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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Development of the ARM Lagrangian Large-Scale Forcing Data (ARMLAGTRAJ) Value-Added Product Based on the lagtraj Framework

The Atmospheric Radiation Measurement (ARM) large-scale forcing data developed based on the constrained variational analysis (VARANAL) value-added product (VAP) (Zhang and Lin 1997, Zhang et al. 2001, Xie et al. 2004, Tang et al. 2019) has been widely used for single-column models (SCMs), cloud-resolving models (CRMs), and large-eddy simulation models (LESs) to understand and improve physical processes in models. Recently, the U.S. Department of Energy (DOE) ARM user facility conducted several major field campaigns using ship-based moving observational platforms. For example, the Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign focused on the role of subtropical marine-boundary layer (MBL) clouds, and the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign aimed to improve understanding of the coupled climate systems in the Arctic. Observations from moving platforms are critical to provide a comprehensive characterization of coupled-system processes associated with all stages of the cloud and/or sea-ice life cycle. Traditional ARM large-scale forcing data have been developed at fixed locations. They need to be extended to include these moving platforms to address data needs for ship-based field campaigns or to support LES modeling in a Lagrangian framework. With these considerations in mind, we develop ARM-type Lagrangian large-scale forcing data sets based on the lagtraj framework (Boeing et al. 2020) with notable enhancements in generating forcings that are more suitable for ARM field campaigns. The lagtraj is a novel tool that generates forcings for LES and SCM simulation in both Lagrangian and Eulerian perspective. This technical report focuses on the major changes we performed on the lagtraj algorithm and provides an overview of the ARM Lagrangian Large-Scale Forcing Data (ARMLAGTRAJ) value-added products.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Energy Transfer Mechanisms in Large Low-Bandgap Polymers from Time-Resolved Experiments and Nonadiabatic Molecular Dynamics Calculations

Conjugated polymers offer unprecedented chemical tunability for modulating energy transfer in a multitude of infrared light applications. In this work, we use a combination of time-resolved spectroscopic experiments and nonadiabatic molecular dynamics calculations to probe the photochemistry and nonradiative transitions in a recently synthesized narrow bandgap donor–acceptor conjugated polymer based on alternating cyclopentadithiophene and electronegative benzothiadiazole heterocycles. Using large-scale semi-empirical nonadiabatic molecular dynamics, which can treat a large 260-atom hexamer, we calculate an S 5 → S 1 lifetime of 34.75 fs, which is consistent with our time-resolved spectroscopic data. Our simulations suggest that vibronic motions of the central carbons in the cyclopentadithiophene functional groups are predominantly involved in the nonradiative transitions, and the excitation becomes more localized on a monomer fragment over time. The combined use of time-resolved experiments and nonadiabatic molecular dynamics calculations in this work provides mechanistic insight into chemical functionalities that can be tuned to enhance energy transfer in other prospective low-bandgap polymer materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Scalable Algorithms for Inverse Problems With High-Dimensional Parameter Spaces

Inverse problems, which involve inferring unknown parameters from observed data, present significant computational challenges, especially in large-scale settings with high-dimensional unknown parameters and nonlinear relationships between the unknowns and observations. Bayesian inference provides an approach for addressing these problems, often relying on sequential sampling methods like Markov chain Monte Carlo (MCMC) to approximate the posterior distribution of the parameters. However, MCMC methods become computationally demanding as the dimensionality of the problem increases, particularly in large-scale systems where likelihood evaluations rely on solving partial differential equations (PDEs) on large spatial domains with finely resolved meshes. To overcome these limitations, recent advancements have focused on designing scalable computa tional techniques – for both PDE simulations and sampling strategies – to make Bayesian methods feasible for high-dimensional problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Final DOE-ASR Report for the Project “Using LASSO to bridge the gap between model and observations and to learn about atmospheric convection”

