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At least 793 records · Page 44

Construction of hopfion crystals

Hopfions, three-dimensional topological solitons characterized by nontrivial Hopf indices, represent a fundamental class of field configurations that emerge across diverse areas of physics. Despite extensive studies of isolated hopfions, a framework for constructing spatially ordered arrays of hopfions, i.e., hopfion crystals, has been lacking. Here, we present a systematic approach for generating hopfion crystals with cubic symmetry by combining the Hopf map with rational mapping techniques. By superposing helical waves in ℝ 4 , we construct hopfion crystals with tunable Hopf indices and controllable topology. We demonstrate simple cubic, face-centered cubic, and body-centered cubic hopfion crystals and extend our framework to create crystals of more complex topological structures, including axially symmetric tori, torus links, and torus knots with higher Hopf indices. Our results provide a foundation for searching hopfions in real materials and studying their collective phenomena.

3-dimensional systems↗

Engineering Privacy at the Edge: A Practical Guide to Differential Privacy in System Architectures

The rapid expansion of distributed and edge computing platforms—spanning autonomous vehicles, IoT sensors, and healthcare monitors—has heightened concerns about data privacy. Differential Privacy (DP) offers a rigorous mathematical framework to protect sensitive information while retaining analytical utility. This tutorial introduces the foundations of DP for both numerical and categorical datasets and extends the discussion to correlation-aware techniques tailored for structured and high-dimensional data. Hands-on demonstrations will begin with the PETINA (Privacy prEservaTIoN Algorithms) package for numerical data and continue with MIC-DP (Maximum Information Correlated Differential Privacy) for tabular data. Designed for researchers and practitioners in secure systems, embedded architectures, and AI accelerators, the tutorial emphasizes practical and scalable methods for integrating DP into real-world system designs.

Kotevska, Olivera [ORNL] (ORCID:0000000316772243)↗

Kinetic frustration by limited bond availability controls the LAT protein condensation phase transition on membranes

LAT is a membrane-linked scaffold protein that undergoes a phase transition to form a two-dimensional protein condensate on the membrane during T cell activation. Governed by tyrosine phosphorylation, LAT recruits various proteins that ultimately enable condensation through a percolation network of discrete and selective protein-protein interactions. Here, we describe detailed kinetic measurements of the phase transition, along with coarse-grained model simulations, that reveal that LAT condensation is kinetically frustrated by the availability of bonds to form the network. Unlike typical miscibility transitions in which compact domains may coexist at equilibrium, the LAT condensates are dynamically arrested in extended states, kinetically trapped out of equilibrium. Modeling identifies the structural basis for this kinetic arrest as the formation of spindle arrangements, favored by limited multivalent binding interactions along the flexible, intrinsically disordered LAT protein. These results reveal how local factors controlling the kinetics of LAT condensation enable formation of different, stable condensates, which may ultimately coexist within the cell.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tantalum-stabilized ruthenium oxide electrocatalysts for industrial water electrolysis

The iridium oxide (IrO 2 ) catalyst for the oxygen evolution reaction used industrially (in proton exchange membrane water electrolyzers) is scarce and costly. Although ruthenium oxide (RuO 2 ) is a promising alternative, its poor stability has hindered practical application. Here, we used well-defined extended surface models to identify that RuO 2 undergoes structure-dependent corrosion that causes Ru dissolution. Tantalum (Ta) doping effectively stabilized RuO 2 against such corrosion and enhanced the intrinsic activity of RuO 2 . In an industrial demonstration, Ta-RuO 2 electrocatalyst exhibited stability near that of IrO 2 and had a performance decay rate of ~14 microvolts per hour in a 2800-hour test. At current densities of 1 ampere per square centimeter, it had an overpotential 330 millivolts less than that of IrO 2 .

