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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Quantum-centric supercomputing for materials science: A perspective on challenges and future directions

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Computationally hard tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their resources for simulation, analysis, and data processing. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. Here in this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Relative phase stability of L1 2 and DO 22 /DO 23 structures in Al 3 Nb, Al 3 Zr and Al 3 V compounds

The relative stability of the different tri-aluminide (Al 3 M) phases in three binary systems (M = Zr, Nb and V) was assessed for their potential to form fine cubic L1 2 precipitates in additively manufactured alloys. Supersaturated thin films of Al-(8–30) at% M were sputtered and heat treated during in-situ x-ray diffraction (XRD) measurements to observe the temperature ranges of stability for each phase. As-sputtered films were then processed with laser tracks simulating additive manufacturing solidification conditions, and the formation of phases in the laser tracks was correlated with density functional theory (DFT) and nucleation rate calculations. We found that the metastable L1 2 structure is highly competitive with the stable DO 23 structure in the Al-Zr system, but much less stable than the DO 22 structure in the Al-Nb system, and both the DO 22 and Al 8 V 5 structure in the Al-V system. Furthermore, these experimental results were found to be in good agreement with the DFT and kinetic calculations, as we determined that the metastable L1 2 in Al-Zr only requires a small amount of undercooling to favor its nucleation over the stable DO 23 , suggesting additive manufacturing can be a viable pathway to develop Al-Zr alloys strengthened by a high volume fraction of L1 2 Al 3 Zr phase.

Perrin, Alice E. [Oak Ridge National Laboratory (O↗
DOE OSTI2025

NEML2: An efficient and modular multiphysics constitutive modeling library for hybrid computing environments

This paper presents NEML2, an open-source, high-performance library developed for constitutive material modeling, designed to support the flexible and modular development of models for complex material behavior. Building on the foundational structure of its predecessor, NEML, the NEML2 library introduces significant improvements, including enhanced vectorization, automatic differentiation, and seamless integration with PyTorch, facilitating the application of machine learning techniques in material simulations. NEML2 provides a C++ backend with Python bindings, enabling users to create custom material models that can be executed efficiently on both CPU and GPU platforms. The library also supports coupling with Multiphysics simulation frameworks like MOOSE, making it suitable for realistic simulations involving coupled physical processes. Rigorous quality assurance through unit and regression testing ensures the reliability of results, while the extensible, user-friendly design encourages collaboration and reproducibility across the scientific community. This paper provides an overview of NEML2’s architecture, core features, and applications, highlighting its impact on accelerating material qualification and advancing computational methods in materials science.

GPU↗
DOE OSTI2024

Quantum Molecular Charge-Transfer Model for Multistep Auger–Meitner Decay Cascade Dynamics

The fragmentation of molecular cations following inner-shell decay processes in molecules containing heavy elements underpins the X-ray damage effects observed in X-ray scattering measurements of biological and chemical materials, as well as in medical applications involving Auger electron-emitting radionuclides. Traditionally, these processes are modeled using simulations that describe the electronic structure at an atomic level, thereby omitting molecular bonding effects. This work addresses the gap by introducing a novel approach that couples Auger–Meitner decay to nuclear dynamics across multiple decay steps, by developing a decay spawning dynamics algorithm and applying it to potential energy surfaces characterized with ab initio molecular dynamics simulations. We showcase the approach on a model decay cascade following K-shell ionization of IBr and subsequent Kβ fluorescence decay. We examine two competing channels that undergo two decay steps, resulting in ion pairs with a total 3+ charge state. This approach provides a continuous description of the electron transfer dynamics occurring during the multistep decay cascade and molecular fragmentation, revealing the combined inner-shell decay and charge transfer time scale to be approximately 75 fs. In conclusion, our computed kinetic energies of ion fragments show good agreement with experimental data.