Atmospheric convection spans a wide range of spatial and temporal scales and involves complex interactions with the surrounding dynamic and thermodynamic environment, particularly over tropical continental regions. These processes remain a major source of uncertainty in weather and climate models, including persistent biases in the diurnal cycle of convective precipitation that directly affect estimates of climate sensitivity. Addressing these challenges requires the combined use of high-resolution observations and cloud-resolving modeling frameworks. In this context, the DOE Atmospheric Radiation Measurement (ARM) program’s Large-Eddy Simulation ARM Symbiotic Simulation and Observation (LASSO) activity provides a powerful platform that pairs comprehensive observations with numerical simulations to enable process-level understanding of atmospheric convection. Within this context, this Research and Development Partnership Pilot (RDPP) project was designed to initiate and expand DOE ARM/ASR research capacity at minority-serving institutions, while advancing scientific understanding of convective processes over the Amazon rainforest. Consistent with the RDPP mission, the project emphasized partnership development, training, and workforce capacity building alongside exploratory research activities. On the scientific side, the project produced two peer-reviewed journal articles, and one manuscript currently under review (see list in section 3.1). Together, these studies combine long-term ARM observations and cloud-resolving and convection-permitting modeling to investigate the environmental controls on the shallow-to-deep convective transition during the Amazon wet season. The results demonstrate the central role of early-day moisture preconditioning and large-scale dynamical forcing in regulating isolated deep convection, provide mechanistic insight into convective evolution, and establish physically informed modeling frameworks for future sensitivity experiments. These scientific outcomes are described in sections 2.1 to 2.3 and were disseminated in 8 conference presentations (see section 3.2) and 5 invited talks (see section 3.3), reflecting broad engagement with our community. Equally important, the project achieved its RDPP capacity-building objectives (see section 2.4). A sustained research partnership was established among the University of Maryland, Baltimore County (UMBC), Morgan State University (MSU), and Howard University (HU), and extended to include collaboration with Pacific Northwest National Laboratory (PNNL). The project organized multiple multi-day training events focused on ARM data, LASSO simulations, and quantitative analysis methods, directly engaging students, postdoctoral researchers, and faculty across institutions. These activities broadened participation in ASR research and led to independent adoption of LASSO workflows by students beyond the immediate project team. Finally, the project successfully positioned the participating institutions to pursue future DOE research. Preliminary scientific results, coupled with strengthened partnerships and technical capacity, enabled the submission of follow-on proposals to DOE ASR funding opportunities. In this way, the project fulfilled the RDPP goal of seeding durable research capacity and laying the foundation for larger-scale, sustained engagement with DOE ARM and ASR programs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Generalizing the compressible pairwise interaction extended point-particle model

Ejecta physics plays an important role in material interfaces that are impacted by a strong shock wave. When a shock impacts a rough surface of solid material and melts it, the Richtmyer–Meshkov instability grows perturbations on the surface, which can eject particles. After release, the ejecta travel through the post-shock compressible flow. To accurately simulate a large number of ejecta particles, an Euler–Lagrange approach is preferred, which requires modeling the subgrid-scale physics involved with fluid–particle interactions. We generalize the previous work from Hsiao et al. (2023) to consider systems of moving particles subject to any loading shock. The following improvements were made: (1) Particles are allowed to move relative to each other (2) Non-planar shocks are accounted for along with allowing for variable shock speeds. As a result, the generalized algorithm was tested with particle-resolved simulations for canonical test cases. The results of these tests are discussed and analyzed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

GR-Athena++: General-relativistic Magnetohydrodynamics Simulations of Neutron Star Spacetimes

