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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23

CHEQUP v0.1

CHEQUP (Castro-based Hofi Expansion with QUasineutral Plasma) is a simulation code for modeling the formation of hydrodynamic optical-field-ionized (HOFI) plasma channels, which are used as waveguides in laser-plasma acceleration experiments. This includes experiments performed at LBNL's BELLA facility as well as other laser facilities across the world. CHEQUP extends the open-source Castro hydrodynamics framework with physics modules tailored for modeling HOFI plasma channels -- including multi-species ionization and three-body recombination for mixtures of hydrogen, nitrogen, helium, and argon ; a two-temperature model tracking electron and heavy-species temperatures separately ; and coupling with other codes of the BLAST ecosystem (https://blast.lbl.gov/) such as WarpX, via the openPMD standard. CHEQUP inherits from Castro the ability to run on modern GPU architectures (NVIDIA CUDA, AMD HIP) and supports adaptive mesh refinement (AMR) for efficient multi-scale resolution. Compared to existing tools, CHEQUP would be, to our knowledge, the first open-source code implementing the full HOFI channel formation physics, and the first implementation capable of running on GPUs. This enables significantly faster, large-scale parameter scans critical for the design of next-generation LPA-based accelerators and light sources.

Lehe, Remi [Lawrence Berkeley National Laboratory ↗

autoGEMM: Pushing the Limits of Irregular Matrix Multiplication on Arm Architectures

This paper presents an open-source library that pushes the limits of performance portability for irregular General Matrix Multiplication (GEMM) on the widely-used Arm architectures. Our library, autoGEMM, is designed to support a wide range of Arm processors: from edge devices to HPC-grade CPUs. autoGEMM generates optimized kernels for various hardware configurations by auto-combining fragments of autogenerated micro-kernels that employ hand-written optimizations to maximize computational efficiency. We optimize the kernel pipeline by tuning the register reuse and the data load/store overlapping. In addition, we use a dynamic tiling scheme to generate balanced tile shapes. Finally, we position autoGEMM on top of the TVM framework where our dynamic tiling scheme prunes the search space for TVM to identify the optimal combination of parameters for code optimization. Evaluations on five different classes of Arm chips demonstrate the advantages of autoGEMM. For small matrices, autoGEMM achieves 98% of peak and up to 2.0x speedup over state-of-the-art libraries such as LIBXSMM and LibShalom. For irregular matrices (i.e. tall skinny and long rectangles), autoGEMM is 1.3-2.0x faster than widely-used libraries such as OpenBLAS and Eigen. autoGEMM is publicly available at: https://github.com/wudu98/autoGEMM.

Wu, Du↗

A fault-tolerant neutral-atom architecture for universal quantum computation

Quantum error correction (QEC) is essential for the realization of large-scale quantum computers. However, owing to the complexity of operating on the encoded ‘logical’ qubits, understanding the physical principles for building fault-tolerant quantum devices and combining them into efficient architectures is an outstanding scientific challenge. Here we use reconfigurable arrays of up to 448 neutral atoms to implement the key elements of a universal, fault-tolerant quantum processing architecture and experimentally explore their underlying working mechanisms. We first use surface codes to study how repeated QEC suppresses errors, demonstrating 2.14(13)x below-threshold performance in a four-round characterization circuit by leveraging atom loss detection and machine learning decoding. We then investigate logical entanglement using transversal gates and lattice surgery and extend it to universal logic through transversal teleportation with three-dimensional [[15,1,3]] codes, enabling arbitrary-angle synthesis with polylogarithmic overhead. Finally, we develop mid-circuit qubit reuse16, increasing experimental cycle rates by two orders of magnitude and enabling deep-circuit protocols with dozens of logical qubits and hundreds of logical teleportations with [[7,1,3]] and high-rate [[16,6,4]] codes while maintaining constant internal entropy. Our experiments show key principles for efficient architecture design, involving the interplay between quantum logic and entropy removal, judiciously using physical entanglement in logic gates and magic state generation, and leveraging teleportations for universality and physical qubit reset. These results establish foundations for scalable, universal error-corrected processing and its practical implementation in neutral atom systems.

atomic and molecular physics↗

Multi-Stage FNO

This is the code developed for paper - Reducing Frequency Bias of Fourier Neural Operators in 3D Seismic Wavefield Simulations Through Multi-Stage Training (https://arxiv.org/abs/2503.02023), it contains training the multi-stage FNO model to generate the seismic forward simulations in 3D medium.

