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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Cross-scale covariance for material property prediction

A simulation can stand its ground against an experiment only if its prediction uncertainty is known. The unknown accuracy of interatomic potentials (IPs) is a major source of prediction uncertainty, severely limiting the use of large-scale classical atomistic simulations in a wide range of scientific and engineering applications. Here we explore covariance between predictions of metal plasticity, from 178 large-scale (~10 8 atoms) molecular dynamics (MD) simulations, and a variety of indicator properties computed at small-scales (≤10 2 atoms). All simulations use the same 178 IPs. In a manner similar to statistical studies in public health, we analyze correlations of strength with indicators, identify the best predictor properties, and build a cross-scale “strength-on-predictors” regression model. This model is then used to estimate regression error over the statistical pool of IPs. Small-scale predictors found to be highly covariant with strength are computed using expensive quantum-accurate calculations and used to predict flow strength, within the statistical error bounds established in our study.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Aging studies of Dual functional materials for CO 2 direct air capture with in situ methanation under simulated ambient conditions: Ru thrifting for cost reduction

Dual function materials (DFMs) comprised of 0.25 %Ru, 6.1 %Na 2 O/γ-Al 2 O 3 //monolith were evaluated for about 250 hours time-on-stream (TOS) at various simulated ambient climate capture conditions followed by temperature swing methanation to 280 °C. Herein this paper focuses on the impact of thrifting Ru to low levels and the impact on performance. Results showed both stable CO 2 capture capacity and CH 4 production with 0.25 % Ru DFM deposited on a ceramic monolith. The CO 2 conversion to CH 4 production was decreased slightly by the Ru decrease from 1 % to 0.25 %. The capture capacity decreased since a lower Ru content reduces the complete decomposition of the Na 2 CO 3 precursor producing fewer active adsorption sites (“Na 2 O”). The deployment of a low Ru DFM monolith would significantly decrease the overall capital cost and give more potential for a large-scale direct air capture and methanation (DACM) application.

03 NATURAL GAS↗
DOE OSTI2022

Real-Time Inventory Change Detection for the Protactinium Decay Inventory of the Molten Salt Breeder Reactor

This work presents a novel monitoring method for detecting material loss from the decay inventory of the molten salt breeder reactor (MSBR) by monitoring for changes to the system dynamics using an isotopic ratio. Here the isotopic masses in the decay inventory of a MSBR were simulated under several material loss scenarios. In each case, the ratio of 231 Pa to 233 Pa served as a sensitive and lasting indicator of material loss. This isotope ratio quickly decreased outside the normal range after a material loss, and the ratio remained depressed for several years after the loss. The dynamics of this ratio were driven by the periodic batch discard from the decay inventory every 220 days, which was specified in the MSBR design to periodically remove fission product buildup. For this method, isotopic ratios were found to be rapid and enduring indicators of inventory change if they comprise a pair with a short half-life (e.g., 233 Pa) and a long half-life (e.g., 231 Pa) relative to the effective half-life induced by the driving system process (e.g., the batch discard cycle). Using such an isotope pair enabled a method to monitor for changes to the effective half-life of the system and by extension changes to the system inputs and outputs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Metal additive manufacturing simulation across length, time, and computing scales

Metal additive manufacturing (AM) offers a unique opportunity for production of advanced materials and complex geometries. However, variability in microstructure and properties challenges conventional approaches to design, process optimization, qualification, and materials selection. Modeling and simulation can improve understanding of AM processing and materials, but also poses major challenges for existing computational methods. Simultaneously, modern scientific computing hardware has become increasingly complex, most notably with the adoption of hybrid architectures such as Graphical Processing Units (GPUs). If appropriately utilized, emerging computational capabilities provide an opportunity to reveal new insight into AM processing and the resulting material structure and properties. In this review we describe the computational AM landscape, identify critical gaps, and highlight opportunities to impact the development and application of AM. First, the requirements and challenges of representative AM problem statements will be defined. Here, these problems range from scientific studies to industrial applications and are designed to capture the breadth of challenges facing the AM community. Next, the current state of AM modeling and simulation is evaluated, broken down by enabling hardware and software, process simulation, microstructure simulation, and property simulation. Each section describes the diversity of simulation approaches and associated trade-offs in physical fidelity and computational expense. Each area is then assessed based on their suitability and readiness for current and developing computational architectures. Lastly, the greatest opportunities for future research and application are highlighted, including gaps in modeling capabilities, opportunities for near-term application, and key scientific challenges.

