategy in which aliovalent cations are preferentially introduced at the La 3+ crystallographic site of LaOCl in the 2c Wyckoff position, enabling controlled generation of chloride vacancies and modification of lattice dynamics to enhance chloride-ion conductivity. Aliovalent substitution of La 3+ with Mg 2+ , Ca 2+ , and Sr 2+ generates charge-compensating Cl vacancies while preserving the matlockite crystal structure. X-ray excited optical luminescence measurements with Dy 3+ as a reporter chromophore evidence vacancy-derived midgap electronic states and an extended energy range of radiation-less Auger electron emission corresponding to substantial modification of electronic structure and local electrostatic potentials. Ca alloying at 8−10 at. % increases the chloride-ion conductivity by three- to 4 orders of magnitude as compared to unalloyed LaOCl, whereas comparable amounts of Sr- and Mg-alloying in LaOCl imbue less pronounced conductivity enhancements. Temperature-dependent Raman spectroscopy measurements reveal that Ca- and Sr-alloying substantially soften the La−Cl sublattice and yield a more compliant crystal lattice that can deform to accommodate Cl-ion migration. Structure solutions derived from Rietveld refinements to powder Xray diffraction reveal larger O−La−Cl bond-angle deviations and enhanced out-of-plane cation displacements for Ca- and Sr-alloyed compositions as compared to Mg-alloyed LaOCl. Such local distortions enhance chloride-ion mobility by reshaping and flattening vacancy migration energy landscapes and by modulating lattice dynamics governing anion conduction. We further illustrate that coalloying of Ca with Mg and Sr induces a nonmonotonic conductivity−defect stoichiometry relationship that can be rationalized based on cooperative interactions. Together, these results establish site-selective aliovalent alloying of LaOCl as an effective route to halide-ion solid electrolytes and provide broadly generalizable design principles for site-selective modification to induce vacancy formation and lattice softening to engender facile anion transport

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Geometric transformation and three-dimensional hopping of Hopf solitons

Arising in many branches of physics, Hopf solitons are three-dimensional particle-like field distortions with nontrivial topology described by the Hopf map. Despite their recent discovery in colloids and liquid crystals, the requirement of applied fields or confinement for stability impedes their utility in technological applications. Here we demonstrate stable Hopf solitons in a liquid crystal material without these requirements as a result of enhanced stability by tuning anisotropy of parameters that describe energetic costs of different gradient components in the molecular alignment field. Nevertheless, electric fields allow for inter-transformation of Hopf solitons between different geometric embodiments, as well as for their three-dimensional hopping-like dynamics in response to electric pulses. Numerical modelling reproduces both the equilibrium structure and topology-preserving out-of-equilibrium evolution of the soliton during switching and motions. Our findings may enable myriads of solitonic condensed matter phases and active matter systems, as well as their technological applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Converting tabular data into images for deep learning with convolutional neural networks

Abstract Convolutional neural networks (CNNs) have been successfully used in many applications where important information about data is embedded in the order of features, such as speech and imaging. However, most tabular data do not assume a spatial relationship between features, and thus are unsuitable for modeling using CNNs. To meet this challenge, we develop a novel algorithm, image generator for tabular data (IGTD), to transform tabular data into images by assigning features to pixel positions so that similar features are close to each other in the image. The algorithm searches for an optimized assignment by minimizing the difference between the ranking of distances between features and the ranking of distances between their assigned pixels in the image. We apply IGTD to transform gene expression profiles of cancer cell lines (CCLs) and molecular descriptors of drugs into their respective image representations. Compared with existing transformation methods, IGTD generates compact image representations with better preservation of feature neighborhood structure. Evaluated on benchmark drug screening datasets, CNNs trained on IGTD image representations of CCLs and drugs exhibit a better performance of predicting anti-cancer drug response than both CNNs trained on alternative image representations and prediction models trained on the original tabular data.

59 BASIC BIOLOGICAL SCIENCES↗

Transfer learning nonlinear plasma dynamic transitions in low dimensional embeddings via deep neural networks

Deep learning algorithms provide a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. Development of novel, data-driven model reduction methods, coupled with detection of abnormal modes with plasma physics, opens a unique opportunity to identify plasma instabilities through automated construction of parsimonious models that can be tuned to balance accuracy and cost. Our fusion transfer learning (FTL) model demonstrates success in rapidly reconstructing nonlinear kink mode structures by learning from a limited amount of nonlinear simulation data. The knowledge transfer process leverages a pre-trained neural encoder–decoder network, initially trained on linear simulations, to effectively capture nonlinear dynamics. The low-dimensional embeddings extract the coherent structures of interest, while preserving the inherent dynamics of the complex system. Experimental results highlight FTL’s capacity to capture transitional behaviors and dynamical features in plasma dynamics—a task often challenging for conventional methods. The model developed in this study is generalizable and can be extended broadly through transfer learning to address various magnetohydrodynamics modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Lattice symmetry breaking transition and critical size limit for ferroic orders in nanophase BiFeO3

Finite size effects on the ferroic orders in BiFeO 3 are studied by atomic pair distribution function analysis and magnetic measurements. While bulk rhombohedral BiFeO 3 exhibits ferroelectricity and antiferromagnetism with a cycloidal magnetic moment arrangement leading to zero magnetization and weak magnetoelectric coupling, BiFeO 3 nanoparticles with a size smaller than the spin cycloid period of 62 nm preserve their polar rhombohedral structure and develop ferromagnetism, thus exhibiting coexisting polarization and nonzero magnetization that enhances the magnetoelectric coupling. When the nanoparticles become smaller than 17 nm, however, their crystal lattice expands and becomes nonpolar cubic. They also become superparamagnetic and thus simultaneously cease exhibiting both ferroelectricity and ferromagnetism. Our findings shed light on the interaction between the lattice structure and ferroic orders in nanophase perovskites and also provide a rare example of a lattice symmetry breaking phase transition that determines their critical size.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Euclidean formulation of relativistic quantum mechanics of N particles

A Euclidean formulation of relativistic quantum mechanics for systems of a finite number of degrees of freedom is discussed. Relativistic treatments of quantum theory are needed to study hadronic systems at subhadronic distance scales. While direct interaction approaches to relativistic quantum mechanics have proved to be useful, they have two disadvantages. One is that cluster properties are difficult to realize for systems of more than two particles. The second is that the relation to quantum field theories is indirect. Euclidean formulations of relativistic quantum mechanics provide an alternative representation that does not have these difficulties. More surprising, the theory can be formulated entirely in the Euclidean representation without the need for analytic continuation. In this work a Euclidean representation of a relativistic N-particle system is discussed. Kernels for systems of N free particles of any spin are given and shown to be reflection positive. Explicit formulas for generators of the Poincaré group for any spin are constructed and shown to be self-adjoint on the Euclidean representation of the Hilbert space. The structure of correlations that preserve both the Euclidean covariance and reflection positivity is discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