Kong, Qingkai [Lawrence Livermore National Laborat↗

Gold-et-al_2024_EarthsFuture

Results from Gold et al. submitted to Earth's Future. All code to reproduce the experiment and make the figures can be found here: https://github.com/davidfgold/Gold-etal_2024_EarthsFuture For a detailed guide to data in this repository, see the README.txt file. Shortage output from .xdd files generated by StateMod was compressed into .parquet files. Reservoir output from .xre files can be found in the "Reservoir" directory. We adopted the CDSS naming convention: cm = Upper Colorado River Basin gm = Gunnison River Basin ym = Yampa River Basin wm = White River Basin sj = Southwest Basin

Climate Change↗

Data for Unraveling the Drivers of Water Shortage across Spatial Scales and Sectors in Colorado's West Slope River Basins

Results from Sunkara et al. submitted to Earth's Future. All code to reproduce the experiment and make the figures can be found here: https://github.com/ssaiveena/Sunkara-etal_2025_WestSlope For a detailed guide to data in this repository, see the README.txt file. Shortage output from .xdd files generated by StateMod was compressed into .parquet files in the Uncertain_scenarios folder. Reservoir output from .xre files can be found in the "Reservoir" directory within the Uncertain_scenarios folder. We adopted the CDSS naming convention: cm = Upper Colorado River Basin gm = Gunnison River Basin ym = Yampa River Basin wm = White River Basin sj = Southwest Basin

Climate Change↗

Assessment of CTF for Steady-state and Transient Post-CHF Conditions in Support of Time-at-Temperature Modeling Applications

The US nuclear industry is exploring options to improve operational economics and uprate the current fleet of light-water reactors by investigating transitioning to cladding performance–based safety criteria as opposed to the current limit, which requires complete avoidance of critical heat flux (CHF)/dryout. Past experience has shown that not all events leading to a dryout are severe enough to cause fuel performance degradation. Allowing temporary dryout of the fuel—that is, using a time-at-temperature (TaT) strategy—could allow for economic improvements via large power uprates and enhanced operational flexibility for current plants without compromising fuel integrity. To support this effort, the US Department of Energy is executing a comprehensive program that includes generating cladding material data under TaT conditions, developing new mechanistic models, and demonstrating modeling and simulation capabilities for transients of interest. This paper presents work performed to assess the CTF thermal-hydraulics subchannel code. CTF is a package used in the VERA core simulator, which will ultimately be used for TaT analysis. CTF will provide the thermal-hydraulic boundary conditions that will be needed for fuel performance analysis in the BISON code. Quantifying both the accuracy and uncertainty of post-CHF models will therefore be necessary. This paper outlines the strategy for the assessment of TaT and presents the results of using the steady-state and transient dryout experiments of the Boiling Fine-mesh Bundle Tests for CTF validation. The results show that the current model tends to overpredict steady-state critical power. This behavior translates to the transient tests, in which CTF is unable to capture transient dryout behavior. Some discussion of sensitivity analysis work being performed is provided to indicate which models must be further analyzed to properly model transient dryout and its uncertainty.