additive manufacturing↗
NASA NTRSDate not supplied

TPSAS-NF1676L-13792-DND

Extreme structural requirements of future aerospace vehicles motivate the development of new, ultra-durable materials and game-changing methodologies for material certification and sustainment. Computational simulations spanning many orders of magnitude in length and time scales—from the nanoscale of underlying damage processes to the larger scales of continuum cracks—are being developed to support these requirements. Results of these simulations are used to deduce key aspects of material response to loads and environments, including: - The microstructural mechanics that govern metal fatigue crack initiation and growth - The variety and complexity of the dislocation-precipitate interac- tions that underpin plastic behavior and damage evolution - The energetic principles that govern the interaction of water with crack surfaces within a structural component - The mechanics of grain boundary separation Modeling the physics behind these metal fatigue behaviors is extremely complex, and requires intensive, high-fidelity simulations. The knowledge gained through these simulations, however, is forming the keystone for advanced material design and will enable development of more capable, reliable structures for aerospace vehicles.

Jacob Hochhalter↗
DOE OSTI2020

Ion-Exchange Kinetics of Alpha-Zirconium Phosphate Nanoplatelets for Application in Targeted Alpha Therapy

The loading and kinetics of uptake for the inorganic ion-exchange material, α-zirconium phosphate, Zr(HPO 4 ) 2 •H 2 O, were investigated with ions relevant to targeted alpha therapy including natural Cs + (as a surrogate for 221 Fr), natural Bi 3+ (as a surrogate for 213 Bi), and natural La 3+ (as a surrogate for 225 Ac). The narrow interlayer spacing of the α-phase (d = 7.6 Å) was found not to be advantageous with respect to rapid ion exchange, while converting the material to the hydrated Na-phase (d = 12.2 Å) allowed ion exchange to proceed more quickly, reaching equilibrium in under an hour. High loading was achieved for all three ions, at 72 ± 4% for Cs + and 95 ± 5% for La 3+ at pH 3 and 108 ± 10% for Bi 3+ at pH 0.5. Leaching profiles of the loaded materials in a simulated human plasma environment of 10 mM carbonate buffer at pH 7.4 and 37°C, showed negligible release, with less than 1% in all cases. Furthermore, the ion-exchange properties and overall benign nature of zirconium phosphate highlight these materials as a promising platform for a targeted alpha therapy drug-delivery vehicle.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2006

Platform for Testing Robotic Vehicles on Simulated Terrain

The variable terrain tilt platform (VTTP) is a means of providing simulated terrain for mobility testing of engineering models of the Mars Exploration Rovers. The VTTP could also be used for testing the ability of other robotic land vehicles (and small vehicles in general) to move across terrain under diverse conditions of slope and surface texture, and in the presence of obstacles of various sizes and shapes. The VTTP consists mostly of a 16-ft-(4.88-m)-square tilt table. The tilt can be adjusted to any angle between 0 (horizontal) and 25 . The test surface of the table can be left bare; can be covered with hard, high-friction material; or can be covered with sand, gravel, and/or other ground-simulating material or combination of materials to a thickness of as much as 6 in. (approx. 15 cm). Models of rocks, trenches, and other obstacles can be placed on the simulated terrain. For example, for one of the Mars- Rover tests, a high-friction mat was attached to the platform, then a 6-in.- ( 15 cm) deep layer of dry, loose beach sand was deposited on the mat. The choice of these two driving surface materials was meant to bound the range of variability of terrain that the rover was expected to encounter on the Martian surface. At each of the different angles at which tests were performed, for some of the tests, rocklike concrete obstacles ranging in height from 10 to 25 cm were placed in the path of the rover (see figure). The development of the VTTP was accompanied by development of a methodology of testing to characterize the performance and modes of failure of a vehicle under test. In addition to variations in slope, ground material, and obstacles, testing typically includes driving up-slope, down-slope, cross-slope, and at intermediate angles relative to slope. Testing includes recording of drive-motor currents, wheel speeds, articulation of suspension mechanisms, and the actual path of the vehicle over the simulated terrain. The collected data can be used to compute curves that summarize torque, speed, power-demand, and slip characteristics of wheels during the traverse.

