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1,493 records · Page 67

Superconducting phase diagram of multilayer square-planar nickelates

The discovery of superconductivity in square-planar nickelates has offered a rich materials platform to explore the origins of high-temperature superconductivity. However, experimental investigations have largely been limited to the infinite-layer R NiO 2 ( R , rare earth) nickelates. For this work we constructed a phase diagram of multilayer square-planar Nd n+1 Ni n O 2n+2 compounds and found signatures of superconductivity for dimensionality n = 4 to 8. Upon decreasing n , the superconducting anisotropy evolves owing to 4ƒ electron effects, and electronic structure characteristics approach cuprate-like behavior. Magnetic fluctuations persist from within the superconducting regime and into the overdoped, nonsuperconducting regime. The superconducting regime overlaps with that of chemically doped infinite-layer nickelates, demonstrating underlying commonalities as well as differences across varying structural realizations of square-planar nickelates. Our work establishes this layered template for creating new nickel-based superconductors.

36 MATERIALS SCIENCE

The occurrence rate of galaxies with polar structures may be significantly underestimated

Polar-ring galaxies are photometrically and kinematically decoupled systems that are highly inclined to the major axis of the host. These galaxies have been explored since the 1970s, but the rarity of these systems has made such systematic studies difficult. However, over 250 good candidates have been identified. In this work, we examine a sample of over 18 000 galaxies from the Sloan Digital Sky Survey (SDSS) Stripe 82 for the presence of galaxies with polar structures. Using deep SDSS Stripe 82, DESI Legacy Imaging Surveys, and Hyper Suprime-Cam Subaru Strategic Program, we selected 53 good candidate galaxies with photometrically decoupled polar rings, 9 galaxies with polar halos, 6 galaxies with polar bulges, and 34 possibly forming polar-ring galaxies, versus 13 polar-ring candidates previously selected in Stripe 82. Our results suggest that the occurrence rate of galaxies with polar structures may be significantly underestimated, as revealed by the deep observations, and may amount to 1–3% of non-dwarf galaxies.

Astronomy & Astrophysics

Reconfigurable Cascaded Thermal Neuristors for Neuromorphic Computing

While the complementary metal-oxide semiconductor (CMOS) technology is the mainstream for the hardware implementation of neural networks, an alternative route is explored based on a new class of spiking oscillators called “thermal neuristors”, which operate and interact solely via thermal processes. Utilizing the insulator-to-metal transition (IMT) in vanadium dioxide, a wide variety of reconfigurable electrical dynamics mirroring biological neurons is demonstrated. Notably, inhibitory functionality is achieved just in a single oxide device, and cascaded information flow is realized exclusively through thermal interactions. To elucidate the underlying mechanisms of the neuristors, a detailed theoretical model is developed, which accurately reflects the experimental results. In conclusion, this study establishes the foundation for scalable and energy-efficient thermal neural networks, fostering progress in brain-inspired computing.

36 MATERIALS SCIENCE

Sierra/SD Verification Test Manual 5.32

Tests from the Sierra Structural Dynamics verification test suite are reviewed. For each of the tests presented in this document the test setup, derivation of the analytic solution, and comparison of the Sierra code results to the analytic solution is provided. This document can be used to confirm that a given code capability is verified or referenced as a compilation of example problems.

Beale, Dagny Marie [Sandia National Laboratories (

A Novel Low-Profile High-Efficiency Three-Phase Matrix Transformer

High step-down isolated DC-DC conversion from an 800 V DC bus to low-voltage, high-current outputs is required in automotive auxiliary converters and data center power supplies. In such applications, conventional transformer-based converters require large turns ratios, which increase winding resistance, leakage inductance, and magnetic height. This paper proposes a novel low-profile three-phase matrix transformer that realizes a large effective voltage ratio through flux division among multiple secondary legs, without increasing the physical turns count of each winding. As a result, the proposed structure reduces copper usage and transformer height while preserving the voltage conversion capability of a conventional three-phase transformer. Finite element analysis shows that the proposed design reduces magnetic height by 27%, ferrite volume by 34%, and copper volume by 28%. Circuit-level simulations of an 800 V/12 V,3 kW CLLLC dual-active-bridge converter further show that the lower winding resistance reduces total system loss by 91% and increases DC-DC efficiency from 82.6% to 97.6% at 3 kW output.