Salko Jr, Robert [ORNL] (ORCID:0000000253566679)↗

Dataset, Code, and Models for Training Deep Learning Potentials for Low Temperature Plasma-Surface Interactions

This repository contains datasets, training scripts, and finished models, and test simulations used in the development of DeepREBO— a machine-learned interatomic potential trained to emulate the REBO2 empirical potential. The data was generated to study deep potential development for simulations of plasma-surface interactions. It uses an active learning framework, starting from a minimal dataset and iteratively expanding it. Included are those generated datasets, the trained models, and simulations used to evaluate the performance of the training process. This resource supports reproducibility and provides a reference framework for training deep potentials in plasma-surface interaction studies.

active learning↗

Advanced Manufactured Home Case Study: A Collaboration for High-Efficiency, Affordable Housing

The introduction of Zero Energy Ready Home Manufactured Homes (ZERH MH) qualification for manufactured homes has generated significant attention and interest in the industry to employ advanced manufacturing techniques. VEIC engaged with Titan Homes to create an advanced manufactured home design that employs ZERH standards, other client-driven above-code standards, and manufacturing processes improvements. This case study identifies specific energy-efficient and quality improvement measures that were implemented to achieve certification and take advantage of incentives for home manufacturers.

14 SOLAR ENERGY↗

NanoPSD: A software for automatic detection of Nano-Particle Shape Distribution in electron microscopy images

Accurate quantification of the size and morphology of nanoparticles from electron microscopy (EM) images is essential to understand growth mechanisms, surface reactivity, and functional behavior in nanoscale materials. Manual analysis remains slow, subjective, and difficult to reproduce in large datasets. We introduce NanoPSD (Nano-Particle Shape Distribution), an open-source and fully automated framework for quantitative particle detection and morphology analysis from EM images. NanoPSD integrates adaptive contrast enhancement, polarity-agnostic scale-bar detection, Optical Character Recognition (OCR)-based calibration, and classical segmentation via Otsu thresholding with morphological refinement. Particle contours are used to extract geometric descriptors, including equivalent circular diameter, aspect ratio, circularity, and solidity, enabling automated classification into spherical, rod-like, and aggregate morphologies. The framework supports both single-image and batch processing, generating publication-quality visualizations, LaTeX-ready tables, and structured comma-separated values (CSV) datasets. As a demonstration, we applied NanoPSD to plasma-synthesized nanoparticle samples diagnosed via transmission electron microscopy (TEM). The code produced statistically robust size and morphology distributions spanning a few to tens of nanometers with minimal user supervision. The pipeline demonstrates high reproducibility and scalability, processing large image collections with consistent calibration and output formatting. Its modular design enables seamless integration of future deep-learning-based segmentation models, providing a pathway toward intelligent, data-driven electron microscopy analysis.

36 MATERIALS SCIENCE↗

Advanced Reactor Safeguards & Security 2024 Program Roadmap

The Advanced Reactor Safeguards and Security (ARSS) program was established to provide research support addressing near term challenges that advanced nuclear reactor vendors face in meeting domestic Material Control and Accounting (MC&A), Physical Protection System (PPS), and Cybersecurity requirements for U.S. construction. The technical work in the program is meant to (1) support nuclear reactor vendors with advanced MC&A, PPS, and Cybersecurity designs for next generation reactors, (2) provide technical bases for the regulator, and (3) promote the integration of Safeguards and Security by Design early in the design process. Existing domestic regulations for safeguards and security, as outlined in the Code of Federal Regulations, were written for large light water reactors, and rule-making efforts are underway to develop regulations more suited to different reactor designs. The ARSS program seeks to remove roadblocks in the deployment of new and advanced reactors by solving regulatory challenges, reducing safeguards and security costs, and utilizing the latest technologies and approaches for robust plant monitoring and protection. This roadmap discusses the goals of the ARSS program, current research, and program plan for the next five years.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Basic Physical Processes Involving Dust in Fusion Plasmas