Ab initio molecular dynamics↗
DOE OSTI2024

Mesoscale Convective Systems Represented in High Resolution E3SMv2 and Impact of New Cloud and Convection Parameterizations

Mesoscale convective systems (MCSs) play an important role in modulating the global hydrological cycle, general circulation, and radiative energy budget. In this study, we evaluate MCS simulations in the second version of U.S. Department of Energy (DOE) Energy Exascale Earth System Model (E3SMv2). E3SMv2 atmosphere model (EAMv2) is run at the uniform 0.25? horizontal resolution. We track MCSs consistently in the model and observations using the PyFLEXTRKR algorithm, which defines MCS based on both cloud-top brightness temperature (Tb) and surface precipitation. Results from using Tb only to define MCS, commonly used in previous studies, are also discussed. Furthermore, sensitivity experiments are performed to examine the impact of new cloud and convection parameterizations developed for EAMv3 on simulated MCSs. Our results show that EAMv2 simulated MCS precipitation is largely underestimated in the tropics and contiguous United States. This is mainly attributed to the underestimated precipitation intensity in EAMv2. In contrast, the simulated MCS frequency becomes more comparable to observations if MCSs are defined only based on cloud-top Tb. The Tb-based MCS tracking method, however, includes many cloud systems with very weak precipitation which conflicts with the MCS definition. This result illustrates the importance of accounting for precipitation in evaluating simulated MCSs. We also find that the new physics parameterizations help increase the relative contribution of convective precipitation to total precipitation in the tropics, but the simulated MCS properties are generally not improved. This suggests that simulating MCSs will remain a challenge for the next version of E3SM.

Zhang, Meng↗
DOE OSTI2025

Insights Into Nature-Based Climate Solutions: Managing Forests for Climate Resilience and Carbon Stability

Successful implementation of forest management as a nature-based climate solution is dependent on the durability of management-induced changes in forest carbon storage and sequestration. As forests face unprecedented stability risks in the face of ongoing climate change, much remains unknown regarding how management will impact forest stability, or how interactions with climate might shift the response of forests to management across spatiotemporal scales. Here, we used a process-based model to simulate multidecadal projections of forest dynamics in response to changes in management and climate. Simulations were conducted across gradients in forest type, edaphic factors, and management intensity under two alternate radiative forcing scenarios (RCP4.5 and RCP8.5). This allowed for the quantification of forest stability shifts in response to climate change, and the role of management in modulating that response, where ecosystem stability is characterized as the resilience and temporal stability of net primary production, aboveground biomass, and soil carbon. Our results indicate that forest structure is primarily shaped by management, but the same management strategy often produced divergent structures over time, due to interactions with regional climate change. We found that management can be used to increase stability and minimize the release of stored carbon by reducing mortality, but also highlight the regional dependency of management-induced changes in resilience to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Diffusion‐Based Uncertainty Quantification Method to Advance E3SM Land Model Calibration

Abstract Calibrating land surface models and accurately quantifying their uncertainty are crucial for improving the reliability of simulations of complex environmental processes. This, in turn, advances our predictive understanding of ecosystems and supports climate‐resilient decision‐making. Traditional calibration methods, however, face challenges of high computational costs and difficulties in accurately quantifying parameter uncertainties. To address these issues, we develop a diffusion‐based uncertainty quantification (DBUQ) method. Unlike conventional generative diffusion methods, which are computationally expensive and memory‐intensive, DBUQ innovates by formulating a parameterized generative model and approximates this model through supervised learning, which enables quick generation of parameter posterior samples to quantify its uncertainty. DBUQ is effective, efficient, and general‐purpose, making it suitable for site‐specific ecosystem model calibration and broadly applicable for parameter uncertainty quantification across various earth system models. In this study, we applied DBUQ to calibrate the Energy Exascale Earth System Model land model at the Missouri Ozark AmeriFlux forest site. Results indicated that DBUQ produced accurate parameter posterior distributions similar to those from Markov Chain Monte Carlo sampling but with 30 times less computing time. This significant improvement in efficiency suggests that DBUQ can enable rapid, site‐level model calibration at a global scale, enhancing our predictive understanding of climate impacts on terrestrial ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Quantifying the Resolution Sensitivity of the Kain–Fritsch Scheme Across the Gray Zone by Isolating Interactions: A TWP‐ICE Case Study