Inoue, Shuntaro [ORNL] (ORCID:0000000262637627)

Dark Energy Survey Year 6 results: Redshift calibration of the MagLim++ lens sample

In this work, we derive and calibrate the redshift distribution of the MagLim++ lens galaxy sample used in the Dark Energy Survey Year 6 (DES Y6) 3 x 2pt cosmology analysis. The 3 x 2pt analysis combines galaxy clustering from the lens galaxy sample and weak gravitational lensing. The redshift distributions are inferred using the SOMPZ method - a Self-Organizing Map framework that combines deep-field multi-band photometry, wide-field data, and a synthetic source injection ( B alrog) catalog. Key improvements over the DES Year 3 (Y3) calibration include a noise-weighted SOM metric, an expanded Balrog catalogue, and an improved scheme for propagating systematic uncertainties, which allows us to generate O(10 8 ) redshift realizations that collectively span the dominant sources of uncertainty. These realizations are then combined with independent clustering-redshift measurements via importance sampling. The resulting calibration achieves typical uncertainties on the mean redshift of 1-2%, corresponding to a 20-30% average reduction relative to DES Y3. We compress the n(z) uncertainties into a small number of orthogonal modes for use in cosmological inference. Marginalizing over these modes leads to only a minor degradation in cosmological constraints. Here, this analysis establishes the MagLim++ sample as a robust lens sample for precision cosmology with DES Y6 and provides a scalable framework for future surveys.

dark energy

Microscopy modality transfer of steel microstructures: Inferring scanning electron micrographs from optical microscopy using generative AI

Scanning electron microscopy (SEM) is resource intensive, which limits its throughput in some applications. As an alternative, we propose applying computer vision and machine learning to generate high-quality synthetic SEM micrographs from micrographs obtained using light optical microscopy (LOM). Working with a correlated LOM/SEM dataset of dual-phase steel images, we test generative models of various architectures, including encoder-decoder networks, generative adversarial networks (GANs), and diffusion-based models. We find that the diffusion models significantly outperform other methods on both qualitative and quantitative assessments, while preserving key metallurgical meaning. This work establishes diffusion as the state-of-the-art for microscopy modality transfer and demonstrates the potential of AI-powered microscopy to enhance LOM with micron scale structural recreation.

Computer vision

Mitigating electrochemical degradation in CsPbBr{sub 3} gamma detectors by organic and inorganic encapsulation.

CsPbBr3 perovskite semiconductors have emerged as a leading candidate for nextgeneration radiation detectors because of their exceptional charge transport properties, defect tolerance, and record-breaking sensitivity and energy resolution. Their long-term stability, however, is hindered by electrode-driven electrochemical decomposition, which is accelerated by moisture- and oxygen-assisted ion migration during operation. Here, we investigated organic and inorganic encapsulation strategies as both environmental barriers and means to suppress interfacial degradation pathways. Atomic layer deposition (ALD) of Al2O3 provided a conformal passivation layer that blocked environmental ingress, suppressed ionic diffusion, reduced leakage current, enhanced energy resolution and expanded the operational electric-field window beyond 5 kV∙cm1 . By contrast, organic encapsulants such as paraffin wax and polystyrene slowed moisture diffusion but did not suppress interfacial reactions, with wax extending stability to over 90 days. These results show that ALD-Al2O3 suppresses dominant interfacial degradation pathways, enabling stable, high-field operation and advancing the practical deployment of CsPbBr3 γ-ray detectors.

Unal, Mustafa

Fabrication of Large-Area Metal-on-Carbon Catalytic Condensers for Programmable Catalysis