We present the extension of GR-Athena++ to general-relativistic magnetohydrodynamics (GRMHD) for applications to neutron star spacetimes. The new solver couples the constrained transport implementation of Athena++ to the Z4c formulation of the Einstein equations to simulate dynamical spacetimes with GRMHD using oct-tree adaptive mesh refinement. We consider benchmark problems for isolated and binary neutron star spacetimes demonstrating stable and convergent results at relatively low resolutions and without grid symmetries imposed. The code correctly captures magnetic field instabilities in nonrotating stars with total relative violation of the divergence-free constraint of 10 –16 . It handles evolutions with a microphysical equation of state and black hole formation in the gravitational collapse of a rapidly rotating star. For binaries, we demonstrate correctness of the evolution under the gravitational radiation reaction and show convergence of gravitational waveforms. We showcase the use of adaptive mesh refinement to resolve the Kelvin–Helmholtz instability at the collisional interface in a merger of magnetised binary neutron stars. GR-Athena++ shows strong scaling efficiencies above 80% in excess of 10 5 CPU cores and excellent weak scaling is shown up to ~5 × 10 5 CPU cores in a realistic production setup. GR-Athena++ allows for the robust simulation of GRMHD flows in strong and dynamical gravity with exa-scale computers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Development of a coupled experimental–computational approach for engineering optimization of spout-fluidized bed particle coating systems

The design of spout-fluidized bed (SFB) coating systems for nuclear particle fuels typically relies on trial-and-error processes, comprising iterative and time-consuming coating deposition experiments and post-deposition characterization. At an engineering scale, this approach to guided SFB system design is inefficient, highlighting the need for streamlined experimental methodologies which can correlate fluidization conditions to downstream coating outcomes. In this study, we combine time-resolved particle image velocimetry (PIV) with CFD–DEM simulations to benchmark hydrodynamic behavior in a 3D spout-fluidized bed. By exploiting easily accessible optical measurements of particle motion at the bed wall and within the spouting region, we obtain quantitative velocity fields that can be directly compared with model predictions of the occluded bed region, without resorting to complex imaging and characterization techniques such as X-ray or magnetic resonance tomography. Experimental benchmarking reveals strong agreement between CFD–DEM and PIV in the spout and annulus regions, while discrepancies near the wall highlight areas for future model development. Here, the proposed integrated experimental–numerical framework will enable a direct connection between measured variables and numerically predicted fluidization performance of dense, surrogate nuclear particle fuel feedstock such that experimental SFB component design can be rapidly evaluated, informing design decisions for nozzle geometry and operating conditions. Future work will extend this framework by correlating quantified fluidization metrics across nozzle geometries and operating conditions with the resulting coating morphology, microstructure, and uniformity. Establishing these correlations will enable predictive links between hydrodynamic performance and coating quality, providing a rational, scalable basis for optimizing SFB design prior to coating deposition.

CFD/DEM↗
DOE OSTI2025

Terahertz-field activation of polar skyrons

Unraveling collective modes arising from coupled degrees of freedom is crucial for understanding complex interactions in solids and developing new functionalities. Unique collective behaviors emerge when two degrees of freedom, ordered on distinct length scales, interact. Polar skyrmions, three-dimensional electric polarization textures in ferroelectric superlattices, disrupt the lattice continuity at the nanometer scale with nontrivial topology, leading to previously unexplored collective modes. Here, using terahertz-field excitation and femtosecond x-ray diffraction, we discover subterahertz collective modes, dubbed “skyrons”, which appear as swirling patterns of atomic displacements functioning as atomic-scale gearsets. The key to activating skyrons is the use of the THz field that couples primarily to skyrmion domain walls. Momentum-resolved time-domain measurements of diffuse scattering reveal an avoided crossing in the dispersion relation of skyrons. Atomistic simulations and dynamical phase-field modeling provide microscopic insights into the three-dimensional crystallographic and polarization dynamics. The amplitude and dispersion of skyrons are demonstrated to be controlled by sample temperature and electric-field bias. The discovery of skyrons and their coupling with terahertz fields opens avenues for ultrafast control of topological polar structures.