The resolution sensitivity of the Kain–Fritsch (KF) convection scheme and the role of interactions between the physics and dynamics within the gray zone (<10 km) were investigated using the Separate Physics and Dynamics Experiment (SPADE) framework. Two groups of experiments were conducted using the Weather Research and Forecasting (WRF) model via traditional (Tradition) runs and SPADE runs with resolutions of 1, 2, 4, and 8 km during the wet period of the Tropical Warm Pool–International Cloud Experiment (TWP‐ICE). Results show that the KF scheme simulates the weakened convective processes well as the resolution increases in both groups, and the changes in the convective variables with resolution in SPADE are smaller than in the Tradition group. This indicates the important effects of interactions between model components on convection parameterizations as the resolution changes. Additionally, the microphysics variables remain nearly unchanged with resolution in SPADE and weaken slightly in Tradition as the resolution decreases, suggesting the relatively weaker influences of model interactions for the resolved‐cloud parameterization. Therefore, the scale‐aware behavior of KF scheme is further strengthened in Tradition runs, primarily through inhibiting the strength of stratiform processes through physics–dynamics interactions and physical components.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A meshless stochastic method for Poisson–Nernst–Planck equations

A plethora of biological, physical, and chemical phenomena involve transport of charged particles (ions). Its continuum-scale description relies on the Poisson–Nernst–Planck (PNP) system, which encapsulates the conservation of mass and charge. The numerical solution of these coupled partial differential equations is challenging and suffers from both the curse of dimensionality and difficulty in efficiently parallelizing. We present a novel particle-based framework to solve the full PNP system by simulating a drift–diffusion process with time- and space-varying drift. We leverage Green’s functions, kernel-independent fast multipole methods, and kernel density estimation to solve the PNP system in a meshless manner, capable of handling discontinuous initial states. The method is embarrassingly parallel, and the computational cost scales linearly with the number of particles and dimension. We use a series of numerical experiments to demonstrate both the method’s convergence with respect to the number of particles and computational cost vis-à-vis a traditional partial differential equation solver.

Chemistry↗
DOE OSTI2025

Phase-based velocity extraction method for photonic Doppler velocimetry with potential higher time resolution

We present an extension of the [Takeda et al., J. Opt. Soc. Am. 72, 156 (1982)] phase extraction method to heterodyne photonic Doppler velocimetry applications. The method yields results equivalent to those obtained by the short-time Fourier transform (STFT), while offering potential improvements in time resolution. Unlike STFT, which relies on window functions, such as the Hamming window, that emphasize central data points and diminish the influence of edges, the extended Takeda method utilizes all data uniformly. This uniform treatment allows for the derivation of empirical equations that directly relate velocity error to the actual time resolution rather than to the local analysis duration. The established equation provides a useful metric for both optimizing hardware configuration and guiding data analysis. Simulation and experimental results confirm that, for a given dataset, specifying a target time resolution yields consistent velocity errors for both methods. These findings underscore the Takeda method’s advantages, particularly its potential higher time resolution and reduced computational burden, making it a valuable tool for high-throughput applications such as laser dynamic compression experiments.

Computer simulation↗
DOE OSTI2024

Investigations of atomic and molecular processes of NBI-heated discharges in the MAST Upgrade Super-X divertor with implications for reactors

This experimental study presents an in-depth investigation of the performance of the MAST-U Super-X divertor during NBI-heated operation (up to 2.5 MW) focussing on volumetric ion sources and sinks as well as power losses during detachment. The particle balance and power loss analysis revealed the crucial role of Molecular Activated Recombination and Dissociation (MAR and MAD) ion sinks in divertor particle and power balance, which remain pronounced in the change from ohmic to higher power (NBI heated) L-mode conditions. The importance of MAR and MAD remains with double the absorbed NBI heating. MAD results in significant power dissipation (up to ${\sim} 20\%$ of $P_\textrm{SOL}$), mostly in the cold ($T_e \lt 5$ eV) detached region. Theoretical and experimental evidence is found for the potential contribution of $D^-$ to MAR and MAD, which warrants further study. These results suggest that MAR and MAD can be relevant in higher power conditions than the ohmic conditions studied previously. Post-processing reactor-scale simulations suggests that MAR and MAD can play a significant role in divertor physics and synthetic diagnostic signals of reactor-scale devices, which are currently underestimated in exhaust simulations. This raises implications for the accuracy of reactor-scale divertor simulations of particularly tightly baffled (alternative) divertor configurations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