Catalytic condensers stabilize charge on either side of a high-k dielectric film to modulate the electronic states of a catalytic layer for the electronic control of surface reactions. Here, carbon sputtering provided for fast, large-scale fabrication of metal–carbon catalytic condensers required for industrial application. Carbon films were sputtered on HfO 2 dielectric/p-type Si with different thicknesses (1, 3, 6, and 10 nm), and the enhancement of conductance and capacitance of carbon films was observed upon increasing the carbon thickness following thermal treatment at 400 °C. After Pt deposition on the carbon films, the Pt catalytic condenser exhibited a high capacitance of ∼210 nF/cm 2 that was maintained at a frequency ∼1000 Hz, satisfying the requirement for a dynamic catalyst to implement catalytic resonance. Temperature-programmed desorption of carbon monoxide yielded CO desorption peaks that shifted in temperature with the varying potential applied to the condenser (−6 or +6 V), indicating a shift in the binding energy of carbon monoxide on the Pt condenser surface. A substantial increase in capacitance (∼2000 nF/cm 2 ) of the Pt-on-carbon devices was observed at elevated temperatures of 400 °C that can modulate ∼10% of charge per metal atom when 10 V potential was applied. A large catalytic condenser of 42 cm 2 area Pt/C/HfO 2 /Si exhibited a high capacitance of 9393 nF with a low leakage current/capacitive current ratio (<0.1), demonstrating the practicality and versatility of the facile, large-scale fabrication method for metal–carbon catalytic condensers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Electrically Accelerated Mechanochemical Film Formation by a Phosphonium Phosphate Ionic Liquid: An In Situ Chemical Kinetics Investigation

Powertrains in electric vehicles are exposed to stray currents that accelerate wear and cause failure of mechanical components. These durability issues are further aggravated when using low-viscosity lubricants, which are desired for energy efficiency but create harsher contact conditions at sliding interfaces. This study investigates a phosphonium phosphate ionic liquid as a performance-enhancing additive in a low-viscosity base oil for lubricating electrified sliding interfaces. Ionic liquids can adsorb and react on contact interfaces via stress-assisted chemical reactions, generating nanometric tribofilms that provide protection against wear. However, the effect of electric fields on the mechanochemistry of ionic liquids is poorly understood, hindering their adoption in lubricants for electrified powertrains. This article reports an in situ optical interferometry study of ionic liquid derived tribofilm growth kinetics at stressed sliding/rolling interfaces under direct currents. The application of electric currents accelerated tribofilm formation up to a critical current density (∼1.4 A/mm 2 ), beyond which pitting-induced wear dominated. The tribofilms were composed of iron phosphates, iron oxides, and carbon species, with iron oxides becoming predominant under applied currents. These tribofilms prevented the scuffing failure of steel surfaces under electrified conditions. Based on the results, a kinetic model is proposed that integrates electric current effect into the classical stress-assisted thermal activation framework to allow prediction of tribofilm growth at electrified sliding contacts. This framework provides crucial guidance for designing next-generation lubricants for electrified transportation and power generation systems.

additives

Direct Visualization of Defect‐Controlled Diffusion in van der Waals Gaps

Abstract Diffusion processes govern fundamental phenomena such as phase transformations, doping, and intercalation in van der Waals (vdW) bonded materials. Here, the diffusion dynamics of W atoms by visualizing the motion of individual atoms at three different vdW interfaces: hexagonal boron nitride (BN)/vacuum, BN/BN, and BN/WSe 2 , by recording scanning transmission electron microscopy movies is quantified. Supported by density functional theory (DFT) calculations, it is inferred that in all cases diffusion is governed by intermittent trapping at electron beam‐generated defect sites. This leads to diffusion properties that depend strongly on the number of defects. These results suggest that diffusion and intercalation processes in vdW materials are highly tunable and sensitive to crystal quality. The demonstration of imaging, with high spatial and temporal resolution, of layers and individual atoms inside vdW heterostructures offers possibilities for direct visualization of diffusion and atomic interactions, as well as for experiments exploring atomic structures, their in situ modification, and electrical property measurements of active devices combined with atomic resolution imaging.

Chemistry

The Hawaii Meteorology, Energy and Transmission (MET) Toolkit

Reliable long-term resource adequacy and grid planning in Hawaii require precise, multi-decadal meteorological records. This paper introduces the Hawaii Meteorology, Energy and Transmission (MET) Toolkit, a 26-year (2000-2025) high-fidelity atmospheric dataset developed by the National Laboratory of the Rockies (NLR). We present a validation study of the underlying WRF model configurations, comparing the legacy MYNN PBL scheme against an alternative YSU formulation. Using vertical lidar profiles and surface buoy data, our analysis identified a foundational geometric distortion in the legacy NOW-23 Hawaii dataset caused by an incorrect grid projection. When evaluated on a corrected, zero-distortion grid, the YSU scheme demonstrated superior performance in bias and cRMSE compared to the legacy setup. To address these findings, the MET Toolkit has been re-produced as a unified 26-year record using the optimized YSU setup and corrected geometry. This dataset offers the Hawaii power sector a robust, validated, and homogenous reference for future grid resilience and energy integration.