This report presents the main outcomes of our research focused on understanding the behavior and effects of dust particles in fusion plasmas, particularly in the edge regions of tokamaks and stellarators. We conducted computer modeling studies of burst injections of carbon and tungsten dust particles in DIII-D like divertor plasmas. The studies investigated effects of transient influx of the low- and high-Z material plasma contaminants in form of dust on the edge plasma dynamics in a modern mid-size tokamak. We also performed theoretical and computational studies of the forces acting on non-spherical dust grains in magnetized and nonmagnetized plasmas. In addition, we cooperated with General Atomics slag management group on development of DIII-D dust injection experiments to measure trajectories of dust grains in the divertor plasma and compare them with DUSTT code predictions for validation of the dust modeling capabilities. We collaborated with JET experimentalists on evaluation of radiative losses induced by injection of mixed neon-deuterium ice pellets for disruption and run-away electron generation mitigation during thermal and current quench phases. We also cooperated with experimentalists at LHD fusion device (Japan) on modeling support of experiments on injection of boron granules in fusion plasma discharges to assess their dynamics and effectiveness for in situ dynamic wall conditioning.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

SAS4A/SASSYS-1 Verification Testing for Sodium Fast Reactor Application: Acceptance Testing Report

AS4A/SASSYS-1 (SAS) is a simulation tool used to perform deterministic analyses of anticipated events as well as design basis and beyond design basis accidents for advanced liquid-metal-cooled nuclear reactors. With its origin as SAS1A in the late 1960s, the SAS series of codes has been under continuous use and development for over sixty years and represents a critical investment in safety analysis capabilities for the U.S. Department of Energy. To support the dedication effort, this report has been generated to provide a detailed description of the available verification testing. The verification testing presented in this report captures functionality testing, focusing mainly on the testing of specific functions and algorithms for accuracy and precision of output, and interface testing, focusing mainly on the testing of critical input parameters and their valid ranges. Although SAS was developed to support the analysis of any liquid-metal-cooled nuclear reactor, the testing described in this document primarily focuses on the verification of SAS capabilities as they relate to a generic pool-type Sodium Fast Reactor (SFR).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Additive Manufactured Composite Phase-Change Material for Thermal Energy Storage Applications

Phase-change materials play a critical role in industrial energy storage applications to drive efficiency improvements, thermal energy management, and carbon emissions reductions. Recently, it has been shown that rapid solidification of alloys with metastable immiscibility in the liquid phase has the potential to form unique microstructures in which a low-melting phase is uniformly distributed in a high-melting matrix. This feature can be exploited using additive manufacturing to produce components with complex geometries containing such unique phase-change microstructures. Phase-field simulations utilizing high-performance computing were used to provide a detailed description of the evolution of the active phase during service in terms of their morphology and composition in different polycrystalline matrix grain morphologies that are typically produced during additive manufacturing. Phase field simulations were performed using, MEUMAPPS-SL (Microstructure Evolution Using Massively Parallel Phase-field Simulations – Solid Liquid) code that was developed in-house by the Oak Ridge National Laboratory. The simulations utilized the capabilities of the Kestrel supercomputer at the National Renewable Energy Laboratory. The simulation results were compared with experimental results generated at Siemens Energy, Inc. The results indicate that the kinetics of liquid spreading along grain boundaries is largely determined by the mobility of the triple line along the intersection of the grain boundary liquid and the grain boundary plane.

25 ENERGY STORAGE↗

The Effects of Realistic Impact-processed Asteroid Topology on Atmospheric Airbursts

When small asteroids (∼10–200 m) enter Earth’s atmosphere they can break up before hitting the ground, releasing a considerable amount of energy in what is known as an atmospheric airburst. To date, numerous studies have examined how an asteroid’s strength, size, shape, and entry characteristics affect the breakup process; but few have assessed the effects of heterogenous internal topologies. We present a two-step high-fidelity simulation approach, which we use to model the atmospheric breakup of asteroids with realistic impact-processed internal topologies and their associated ground effects. In the first step, we model the asteroid as it is impacted to generate an “impact-processed” topology. We then map the resulting fractures (i.e., damage field) from that simulation to the initial state of an atmospheric breakup simulation. For both phases, we use the smoothed particle hydrodynamics code Spheral++. As a demonstrative example, we apply our new simulation pipeline to a Tunguska-scale impactor (50 m diameter, 20 km s −1 entry velocity, and 45° angle) in a case study comparing impact-processed and fully intact asteroids in both planar 2D and full 3D. For sufficiently strong asteroids, we find that impact processing generally causes the asteroid to break up at higher altitudes. We also observe that impact-processed asteroids break up into smaller fragments than objects with equivalent properties that have not been impact-processed.