Zhang, Jiahao [Sichuan Univ., Chengdu (China); Uni↗

3D diffractive imaging of nanoparticle ensembles using an x-ray laser

Single particle imaging at x-ray free electron lasers (XFELs) has the potential to determine the structure and dynamics of single biomolecules at room temperature. Two major hurdles have prevented this potential from being reached, namely, the collection of sufficient high-quality diffraction patterns and robust computational purification to overcome structural heterogeneity. We report the breaking of both of these barriers using gold nanoparticle test samples, recording around 10 million diffraction patterns at the European XFEL and structurally and orientationally sorting the patterns to obtain better than 3-nm-resolution 3D reconstructions for each of four samples. With these new developments, integrating advancements in x-ray sources, fast-framing detectors, efficient sample delivery, and data analysis algorithms, we illuminate the path towards sub-nanometer biomolecular imaging. The methods developed here can also be extended to characterize ensembles that are inherently diverse to obtain their full structural landscape.

47 OTHER INSTRUMENTATION↗

xCDAT: A Python Package for Simple and Robust Analysis of Climate Data

xCDAT (Xarray Climate Data Analysis Tools) is an open-source Python package that extends Xarray (Hoyer & Hamman, 2017) for climate data analysis on structured grids. xCDAT streamlines analysis of climate data by exposing common climate analysis operations through a set of straightforward APIs. Some of xCDAT’s key features include spatial averaging, temporal averaging, and regridding. These features are inspired by the Community Data Analysis Tools (CDAT) library (Dean N. Williams et al., 2009) (D. N. Williams, 2014) (Doutriaux et al., 2019) and leverage powerful packages in the Xarray ecosystem including xESMF (Zhuang et al., 2023), xgcm (Abernathey et al., 2022), and CF xarray (Cherian et al., 2023). To ensure general compatibility across various climate models, xCDAT operates on datasets that are compliant with the Climate and Forecast (CF) metadata conventions (Hassell et al., 2017).

54 ENVIRONMENTAL SCIENCES↗

Single-molecule 3D imaging of HIV cellular entry by liquid-phase electron tomography

Enveloped viruses, including human immunodeficiency virus (HIV) and SARS-CoV-2, target cells through membrane fusion process. The detailed understanding of the process is sought after for vaccine development but remains elusive due to current technique limitations for direct three-dimensional (3D) imaging of an individual virus during its viral entry. Recently, we developed a simple specimen preparation method for real-time imaging of metal dynamic liquid-vaper interface at nanometer resolution by transmission electron microscopy (TEM). Here, we extended this method to study biology sample through snapshot 3D structure of a single HIV (pseudo-typed with the envelope glycoprotein of vesicular stomatitis virus, VSV-G) at its intermediate stage of viral entry to HeLa cells in a liquid-phase environment. By individual-particle electron tomography (IPET), we found the viral surface release excess lipids with unbound viral spike proteins forming ~50-nm nanoparticles instead of merging cell membrane. Moreover, the spherical-shape shell formed by matrix proteins underneath the viral envelope does not disassemble into a cone shape right after fusion. Further, the snapshot 3D imaging of a single virus provides us a direct structure-based understanding of the viral entry mechanism, which can be used to examine other viruses to support the development of vaccines combatting the current ongoing pandemic.