Lindemann, Randel↗
DOE OSTI2022

Gaussian approximation potential for amorphous Si : H

Hydrogenation of amorphous silicon (a–Si : H) is critical for reducing defect densities, passivating midgap states and surfaces, and improving photoconductivity in silicon-based electro-optical devices. Modeling the atomic-scale structure of this material is critical to understanding these processes, which in turn is needed to describe c–Si/a–Si : H heterojunctions that are at the heart of modern solar cells with world-record efficiency. Density functional theory (DFT) studies achieve the required high accuracy but are limited to moderate system sizes of 100 atoms or so by their high computational cost. Simulations of amorphous materials have been hindered by this high cost because large structural models are required to capture the medium-range order that is characteristic of such materials. Empirical potential models are much faster, but their accuracy is not sufficient to correctly describe the frustrated local structure. Data-driven, machine-learned interatomic potentials have broken this impasse and have been highly successful in describing a variety of amorphous materials in their elemental phase. Here, we extend the Gaussian approximation potential (GAP) for silicon by incorporating the interaction with hydrogen, thereby significantly improving the degree of realism with which amorphous silicon can be modeled. We show that our Si : H GAP enables the simulation of hydrogenated silicon with an accuracy very close to DFT but with computational expense and run times reduced by several orders of magnitude for large structures. Here, we demonstrate the capabilities of the Si : H GAP by creating models of hydrogenated liquid and amorphous silicon and showing that their energies, forces, and stresses are in excellent agreement with DFT results, and their structure as captured by bond and angle distributions are in agreement with both DFT and experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Generalizable machine learning potentials for quantum-accurate predictions of non-equilibrium behavior in 2D materials

Machine learning interatomic potentials (ML-IAPs) are emerging as transformative tools in materials modeling, promising quantum-level accuracy at a fraction of the computational cost. However, their ability to generalize beyond equilibrium configurations and to reliably capture defect- and temperature-driven behavior remains underexplored. Here, we develop and benchmark two state-of-the-art ML-IAPs, Spectral Neighbor Analysis Potential (SNAP) and Allegro, on a comprehensive dataset for monolayer MoSe₂. Using density functional theory (DFT) as the reference, we evaluate their performance in capturing stress–strain behavior, phase transition energetics, defect evolution, edge stability, and fracture toughness. Allegro, a deep equivariant neural network potential, surpasses both SNAP and the classical Tersoff potential in accuracy, efficiency, and transferability. Importantly, both ML potentials accurately reproduce experimental fracture measurements and ab initio predictions of inversion domain formation—phenomena well beyond their training sets. Our findings establish ML-IAPs as viable replacements for traditional force fields in the study of non-equilibrium mechanical phenomena, enabling large-scale, high-fidelity simulations in 2D materials and beyond. In conclusion, this work provides a broadly applicable framework for data-driven modeling of structural and functional transformations under extreme conditions.