Astronomy and AstroPhysics↗

Arabidopsis GALACTURONOSYLTRANSFERASE (GAUT) 1 synthesizes a homogalacturonan tightly bound to the cell wall and required for cell expansion

Arabidopsis GALACTURONOSYLTRANSFERASE1 (GAUT1) synthesizes homogalacturonan (HG), the most abundant pectin in growing plant cells. GAUT1 has the greatest in vitro enzyme activity of the six confirmed Arabidopsis HG biosynthetic GAUTs, but its biological activity remains elusive. Here we show that Arabidopsis GAUT1 homozygous mutants have a severe dwarfed seedling phenotype, survive several weeks as 2 to 3 mm seedlings, and have severely reduced shoot and root growth and hypocotyl epidermal, cortex and endodermal cell size. gaut1-1 pollen tubes are shorter than WT with increased bursting. Complementation of homozygous gaut1-1 with GAUT1 coding sequence driven by the GAUT1 promoter restored WT-like growth. The extreme dwarf phenotype of homozygous gaut1-1 seedlings precluded their use for detailed cell wall analysis, thus suspensions cultures were produced from callus generated from mutant and WT seedlings. Homozygous gaut1-1 suspension cells were smaller than WT with ∼30% reduced wall GalA content compared to WT. Sequential extraction of the walls with increasingly harsh solvents and sugar composition analysis revealed reduced GalA content in only the 4M KOH post-chlorite fraction, indicating that GAUT1-synthesized HG was held tightly in the wall by direct or indirect hydrogen bonding and/or oxidation-sensitive linkages. Treatment of wall fractions with endopolygalacturonase to hydrolyze HG and gel electrophoretic separation of hydrolysates exposed an HG-associated doublet band markedly downregulated in the homozygous gaut1-1 4M KOH post-chlorite fraction and to a lesser extent in 4M KOH and sodium chlorite fractions. NMR analysis identified the band as rhamnogalacturonan (RG)-II. Super resolution microscopy using anti-HG antibodies showed that, compared to WT, the homozygous gaut1-1 hypocotyl epidermal and callus cells had reduced content and length of HG nanofilaments, HG fibers associated with cell expansion in Arabidopsis. The results demonstrate that GAUT1-synthesized HG resides in a tightly-cell-wall-bound, RG-II-containing polymer required for HG nanofilament formation and seedling cell expansion.