ferroelectrics↗
DOE OSTI2026

Thermal Reservoir Networks for Modularly Expandable Thermal Microgrids

The Department of Defense (DoD) faces the substantial challenge of cost-effectively retrofitting one to two installations per month, each comprising approximately 1,000 buildings, to improve resilience, reduce energy consumption, and enhance energy supply security. Achieving these objectives requires optimal system selection and effective risk mitigation during system integration. To address this need, we introduce Platform-Based Design (PBD), a structured, hierarchical methodology adapted from other industrial sectors to the domain of energy system retrofits. We demonstrate the effectiveness of PBD through a techno-economic feasibility study comparing geothermal-coupled thermal energy networks (TENs) with conventional energy systems for heating, cooling, and powering 17 buildings at Joint Base Andrews (JBA) in Maryland. Our analysis illustrates that the PBD approach enables rigorous, data-driven, sequential decision making, resulting in a family of Pareto-optimal systems, among which the TEN emerged as the most promising solution. The selected TEN design integrates geothermal borefields, heat recovery heat pumps, photovoltaic (PV) arrays, and battery storage. Compared to the baseline system – gas heating combined with air-source chillers – the proposed TEN reduces annual imported energy by 74% and peak electricity demand by 45%, achieves a levelized cost of energy of $\$0.210$/kWh, and substantially enhances resilience. Life-cycle costs increase by approximately 6%, and initial investment costs are about 2.5 times higher than the baseline. However, if central plant infrastructure, district loops, and utility-scale PV and battery systems are privately funded and operated, the initial investment would fall below the baseline system cost. Critical to achieving these significant performance improvements were detailed nonlinear dynamic simulations coupling geothermal heat transfer, energy system operation, and realistic feedback control logic. These simulations identified essential design modifications and control strategy refinements that substantially reduced energy use, peak demand, and compressor shortcycling, thereby improving durability and reliability—issues that would have been significantly more expensive to resolve during operation. Additionally, the verification step highlighted sensitivities to key design parameters that could reduce initial investment by approximately $\$2$ million and reduce annual life-cycle costs more than $\$300,000$. We recommend adopting the PBD methodology for future feasibility studies and TEN pilot projects to gain valuable operational experience. Furthermore, we recommend that DoD invest in transferring and scaling the PBD methodology to other installations. This entails developing standardized computational frameworks and component libraries as well as training industry in conducting PBD. Such investments would enable rapid, robust, reliable, and cost-effective retrofits, supporting DoD’s ambitious energy system modernization goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Improving the QBO Forcing by Resolved Waves With Vertical Grid Refinement in E3SMv2

Abstract The quasi‐biennial oscillation (QBO) is the dominate mode of variability in the tropical stratosphere and plays an important role in stratospheric dynamics and chemistry. The QBO is notably deficient in many climate models, including the Energy Exascale Earth System Model (E3SM) developed by the US Department of Energy. In this work, we refine the lower stratospheric vertical grid spacing from roughly 1 km to 500 m to facilitate more realistic equatorial wave activity in the lower stratosphere in E3SM version 2. The refinement results in a simulated QBO with a reasonable amplitude and easterly‐westerly transition in both directions, but still has a longer period than observed, slower easterly downward propagation speed, and shallower vertical depth. Similar refinement in the multi‐scale modeling framework configuration of E3SM yields similar improvements. By analyzing the forcing contributions from different wave types, we find that most of the QBO forcing still comes from parameterized gravity wave drag from convection. The improved QBO forcing contributions from resolved waves, especially equatorial Kelvin waves and resolved small scale waves, can be attributed to the grid refinement.

E3SM↗
DOE OSTI2024

Large eddy simulation of a supersonic lifted hydrogen flame: Impacts of Lewis, turbulent Schmidt and Prandtl numbers