Kong, Lingli↗

VERA-Grizzly Ex-Core Calculations: Watts Bar Unit 1 Cycles 1-2

The critical structures that comprise light-water reactor (LWR) nuclear power plants are subjected to operating environments that can challenge their integrity. Structures in close proximity to the reactor core, such as the reactor pressure vessel (RPV) and the biological shield wall, are subjected to high levels of radiation emanating from the core, as well as elevated temperatures. As the US fleet of operating LWRs ages, the effects of these operating environments on the integrity of these structures must be considered to ensure their continued safe operation. Extending the lifetime of commercial reactors and maintaining the aging reactor fleet require accurate prediction of the exposure of ex-core components to neutron and photon radiation. In particular, concrete degradation studies must be performed to evaluate the safety and long-term operation of reactors with lifetime extensions. The concrete reactor bioshield is important for providing radiological protection during operation and must last for the entire lifetime of the reactor. Recent interest in lifetime extensions furthers the need to accurately simulate concrete material degradation in the reactor bioshield. As a result of this need, the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has funded this study to couple its tools, Virtual Environment for Reactor Applications (VERA) and Grizzly. VERA allows users to set up models to calculate time-dependent and fully coupled solutions (with thermal feedback) for ex-core quantities of interest such as vessel and coupon fluence and detector responses for multiple statepoints and cycles. Grizzly is a finite-element application based on the Multiphysics Object Oriented Simulation Environment (MOOSE) framework that is used to enable aging materials calculations. This report highlights the work performed to calculate the fluence in the vessel and concrete for Watts Bar Nuclear Plant Unit 1 (WBN1) Cycles 1 and 2. The fluences obtained from VERA were successfully transferred to Grizzly using a Python script. Four simulations were run with Grizzly: (1) the Mazars model with the initial Young’s modulus being the instantaneous modulus, (2) the Mazars model with the initial Young’s modulus being the delayed modulus, (3) the Mazars model with the initial Young’s modulus being the delayed modulus with the addition of the effects of micro-damage caused by irradiation, and (4) the Mazars model with the initial Young’s modulus being the instantaneous modulus, and with the addition of micro-damage and creep. Details regarding the methods used to obtain the fluence and the statistical errors associated with the VERA Monte Carlo Shift calculations are discussed in greater detail in this report. The results obtained from the four Grizzly models are also presented in this report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Ultrasonic Deterrents To Reduce Bat Mortality at Wind Turbines - Short Science Summary

In North America, several bat species commonly collide with operating turbines. Though the ultimate driver of collisions is unknown, studies suggest that bats may be attracted to turbines because they often approach and spend extended periods of time (seconds to minutes) interacting with turbine structures. To reduce bat mortality at wind farm operators, seek to reduce mortality rates by reducing the amount of time that bats interact with spinning turbine blades (or exposure). Current approaches to reduce exposure include curtailment, whereby turbine operators stop turbine rotors from spinning during periods when bats are expected to be at the highest risk of collision, and deterrent technologies that seek to discourage bats from entering/ limit the amount of time spent within the rotor swept area. We briefly describe the state of the science on ultrasonic deterrent technology, highlight potential drivers of variable efficacy for bat mortality reduction, and suggest next steps focus on identifying the driver(s) of such variability.

bats↗

Effects of catalyst droplets on wire growth and the resulting branched structures during VLS growth

Vapor-liquid-solid (VLS) method is vastly employed to grow hierarchical structures with unique properties. However, key questions remain, such as what controls the branched structures and what the roles of catalyst droplet size are during the growth. Here, an in-depth understanding of the kinetics of the nucleation, growth, and subsequent coalescence processes of Bi liquid catalyst droplets is provided by direct observation of PbSe branched wire growth in an environmental transmission electron microscope. This brings a kinetic control of the branch density by varying the parameters, such as temperature. In addition, the dependence of wire growth rate on the catalyst droplet size is revealed, i.e., the smaller the catalyst size the larger the wire growth rate, unlike the wire growth controlled by Gibbs-Thomson effect, possibly due to different mass transport pathways and atomic surface diffusion. These results extend the fundamental understanding of the VLS growth mechanism of branched structures and benefit the structure design of hierarchical materials with tailored properties.

36 MATERIALS SCIENCE↗

Understanding the Mesoscale Degradation in Nickel-Rich Cathode Materials through Machine-Learning-Revealed Strain–Redox Decoupling

The degradation of nickel-rich cathode materials for lithium-ion batteries upon prolonged electrochemical cycling features a complicated interplay among electronic structure, lattice configuration, and micro-morphology. The underlying mechanism for such an entanglement of different material properties at nano- to mesoscales is fundamental to the battery performance but not well-understood yet. Here we investigate the correlation between the local redox reaction and lattice mismatch through a nano-resolution synchrotron spectro-microscopy study of LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NCM 811) cathode particles. With assistance from a machine-learning-based data classification method, we identify local regions that demonstrate a strain–redox decoupling effect, which can be attributed to different side reactions. Overall, our results highlight the mesoscale reaction heterogeneity in the battery cathode and suggest that particle structure engineering could be a viable approach to mitigate the chemomechanical degradation of cathode materials.