Atmodjo↗

matsim-agents v1.0

matsim-agents is a multi-agent AI framework for atomistic materials simulation and discovery. It orchestrates large language models (LLMs), machine-learned interatomic potentials (MLIPs), and DFT codes into a single agentic loop running on laptops and DOE leadership-class supercomputers. MULTI-AGENT ORCHESTRATION A LangGraph state machine with three nodes: a Planner that converts a natural-language research objective into structured tasks; an Executor that dispatches atomistic tools and loops until the queue is empty; and an Analyst that summarizes results into a human-readable report. State is checkpointed after every step and human-in-the-loop gates can be inserted at any edge. HYPOTHESIS-DRIVEN DISCOVERY CHAT An interactive REPL (matsim-agents chat) that couples LLM dialogue with atomistic simulation. Chemical formulas are automatically detected in conversation turns and trigger a full crystal-phase exploration: structure generation → relaxation → stability scoring → result injection back into the conversation, creating a closed hypothesis-refinement loop. CRYSTAL PHASE ENUMERATION Given a composition, the phase explorer enumerates prototypes by stoichiometry: elemental (fcc/bcc/hcp/sc/diamond), binary 1:1 (rocksalt/CsCl/zincblende/ wurtzite/fluorite/rutile), ternary 1:1:3 (cubic perovskite), ternary 1:2:4 (perovskite + spinel), quaternary 1:1:2:6 (Fm-3m double perovskite). 2-D prototypes (graphene, h-BN, MoS2 2H/1T) and multilayer stacking are also supported via --include-2d and --num-layers. SUPERCELL GENERATION AND SITE DECORATION Auto-tiling to a minimum atom count (--min-atoms), explicit NxNxN tiling (--supercell), symmetry-distinct site decorations (--n-orderings), and isotropic lattice-scale sweeps (--lattice-scales) for volume bracketing. MLFF RELAXATION AND STABILITY SCORING HydraGNN (multi-headed GNN) drives structure relaxation via ASE with FIRE, BFGS, or BFGSLineSearch. Stability output: delta-E/atom ranking across phases and a max-residual-force dynamical-stability proxy. Other MLIPs (MACE, NequIP, Orb) can be plugged in through the same interface. DFT BACKENDS Quantum ESPRESSO pw.x and VASP 6.6 are first-class labellers. Both have validated GPU builds and SLURM/PBS launchers for three DOE platforms: Frontier (AMD MI250X, ROCm), Aurora (Intel PVC, oneAPI), Perlmutter (NVIDIA A100, CUDA). QE produces ~100 binaries (pw.x, ph.x, epw.x, ...). VASP supports scf, relax, vc-relax, and vc-relax-shape run types. ACTIVE-LEARNING LOOP matsim-agents al run CONFIG.yaml drives an iterative HydraGNN-DFT loop: MD generates candidates → ensemble/MC-dropout uncertainty selects the most informative → DFT labels them in parallel inside one allocation → dataset grows → HydraGNN retrains → repeat. DFT backend is a single YAML toggle (dft.backend: vasp | qe). LLM-generated seed structures are supported (no curated POSCAR library needed). Config uses ${VAR}, ${VAR:-default}, ${VAR:?msg} shell-style substitution for cross-user/cross-site portability. LLM BACKENDS Ollama (local, default), vLLM (HPC multi-GPU serving), OpenAI, Anthropic, HuggingFace Transformers+Accelerate. Selected at runtime via flag or env var with no code changes. HPC PORTABILITY Same Python entry points run on Frontier (ROCm 7.2), Aurora (oneAPI), and Perlmutter (CUDA 12). DFT and ML stacks are never co-loaded in the same shell; they couple through the scheduler and filesystem. Advanced multi-node launchers (serve, discovery-chat, single-relaxation, active-learning, QE warm-start) are provided for all three platforms. CODABENCH COMPETITION BUNDLE A self-contained benchmark: 159 atomistic test structures across 11 material classes, 5 tasks (formation energy, forces, ML relaxation, AI-DFT relaxation, phase stability ranking), public/private leaderboard split (30/70), and four ready-to-run baselines: MACE-MP-0, HydraGNN, UMA, AllScAIP.

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗

Cosmological Hydrodynamics at Exascale: A Trillion-Particle Leap in Capability

Resolving the most fundamental questions in cosmology requires simulations that match the scale, fidelity, and physical complexity demanded by next-generation sky surveys. To achieve the realism needed for this critical scientific partnership, detailed gas dynamics must be treated self-consistently with gravity for end-to-end modeling of structure formation. Exascale computing enables simulations that span survey-scale volumes while incorporating key astrophysical processes that shape complex cosmic structures. We present results from CRK-HACC, a cosmological hydrodynamics code built for extreme scalability. Using separation-of-scale techniques, GPU-resident tree solvers, in situ analysis pipelines, and multi-tiered I/O, CRK-HACCexecuted Frontier-E: a four trillion particle full-sky simulation, over an order of magnitude larger than previous efforts. The run achieved 513.1 PFLOPs peak performance, processing 46.6 billion particles per second and writing more than 100 PB of data in just over one week of runtime. Frontier-E marks a significant advance in predictive modeling for next-generation cosmological science.

Frontiere, Nicholas [Argonne National Laboratory (↗