Parametric large eddy simulations (LES) of a supersonic lifted hydrogen flame are reported. The emphases are on two aspects: impacts of (1) Lewis number (Lei of the ith species) and (2) turbulent Schmidt and Prandtl numbers (⁠Sc t and Pr t ⁠) on supersonic turbulent flame and flow structures. Five cases are considered: species-specific Le i , Sc t = Sr t = 1.0 (C 0 ); unity Le i , Sc t = Pr t = 1.0 (C 1 ); species-specific Sc t = 0.5, Pr t = 1.0 (C 2 ); species-specific Le i , Sc t = 1.0, Pr t = 0.5 (C 3 ); and species-specific Le i , Sc t = Pr t = 0.5 (C 4 ). Numerical results of instantaneous and/or time-averaged species mole fractions, mixture fraction, heat release rate, flame base location, and mixed modes of premixed and diffusion combustion are compared between cases C 0 and C 1 . Differences in auto-ignition locations and strengths and flame structures and stabilization specify the impacts of Lewis number. They are triggered by different predictions of species mass and thermal diffusions at fuel-coflow and/or coflow-ambient air mixing layers. These differences are rationalized by a scale analysis of mass/thermal diffusion and convection for case C 0 , which suggests the relatively low but non-negligible former against the latter. Cases C 0 and C 2 –C 4 barely see differences in terms of instantaneous and/or time-averaged temperature, velocity, and mixed combustion modes except for further downstream areas where combustion occurs. Both Sc t and Pr t impose less significant influences than Lewis number, as sub-grid scale mass/thermal diffusion is subordinate to its resolved counterpart according to their scale analysis for case C 4 .

42 ENGINEERING↗
DOE OSTI2026

pH-Driven Restructuring of Hydration Layers and Cation Adsorption at the Alumina–Water Interface

Oxide−water interfaces underpin ion separations, catalysis, and electrochemical energy technologies, where the electrical double layer (EDL) controls adsorption, transport, and reactivity. However, the molecular-scale links between pHdependent surface protonation, hydration-layer structure, and counterion adsorption remain poorly defined. Here, we combine in situ crystal truncation rod (CTR) and resonant anomalous X-ray reflectivity (RAXR) with streaming potential measurements and ab initio molecular dynamics (AIMD) simulations to resolve the chemical and structural evolution of the EDL at the single-crystal alumina (012)−water interface in 10 mM Rb + over pH 3−12. CTR measurements reveal two distinct adsorbed water layers at ∼2.2 and ∼3.5 Å above the surface. Each water layer shifts toward the substrate at transition pHs near 6.5 and 10.6, respectively, reflecting changes in primary hydration layer structure in response to the deprotonation of bridging and terminal aluminol groups. RAXR shows a 10-fold increase in Rb + coverage and a decrease in mean adsorption height from ∼3.5 to ∼2.7 Å with increasing pH, indicating enhanced counterion binding accompanied by Stern layer contraction. Streaming potential measurements demonstrate that the zeta potential, i.e., the potential at the hydrodynamic shear plane, is positive at pH 3 and becomes negative at pH ≥ 3.5. The negative charge magnitude increases with increasing pH, consistent with progressive surface deprotonation at higher pH. AIMD identifies inner- and outer-sphere Rb+ complexes whose adsorption heights and coordination geometries depend sensitively on the protonation state of surface oxygens, providing atomistic support for the experimentally inferred trends. These measurements establish two discrete, site-specific pH transitions in hydration-layer structure that track aluminol (de)protonation and quantitatively link them to a pH-driven contraction of the Stern layer (increasing Rb + coverage and decreasing adsorption height). This provides a direct structural basis for connecting surface acid−base chemistry to ion binding distances at an oxide−water interface.

Adsorption↗
DOE OSTI2025

Ship‐Based Lidar Evaluation of Southern Ocean Low Clouds in the Storm‐Resolving General Circulation Model ICON and the ERA5 and MERRA‐2 Reanalyses