24 POWER TRANSMISSION AND DISTRIBUTION

Commutative Algebra Modeling in Materials Science – A Case Study on Metal–Organic Frameworks (MOFs)

Metal-organic frameworks (MOFs) are a class of important crystalline and highly porous materials whose hierarchical geometry and chemistry hinder interpretable predictions in materials properties. Commutative algebra is a branch of abstract algebra that has been rarely applied in data and material sciences. We introduce the first ever commutative algebra modeling and prediction in materials science. Specifically, category-specific commutative algebra (CSCA) is proposed as a new framework for MOF representation and learning. It integrates element-based categorization with multiscale algebraic invariants to encode both local coordination motifs and global network organization of MOFs. These algebraically consistent, chemically aware representations enable compact, interpretable, and data efficient modeling of MOF properties such as Henry’s constants and uptake capacities for common gases. Compared to traditional geometric and graph-based approaches, CSCA achieves comparable or superior predictive accuracy while substantially improving interpretability and stability across data sets. By aligning commutative algebra with the chemical hierarchy, the CSCA establishes a rigorous and generalizable paradigm for understanding structure and property relationships in porous materials and provides a nonlinear algebra-based framework for data-driven material discovery.

Khaemba, Caleb S.

Lagrange-Remap strategy for multi-material fluid-solid simulations using compressive limiters

In the present work, the Lagrange-Remap strategy proposed in [1] is extended to multi-material fluid-solid simulations. Both hypo-elastic and hyper-elastic material models are considered to describe the mechanical behavior of the solids. In practice, the deviatoric stress tensor (for hypo-elastic materials) and the left Cauchy-Green tensor (for isotropic hyper-elastic materials) are remapped, while the use of compressive limiters effectively reduces numerical diffusion during the remapping step. The simplicity of this diffuse interface approach is emphasized in the context of multi-material fluid-solid simulations. A series of Lagrange-Remap test cases, involving both solids and fluids, are conducted and compared with reference Lagrangian simulations, demonstrating the robustness and accuracy of the overall numerical strategy.

Compressive limiters

Fabrication and test of a 6-tesla-class high-temperature superconducting dipole magnet at 4.2 K

Superconducting magnets enable energy-frontier accelerators by generating strong magnetic fields to steer and focus the particles. Although high-temperature superconductors such as REBa 2 Cu 3 O x (, RE = rare earth) hold a strong potential for generating a higher magnetic field than Nb-Ti and Nb 3 Sn , the associated magnet and conductor technology for accelerator applications is still in its infancy. The U.S. Magnet Development Program is developing magnet technology in collaboration with industry. Here we report an experiment of making a dipole magnet called C3 using commercial high-temperature superconducting wires. The magnet, following a canted cos θ design, generated a dipole field of 5.99 T at 4.2 K in its clear aperture of 65 mm at 6.795 kA when a resistive voltage of 105 μ V appeared across one of the coils in the magnet. The stored energy was 53 kJ at the peak field. The magnet showed no degradation in the current-carrying capability at 4.2 K after the thermal cycle. We report on the detailed design, fabrication, and performance of the C3 magnet that can be of interest to potential users of this emerging technology. We also discuss issues and research needs to inform future magnet development. The experiment represented another step to addressing if the high-temperature superconducting accelerator magnet technology can increase the discovery capability of future particle accelerators.