AI for nuclear physics: the EXCLAIM project

An overview of the recent activity of the newly funded EXCLusives with AI and Machine learning (EXCLAIM) collaboration is presented. The main goal of the collaboration is to develop a framework to implement AI and machine learning techniques in problems emerging from the phenomenology of high energy exclusive scattering processes from nucleons and nuclei, maximizing the information that can be extracted from various sets of experimental data, while implementing theoretical constraints from lattice QCD. A specific perspective embraced by EXCLAIM is to use the methods of theoretical physics to understand the working of ML, beyond its standardized applications to physics analyses which most often rely on industrially provided tools, in an automated way.

Analysis and statistical methods↗
DOE OSTI2025

Ice nucleation by volcanic ash greatly alters cirrus cloud properties

The formation of ice crystals in the atmosphere strongly affects cloud properties and climate. While volcanic ash (VA) has been shown to nucleate ice crystals efficiently in laboratory settings, its importance for ice formation in the atmosphere remains elusive. Here, we show evidence of cirrus modification by volcanic eruptions through ice nucleation on VA, revealed by abrupt changes in cirrus properties following volcanic eruptions based on satellite measurements. The distinct changes captured are a phenomenal decrease in number, an increase in size of ice crystals in cirrus clouds, and an increase in cirrus occurrences after ash-rich volcanic eruptions. Conversely, no such changes were detected following the ash-poor eruption. We propose a cirrus formation mechanism where VA nucleates ice heterogeneously, suppressing homogeneous freezing and resulting in fewer but larger ice crystals. This suppression of homogeneous freezing by VA is supported by process-level cloud microphysical simulations. Our findings advance the understanding of aerosol–ice cloud interactions and illuminate cirrus geoengineering.

Lin, Lin [Texas A & M Univ., College Station, TX (↗
DOE OSTI2026

Surface Quantitative Precipitation Estimates (SQUIRE) of Snow Water Equivalent from the Surface Atmospheric Integrated Field Laboratory

The upper Colorado River basin is the primary source of water for 40 million people. With declining snowpack in the basin, forecasting hydrological budgets in the Southwest United States is more important than ever. However, due in part, to a lack of reliable observations of precipitation in complex terrain, hydrological models struggle to assess and forecast snowpack snow water equivalent (SWE) in the upper Colorado River basin (UCRB). Therefore, the need for more reliable SWE forecasts in the UCRB motivated the U.S. Department of Energy Atmospheric Radiation Measurement Facility’s Surface Atmospheric Integrated Field Laboratory (SAIL) that occurred from June 2021 to June 2023. During SAIL, the X-band precipitation radar from Colorado State University conducted volume scans sampling the precipitation properties over the UCRB. The ARM facility developed a gridded Surface Quantitative Precipitation Estimates (SQUIRE) product from the radar observations. To do this, various daily SWE estimates from radar using the radar reflectivity factor Z e and specific differential phase K dp were compared against ground-based precipitation gauges. SWE in precipitation calculated from Wolfe and Snider’s S–Z e estimator was in best agreement with the rain gauges for the days when SWE < 12 mm. For days with SWE > 12 mm, the WSR-88D Intermountain West relationship had the best agreement with the precipitation gauges. Airborne snow depth observations show that SQUIRE captures regions of orographic enhancement in the mountains to the west and northwest of the SAIL study area, indicating that the scientific community should focus on understanding and ultimately simulating orographic atmospheric precipitation processes to improve UCRB snowpack SWE assessment and forecasting.