Global storm resolving models (GSRMs) represent the next generation of global climate models. One of them is a 5-km Icosahedral Nonhydrostatic Weather and Climate Model (ICON). Its high resolution means that parameterizations of convection and clouds, including subgrid-scale clouds, are omitted, relying on explicit simulation but necessarily utilizing microphysics and turbulence parameterizations. Standard-resolution (10–100 km) models, which use convection and cloud parameterizations, have substantial cloud biases over the Southern Ocean (SO), adversely affecting radiation and sea surface temperature. The SO is dominated by low clouds, which cannot be observed accurately from space due to overlapping clouds, attenuation, and ground clutter. We evaluated SO clouds in ICON and the ERA5 and MERRA-2 reanalyzes using approximately 2400 days of lidar observations and 2300 radiosonde profiles from 31 voyages and a Macquarie Island station during 2010–2021, compared to the model and reanalyzes using a ground-based lidar simulator. We found that ICON and the reanalyzes underestimate the total cloud fraction by about 10% and 20%, respectively. ICON and ERA5 overestimate the cloud occurrence peak at about 500 m, associated with underestimated lower tropospheric stability and overestimated lifting condensation level. The reanalyzes strongly underestimate fog and very low-level clouds, and MERRA-2 underestimates cloud occurrence at almost all heights. Outgoing shortwave radiation is overestimated in MERRA-2, implying a “too few, too bright” cloud problem. SO cloud and fog biases are a substantial issue in the analyzed model and reanalyzes and result in shortwave and longwave radiation biases.

Kuma, Peter [Stockholm Univ. (Sweden); Univ. of Ca↗
DOE OSTI2025

Microwave microscope studies of trapped vortex dynamics in superconductors

Trapped vortices in superconductors introduce residual resistance in superconducting radio-frequency (SRF) cavities and disrupt the operation of superconducting quantum and digital electronic circuits. Understanding the detailed dynamics of trapped vortices under oscillating magnetic fields is essential for advancing these technologies. We have developed a near-field magnetic microwave microscope to study the dynamics of a limited number of trapped vortices under the probe when stimulated by a localized rf magnetic field. By measuring the local second-harmonic response (𝑃 2⁢f ) at subfemto-Watt levels, we isolate signals exclusively arising from trapped vortices, excluding contributions from surface defects and Meissner screening currents. Toy models of niobium superconductor hosting vortex pinning sites are introduced and studied with time-dependent Ginzburg-Landau (TDGL) simulations of probe/sample interaction to better understand the measured second-harmonic response. The simulation results demonstrate that the second-harmonic response of trapped vortex motion under a localized rf magnetic field shares key features with the experimental data. Here, this measurement technique provides access to vortex dynamics at the micrometer scale, such as depinning events and spatially resolved pinning properties, as demonstrated in measurements on a niobium film with an antidot flux pinning array.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Resolving Mesoscale Convective Systems: Grid Spacing Sensitivity in the Tropics and Midlatitudes

Abstract Mesoscale convective systems (MCSs) are a critical global water cycle component and drive extreme precipitation events in tropical and midlatitude regions. However, simulating deep convection remains challenging for modern numerical weather and climate models due to the complex interactions of processes from microscales to synoptic scales. Recent models with kilometer‐scale horizontal grid spacings offer notable improvements in simulating deep convection compared to coarser‐resolution models. Still, deficiencies in representing key physical processes, such as entrainment, lead to systematic biases. Additionally, evaluating model outputs using process‐oriented observational data remain difficult. This study presents an ensemble of MCS simulations with spanning the deep convective gray zone ( from 12 km to 125 m) in the Southern Great Plains of the U.S. and the Amazon Basin. Comparing these simulations with Atmospheric Radiation Measurement (ARM) wind profiler observations, we find greater sensitivity in the Amazon Basin compared to the Great Plains. Convective drafts converge structurally at sub‐kilometer scales, but some deficiencies remain. In both regions, simulated up and downdrafts are too deep and extreme downdrafts are not strong enough. Furthermore, Amazonian updrafts are too strong. Overall, we observe higher sensitivity in the tropics, including an artificial buildup in vertical kinetic energy at scales of , suggesting a need for 250 m in this region. Nevertheless, bulk convergence—agreement of storm‐average statistics—is achievable with kilometer‐scale simulations within a 10% error margin with 1 km providing a good balance between accuracy and computational cost.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Efficiently resolving the terrestrial-aquatic interface in E3SM with sub-grid methods to improve coastal simulations (Final Technical Report)