2D materials↗
DOE OSTI2020

Origin of short- and medium-range order in supercooled liquid Ge 3 Sb 2 Te 6 from ab initio molecular dynamics simulations

Phase-change materials such as Ge–Sb–Te compounds have attracted much attention due to their potential value in electrical data storage. In contrast to the amorphous and crystalline phases, supercooled liquids are far from being deeply understood despite their inevitable role in both amorphization and crystallization processes. To this end, we have studied the dynamics properties and structural characteristics of liquid and supercooled liquid Ge 3 Sb 2 Te 6 during the fast cooling process. As the temperature decreases, chemical bonds become more homogeneous, but coordination numbers of Ge, Sb and Te atoms change very little. Meanwhile, the structural order of short-range configuration is obviously enhanced. Further studies suggest that Ge-centered, Sb-centered and Te-centered configurations change to the more ordered defective octahedrons mainly by adjusting the bond-angle relationship and bond length, rather than just by changing the coordination environment. It is the more ordered octahedrons that promote the formation of medium-range order. Our findings provide a deep insight into the origin of local structural order in supercooled liquid Ge 3 Sb 2 Te 6 , which is of great importance for the comprehensive understanding of amorphization and crystallization processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Chemical state mapping of simulant Chernobyl lava-like fuel containing material using micro-focused synchrotron X-ray spectroscopy

Uranium speciation and redox behaviour is of critical importance in the nuclear fuel cycle. X-ray absorption near-edge spectroscopy (XANES) is commonly used to probe the oxidation state and speciation of uranium, and other elements, at the macroscopic and microscopic scale, within nuclear materials. Two-dimensional (2D) speciation maps, derived from microfocus X-ray fluorescence and XANES data, provide essential information on the spatial variation and gradients of the oxidation state of redox active elements such as uranium. In the present work, we elaborate and evaluate approaches to the construction of 2D speciation maps, in an effort to maximize sensitivity to the U oxidation state at the U L 3 -edge, applied to a suite of synthetic Chernobyl lava specimens. Our analysis shows that calibration of speciation maps can be improved by determination of the normalized X-ray absorption at excitation energies selected to maximize oxidation state contrast. The maps are calibrated to the normalized absorption of U L 3 XANES spectra of relevant reference compounds, modelled using a combination of arctangent and pseudo-Voigt functions (to represent the photoelectric absorption and multiple-scattering contributions). We validate this approach by microfocus X-ray diffraction and XANES analysis of points of interest, which afford average U oxidation states in excellent agreement with those estimated from the chemical state maps. This simple and easy-to-implement approach is general and transferrable, and will assist in the future analysis of real lava-like fuel-containing materials to understand their environmental degradation, which is a source of radioactive dust production within the Chernobyl shelter.

36 MATERIALS SCIENCE↗
NASA NTRS1981

Testing of solar cell covers and encapsulants conducted in a simulated space environment

The materials included in the evaluation were 0211 micro-sheet, FEP-A used as a cover and as an adhesive, DC 93-500 adhesive, PFA "hard coat" used as a cover, GE 615/UV-24 used as a cover, GR 650 used as a cover, and electrostatically bonded 7070 glass. The test environments were 1 MeV electron irradiation interspersed with thermal cycling, 0.5 MeV proton irradiation interspersed with thermal cycling and UV exposure interspersed with thermal cycling. Summary data is given describing the response of the test materials both visually and electrically to the three different environments.

Russell, D. A.↗
NASA NTRS1986

Material damping of simple structures in a simulated space environment

The need for accurate, quantitative knowledge of the vibration dissipation of large space structures is explained. The sources of experimental error in vibrational measurements are detailed. A new method for such testing based on the use of a miniature telemetry system is presented, which allows the testing of structures in a simulated space environment consisting of free-fall inside of a vacuum chamber. Theoretical relations are given for the damping ratios of metals and composites. Measured damping ratios for both aluminum and composite beams and plates, and aluminum planar trusses, are presented. Experimental results are used to evaluate the theoretical damping relations.

Edberg, D. L.↗