Hydrology↗
DOE OSTI2024

The EIC accelerator: design highlights and project status

The design of the electron-ion collider (EIC) at Brookhaven National Laboratory is well underway, aiming at a peak electron-proton luminosity of 10e+34 cm^-1·sec^-1. This high luminosity, the wide center-of-mass energy range from 29 to 141 GeV (e-p) and the high level of polarization require innovative solutions to maximize the performance of the machine, which makes the EIC one of the most challenging accelerator projects to date. The complexity of the EIC will be discussed, and the project status and plans will be presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

RESONANT MATCHING SECTION FOR CEBAF ENERGY UPGRADE

In order to prevent emittance growth during long stores of the proton beam at the future Electron-Ion Collider (EIC), we need to have some mechanism to provide fast cooling of the dense proton beams. One promising method is coherent electron cooling (CeC), which uses an electron beam to both ?measure? the positions of protons within the bunch and then apply energy kicks which tend to reduce their longitudinal and transverse actions. In this work, we discuss the under- lying physics of this process. We then discuss simulations which constrain the electrons to move only longitudinally in order to perform fast optimizations and long-term track- ing of the bunch evolution, and benchmark these results against fully 3D codes. Additionally, we discuss practical challenges, including the necessity of a high-quality elec- tron beam and sub-micron alignment of the electrons and protons.

Deitrick, K.↗
DOE OSTI2024

Dynamic Binary Complexes (DBC) as Super-Adjustable Viscosity Modifiers for Hydraulic Fracturing Fluids

In the preceding project year two, we refined three DBC formulations from a selection of over 50 different chemistries. The optimization study primarily encompassed testing for (i) reversibility extent, (ii) performance in the presence of chemical additives, (iii) adhesion and friction behavior during displacement in wellbores and pipelines, (iv) corrosion protection performance, and (v) injection performance with model fracture systems at the laboratory scale. Highly promising results obtained from all these tests signify the significant potential of DBCs in enhancing hydrocarbon recovery from unconventional reservoirs. The primary activities in the third project year included publishing experimental findings across multiple articles and conducting outreach initiatives. Throughout the year, we undertook tasks such as replicating experimental results, further optimizing various formulations and their associated experimental sets, and conducting additional tests to address missing components based on reviewer feedback and suggestions. We also explored the surfactant and friction-reduction aspects of selected formulations through drag reduction tests. In addition, we constructed an improved fracturing performance setup and performed flow injection tests. The specific DBC formulations focused on during this project period were A8/B1, A12/B5, and A10/B12. We also obtained results for additional DBC formulations and a select few commercial fracturing fluids for the purpose of comparison. Within the project's scope, we aim to enhance the experimental findings with the development of various models. The first two years focused on two key aspects: (i) the creation of a high-fidelity hydraulic fracturing model for non-Newtonian fluids to gain insights into the implementation of DBC fluids in fracking environments, and (ii) the development of a multiphase flow simulator for estimating total production, fluid saturation in the reservoir, and the creation of a fracture propagation model and kinetic Monte Carlo (kMC) models for diverse applications. In the third year, we delved into the fundamental nanostructural properties of DBCs, exploring aspects such as material chemistry, pH tunability, and control of DBC formation and stability. Subsequently, in the extension year, we conducted a systematic investigation of various building blocks containing primary, secondary, and tertiary amine functional groups to understand their impact on rheological and viscoelastic properties. Furthermore, we explored a Dissipative Particle Dynamics (DPD) model to simulate self-assembly processes with precision, creating a high-fidelity representation of relevant nanostructures. The tasks performed this year with the significant results obtained have been discussed in Section 2.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Compositional Variation Tests on DuraMelter 100 with LAW Sub-Envelope C1 Feed (LAWC22 Glass) in Support of the LAW Pilot Melter (Final Report)

This report provides the results from tests that were performed on a DM100 system with LAW Sub-Envelope Cl and Al feeds in support of the subsequent Pilot Melter tests. The principal objectives of the DM100 tests were to determine the processing characteristics as the simulated melter feed transitioned from the LAW Sub-Envelope Cl to the Sub-Envelope Al composition and to determine the effect of bubbling rate on production rate.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