The broad goal of this project was to extend the capabilities of MPAS‐Ocean, the ocean component of DOE’s Energy Exascale Earth System Model (E3SM), to better resolve the hydrodynamics of the terrestrial‐aquatic interface without significantly increasing computing resource requirements. Specifically, our goal was to better resolve the small-scale features across the terrestrial‐aquatic interface which includes the low lying coastal floodplain and a dendritic network of hydraulically efficient channels connected to estuarine systems and back bays, barrier islands and high energy inlets. The processes driving flow across the terrestrial‐aquatic interface include upland and floodplain hydrology, tides, wind and atmospheric pressure (including coastally generated storm surge across continental shelves and within estuaries and bays), wind waves and water temperature and salinity gradients.

58 GEOSCIENCES↗
DOE OSTI2024

Massive all-atom analysis of 2D materials with quantum properties (Final report)

Improvements in microscopy have enabled the acquisition of data at a scale that is difficult to process manually, making automated machine learning approaches to analyzing experimental images essential. In this project, we developed and applied machine learning (ML) workflows for atomic resolution scanning transmission electron microscopy (STEM) images. This development included improving both methodology as well as generating user-friendly codes. We developed machine learning architectures which, after training, automatically identify the location and types of defects throughout a material. We used these data to produce class-averaged images of 2D atomic coordinates with up to 0.3 pm precision, uncovering the structure and oscillations of long-range strain fields around point defects in WSe 2-2x Te 2x . We also resolved a long-standing problem in this field in the training of ML models, a lack of labeled experimental data, by developing a cycle-GAN that transformed simulated-generated labeled data into labeled data indistinguishable from experiment and therefore suitable for training. This removed the remaining parts of the ML data processing workflow where human intervention was still critical and therefore a bottleneck to working at scale. Codes have been developed and released for this full machine learning workflow. ML approaches to partially automate STEM acquisition were also developed. Finally we applied ML and other advanced data processing methods to several materials science problems in two-dimensional materials, including studying the evolution of hyperuniformity with defect concentration in WSe2, understanding phase transformations in transition metal dichalcogenides during in-situ heating in the STEM, and exploring how 2D interfaces transform from twisted into aligned structures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Accelerating high-order continuum kinetic plasma simulations using multiple GPUs

Kinetic plasma simulations solve the Vlasov-Poisson or Vlasov-Maxwell equations to evolve scalar-variable distribution functions in position-velocity phase space and vector-variable electromagnetic fields in configuration space. The immense computational cost of evolving high-dimensional variables, and their large number of degrees of freedom, often limits the utility of continuum kinetic simulations and presents a challenge when it comes to accurately simulating real-world physical phenomena. To address this challenge, we present techniques that accelerate and minimize the computational work required for a scalable Vlasov-Poisson solver. We show theoretical hardware compute and communication bounds for solving a fourth-order finite-volume Vlasov-Poisson system. These bounds are then used to inform and evaluate the design of performance portable algorithms for a multiple graphics processing unit (GPU) accelerated version of the Vlasov-Poisson solver VCK-CPU [1]. We demonstrate that the multi-GPU Vlasov solver implementation, VCK-GPU, simultaneously minimizes required inter-process data transfer while also being bounded by the machine network performance limits. This results in an overall strong scaling speedup per timestep of up to 40x in three-dimensional phase space (one position, two velocity coordinates) and 54x in four dimensional phase space (two position, two velocity coordinates) and a 341x increase in simulation throughput of the GPU accelerated code over the existing CPU code. The GPU code is also able to weak scale up to 256 compute nodes and 1024 GPUs. In conclusion, we demonstrate that the improved compute performance enables exploring configurations which were previously computationally infeasible, including resolving fine-scale distribution function filamentation and multi-species dynamics with realistic electron-proton mass ratios.

Continuum kinetics↗