Abraimov, Dmytro [National High Magnetic Field Lab

Thermal property characterization of phase change materials in building applications: A systematic review of fundamentals, recent progress, and future directions

Phase change materials (PCMs) can reduce building peak loads and enable demand-responsive thermal energy storage (TES), but their deployment depends on reliable measurement and interpretation of thermal properties across laboratory, intermediate, and application scales. Here, this review systematically examines characterization methods, testing protocols, and recent advances for neat PCMs and PCM composites, emphasizing thermal conductivity, enthalpy-related properties (phase change temperature, latent heat, specific heat), and cycling stability. For thermal conductivity, we compare steady-state and transient techniques and note limitations when phase transition and contact resistance affect measurements. For enthalpy–temperature characterization, we discuss differential scanning calorimetry together with intermediate- and bulk-scale methods, including T-history, heat flow meter testing, and three-layer calorimetry (3LC), to generate application-relevant enthalpy–temperature profiles. Cycling stability is organized into four experimental families: thermoelectric–air, fully thermoelectric, water-bath, and in situ chamber approaches, with attention to separating reversible supercooling from true degradation such as phase segregation. We highlight emerging noncontact diagnostics, including infrared thermography and embedded sensing, for spatially resolved validation and multiscale interpretation. Finally, we review the growing use of AI and machine learning for property prediction, inverse characterization from experimental signals, and real-time state estimation in building-integrated TES. Key needs include harmonized protocols, interlaboratory benchmarking, uncertainty reporting, and metadata-rich datasets to accelerate reproducible PCM qualification for grid-flexible buildings.

AI

R&D GREET Battery Carbon Footprint Calculator

The Battery Carbon Footprint (CF) Calculator was developed to help U.S. battery manufacturers meet the carbon footprint reporting requirements of the EU Battery Regulation (EU) 2023/1542. The calculator incorporates several major battery carbon footprint frameworks, including the Joint Research Centre's Rules for the Calculation of the Carbon Footprint of Electric Vehicle Batteries (CFB-EV), RECHARGE's Product Environmental Footprint Category Rules for High Specific Energy Rechargeable Batteries for Mobile Applications (PEFCR), the Catena-X Product Carbon Footprint Rulebook (CX-PCF Rules), Battery Pass's Battery Carbon Footprint: Rules for Calculating the Carbon Footprint of the "Distribution" and "End-of-Life and Recycling" Life Cycle Stages, the Global Battery Alliance's Greenhouse Gas Rulebook: Generic Rules, Version 2.1, and the Ministry of Economy, Trade and Industry's draft Carbon Footprint Calculation Method for Automotive Batteries. The tool pairs these frameworks with foreground data from Argonne's R&D GREET models and integrates user-supplied background data covering battery manufacturing and supply chain activities. By bringing multiple international methodologies together in a single platform, the calculator enables manufacturers to evaluate product carbon footprints, improve data consistency, and prepare for evolving regulatory compliance and global market reporting requirements.

Zhang, Jingyi

Multiple Peaks and a Long Precursor in the Type IIn Supernova 2021qqp: An Energetic Explosion in a Complex Circumstellar Environment

Abstract We present optical photometry and spectroscopy of the Type IIn supernova (SN) 2021qqp. Its unusual light curve is marked by a long precursor for ≈300 days, a rapid increase in brightness for ≈60 days, and then a sharp increase of ≈1.6 mag in only a few days to a first peak ofM r ≈ −19.5 mag. The light curve then declines rapidly until it rebrightens to a second distinct peak ofM r ≈ −17.3 mag centered at ≈335 days after the first peak. The spectra are dominated by Balmer lines with a complex morphology, including a narrow component with a width of ≈1300 km s −1 (first peak) and ≈2500 km s −1 (second peak) that we associate with the circumstellar medium (CSM) and a P Cygni component with an absorption velocity of ≈8500 km s −1 (first peak) and ≈5600 km s −1 (second peak) that we associate with the SN–CSM interaction shell. Using the luminosity and velocity evolution, we construct a flexible analytical model, finding two significant mass-loss episodes with peak mass loss rates of ≈10 and ≈5M ⊙ yr −1 about 0.8 and 2 yr before explosion, respectively, with a total CSM mass of ≈2–4M ⊙ . We show that the most recent mass-loss episode could explain the precursor for the year preceding the explosion. The SN ejecta mass is constrained to be ≈5–30M ⊙ for an explosion energy of ≈(3–10) × 10 51 erg. We discuss eruptive massive stars (luminous blue variable, pulsational pair instability) and an extreme stellar merger with a compact object as possible progenitor channels.

Astronomy & Astrophysics