25 ENERGY STORAGE↗

Automated Construction of Artificial Lattice Structures with Designer Electronic States

Manipulating matter with a scanning tunneling microscope (STM) enables the creation of atomically defined artificial structures that host designer quantum states. However, the time-consuming nature of the manipulation process, coupled with the sensitivity of the STM tip, constrains the exploration of diverse configurations and limits the size of the designed features. In this study, we present a reinforcement learning (RL)-based framework for creating artificial structures by spatially manipulating carbon monoxide (CO) molecules on a copper substrate by using the STM tip. The automated workflow combines molecule detection and manipulation, employing deep-learning-based object detection to locate CO molecules and linear assignment algorithms to allocate these molecules to designated target sites. We initially perform molecule maneuvering based on randomized parameter sampling for sample bias, tunneling current set point, and manipulation speed. This data set is then structured into an action trajectory used to train an RL agent. The model is subsequently deployed on the STM for real-time fine-tuning of the manipulation parameters during structure construction. Our approach incorporates path-planning protocols coupled with active drift compensation to enable atomically precise fabrication of structures with significantly reduced human input while realizing larger-scale artificial lattices with the desired electronic properties. Furthermore, using our approach, we demonstrate the automated construction of an extended artificial graphene lattice and confirm the existence of a characteristic Dirac point in its electronic structure. Further challenges regarding the RL-based structural assembly scalability are discussed.

Algorithms↗

Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks

There has been much recent interest in designing symmetry-aware neural networks (NNs) exhibiting relaxed equivariance. Such NNs aim to interpolate between being exactly equivariant and being fully flexible, affording consistent performance benefits. In a separate line of work, certain structured parameter matrices -- those with displacement structure, characterized by low displacement rank (LDR) -- have been used to design small-footprint NNs. Displacement structure enables fast function and gradient evaluation, but permits accurate approximations via compression primarily to classical convolutional neural networks (CNNs). In this work, we propose a general framework -- based on a novel construction of symmetry-based structured matrices -- to build approximately equivariant NNs with significantly reduced parameter counts. Our framework integrates the two aforementioned lines of work via the use of so-called Group Matrices (GMs), a forgotten precursor to the modern notion of regular representations of finite groups. GMs allow the design of structured matrices -- resembling LDR matrices -- which generalize the linear operations of a classical CNN from cyclic groups to general finite groups and their homogeneous spaces. We show that GMs can be employed to extend all the elementary operations of CNNs to general discrete groups. Further, the theory of structured matrices based on GMs provides a generalization of LDR theory focussed on matrices with cyclic structure, providing a tool for implementing approximate equivariance for discrete groups. We test GM-based architectures on a variety of tasks in the presence of relaxed symmetry. We report that our framework consistently performs competitively compared to approximately equivariant NNs, and other structured matrix-based compression frameworks, sometimes with a one or two orders of magnitude lower parameter count.

Samudre, Ashwin↗

Crystal structures and rotational dynamics of a two-dimensional metal halide perovskite (OA) 2 PbI 4

The extended charge carrier lifetime in metal halide perovskites is responsible for their excellent optoelectronic properties. Recent studies indicate that the superb device performance in these materials is intimately related to the organic cation dynamics. Here, we focus on the investigation of the two-dimensional hybrid perovskite, (C 8 H 17 NH 3 ) 2 PbI 4 (henceforth, OA + = C 8 H 17 NH 3 + ). Using elastic and quasielastic neutron scattering techniques and group theoretical analysis, we studied the structural phase transitions and rotational modes of the C 8 H 17 NH 3 + cation in (OA) 2 PbI 4 . Here, our results show that, in the high-temperature orthorhombic ( T > 310 K) phase, the OA + cation exhibits a combination of a twofold rotation of the NH 3 –CH 2 head group about the crystal c -axis with a characteristic relaxation time of ~6.2 ps, threefold rotations (C 3 ) of NH 3 and CH 3 terminal groups, and slow librations of the other atoms. Contrastingly, only the C 3 rotation is present in the intermediate-temperature orthorhombic (238 K < T < 310 K) and low-temperature monoclinic ( T < 238 K) phases.

36 MATERIALS SCIENCE↗

The structure of importin α and the nuclear localization peptide of ChREBP, and small compound inhibitors of ChREBP–importin α interactions

The carbohydrate response element binding protein (ChREBP) is a glucose-responsive transcription factor that plays a critical role in glucose-mediated induction of genes involved in hepatic glycolysis and lipogenesis. In response to fluctuating blood glucose levels ChREBP activity is regulated mainly by nucleocytoplasmic shuttling of ChREBP. Under high glucose ChREBP binds to importin α and importin β and translocates into the nucleus to initiate transcription. We have previously shown that the nuclear localization signal site (NLS) for ChREBP is bipartite with the NLS extending from Arg158 to Lys190. Here, we report the 2.5 Å crystal structure of the ChREBP-NLS peptide bound to importin α. The structure revealed that the NLS binding is monopartite, with the amino acid residues K171RRI174 from the ChREBP-NLS interacting with ARM2–ARM5 on importin α. We discovered that importin α also binds to the primary binding site of the 14-3-3 proteins with high affinity, which suggests that both importin α and 14-3-3 are each competing with the other for this broad-binding region (residues 117–196) on ChREBP. We screened a small compound library and identified two novel compounds that inhibit the ChREBP-NLS/importin α interaction, nuclear localization, and transcription activities of ChREBP. These candidate molecules support developing inhibitors of ChREBP that may be useful in treatment of obesity and the associated diseases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Observed metallization of hydrogen interpreted as a band structure effect

A recent experimental study of the metallization of hydrogen tracked the direct band gap and vibron frequency via infrared measurements up to ~425 GPa (Loubeyre et al (2020 Nature 577 631). Above this pressure, the direct gap has a discontinuous drop to below the minimum experimentally accessible energy (~0.1 eV). The authors suggested that this observation is caused by a structural phase transition between the C2/c-24 molecular phase to another molecular phase such as Cmca-12. Here, through ab initio calculations of pressure dependent vibron frequency and direct band gap, we find that the experimental data is consistent with the C2/c-24 phase up to 425 GPa, and suggest that this consistency extends beyond that pressure. Specifically, we find that qualitative changes in the band structure of the C2/c-24 phase lead to a discontinuous drop of the direct band gap, which can explain the observed drop without a structural transition. In conclusion, this alternative scenario, which naturally explains the absence of hysteresis in the measurements, will hopefully motivate further experimental studies to ascertain the structure of the phase above the high pressure 'phase transition'.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Expanding Configurational Complexity through Dipole Dilution in Pseudohalide Argyrodite Ion Conductors

The advantageous properties of (pseudo)halide argyrodite ion conductors of the formula Li 6 PS 5 X (X = Cl – , Br – , I – , CN – ) have motivated extensive studies of their structure-transport relationships, particularly as they pertain to the role of atomic site disorder. The argyrodite structure can accommodate additional configurational complexity to promote ion transport via extended three-anion site mixing and the potential for orientational disorder of molecular anions. In this work, we explore a ternary anion system including the cyanide anion, expanding site disorder and introducing dipolar orientations as an additional degree of freedom. We prepared the series Li 6 PS 5 (CN) 1–x Br x , in which the dipolar cyanide anions are systematically diluted with bromide. We find that anion disorder, as determined by synchrotron and neutron diffraction and quantified by configurational entropy (S config ), is correlated with lowered activation barriers and increased lithium ion conductivity. We propose that S config describes the electrostatic heterogeneity of the Li environments, flattening the energetic landscape for ion transport. While anion substitution strongly impacts the activation barrier for transport, the temperature-independent Arrhenius prefactor does not follow the same trend. Through heat-capacity measurements of attempt frequency and deconvolution of terms within the prefactor, we rationalize the apparent decoupling of activation energy and prefactor to strong cyanide-lithium interactions that increase the entropy of migration. Together, these results expand the structure–property relationships in the argyrodite family to encompass multiple facets of disorder and the subsequent impact on lithium ion transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