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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 595 records · Page 33

All sources NASA NTRS DOE OSTI

DOE OSTI2026

High-throughput computation of electric polarization in solids via Berry flux diagonalization

Electric polarization in the absence of an externally applied electric field is a key property of polar materials, but the standard interpolation-based ab initio approach to compute polarization differences within the modern theory of polarization presents challenges for automated high-throughput calculations. Berry flux diagonalization [J. Bonini et al., Phys. Rev. B 102, 045141 (2020)] has been proposed as an efficient and reliable alternative, though it has yet to be widely deployed. Here, we assess Berry flux diagonalization using ab initio calculations of a large set of materials, introducing and validating heuristics that ensure branch alignment with a minimal number of intermediate interpolated structures. Our automated implementation of Berry flux diagonalization succeeds in cases where prior interpolation-based workflows fail due to band-gap closures or branch ambiguities. Benchmarking with ab initio calculations of 176 candidate ferroelectrics, we demonstrate the efficacy of the approach on a broad range of insulating materials and obtain accurate effective polarization values with fewer interpolated structures than prior automated interpolation-based workflows. Our real-space heuristics that can predict gauge stability a priori from ionic displacements enable a general automated framework for reliable polarization calculations and efficient high-throughput screening of chemically and structurally diverse polar insulators. These results establish Berry flux diagonalization as a robust and efficient method to compute the effective polarization of solids and to accelerate the data-driven discovery of functional polar materials.

Poteshman, Abigail N. [University of Chicago, IL (↗

DOE OSTI2025

Machine learned potential for high-throughput phonon calculations of metal—organic frameworks

Metal–organic frameworks (MOFs) are highly porous and versatile materials studied extensively for applications such as carbon capture and water harvesting. However, computing phonon-mediated properties in MOFs, like thermal expansion and mechanical stability, remains challenging due to the large number of atoms per unit cell, making traditional Density Functional Theory (DFT) methods impractical for high-throughput screening. Recent advances in machine learning potentials have led to foundation atomistic models, such as MACE-MP-0, that accurately predict equilibrium structures but struggle with phonon properties of MOFs. In this work, we developed a workflow for computing phonons in MOFs within the quasi-harmonic approximation with a fine-tuned MACE model, MACE-MP-MOF0. The model was trained on a curated dataset of 127 representative and diverse MOFs. The fine-tuned MACE-MP-MOF0 improves the accuracy of phonon density of states and corrects the imaginary phonon modes of MACE-MP-0, enabling high-throughput phonon calculations with state-of-the-art precision. The model successfully predicts thermal expansion and bulk moduli in agreement with DFT and experimental data for several well-known MOFs. These results highlight the potential of MACE-MP-MOF0 in guiding MOF design for applications in energy storage and thermoelectrics.

Elena, Alin Marin↗

DOE OSTI2021

Catalytic Activity and Water Stability of the MgO(111) Surface for 2-Pentanone Condensation

Nanomaterials derived from earth-abundant metal oxides have gained tremendous interest as catalysts; although, water stability remains a challenge. This study examines MgO(111) surfaces for 2-pentanone condensation and their evolution during D2O hydration. Catalyst screening confirmed the high activity of fresh MgO(111) for 2-pentanone condensation relative to conventionally prepared MgO(100). Computational modeling suggests that the (111) surface is readily hydroxylated, and that surface hydroxyls help stabilize the surface and reduce the barrier for 2-pentanone condensation. Vapor-phase D2O hydration after 3 min increased MgO(111) hydroxyls and retained surface area and activity; however, after 1 h, deuteroxide formation reduced the surface area and activity by >30 %. After 24 h, deuteroxide growth slowed down, and surface area and activity remained stable. This suggests MgO(111)-derived hydroxide may be the dominant surface responsible for 2-pentanone condensation following water exposure. Thermal regeneration of the 24-h sample restored 86 % of the surface area and 94 % of the activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Optimizing accuracy and efficacy in data-driven materials discovery for the solar production of hydrogen

The production of hydrogen fuels, via water splitting, is of practical relevance for meeting global energy needs and mitigating the environmental consequences of fossil-fuel-based transportation. Water photoelectrolysis has been proposed as a viable approach for generating hydrogen, provided that stable and inexpensive photocatalysts with conversion efficiencies over 10% can be discovered, synthesized at scale, and successfully deployed. While a number of first-principles studies have focused on the data-driven discovery of photocatalysts, in the absence of systematic experimental validation, the success rate of these predictions may be limited. We address this problem by developing a screening procedure with co-validation between experiment and theory to expedite the synthesis, characterization, and testing of the computationally predicted, most desirable materials. Here, starting with 70 150 compounds in the Materials Project database, the proposed protocol yielded 71 candidate photocatalysts, 11 of which were synthesized as single-phase materials. Experiments confirmed hydrogen generation and favorable band alignment for 6 of the 11 compounds, with the most promising ones belonging to the families of alkali and alkaline-earth indates and orthoplumbates. This study shows the accuracy of a nonempirical, Hubbard-corrected density-functional theory method to predict band gaps and band offsets at a fraction of the computational cost of hybrid functionals, and outlines an effective strategy to identify photocatalysts for solar hydrogen generation.

08 HYDROGEN↗

DOE OSTI2025

Toward accelerating rare-earth metal extraction using equivariant neural networks

The separation of rare-earth metals, vital for numerous advanced technologies, is hampered by their similar chemical properties, making ligand discovery a significant challenge. Traditional experimental and quantum chemistry approaches for identifying effective ligands are often resource-intensive. We introduce a machine learning protocol based on an equivariant neural network, Allegro, for the rapid and accurate prediction of binding energies in rare-earth complexes. Key to this work is our newly curated dataset of rare-earth metal complexes—made publicly available to foster further research—systematically generated using the Architector program. This dataset distinctively features functionalized derivatives of proven rare-earth-chelating scaffolds, hydroxypyridinone (HOPO), catecholamide (CAM), and their thio-analogues, selected for their established efficacy in binding these elements. Trained on this valuable resource, our Allegro models demonstrate excellent performance, particularly when trained to directly predict DFT-level binding energies, yielding highly accurate results that closely correlate with theoretical calculations on a diverse test set. Furthermore, this strategy exhibited strong out-of-sample generalization, accurately predicting binding energies for an isomeric HOPO-derivative ligand not seen during training. By substantially reducing computational demands, this machine learning framework, alongside the provided dataset, represent powerful tools to accelerate the high-throughput screening and rational design of novel ligands for efficient rare-earth metal separation.

Gupta, Ankur K. [Lawrence Berkeley National Labora↗

DOE OSTI2021

Multimode Metastructures: Novel Hybrid 3D Lattice Topologies

With the rapid proliferation of additive manufacturing and 3D printing technologies, architected cellular solids including truss-like 3D lattice topologies offer the opportunity to program the effective material response through topological design at the mesoscale. The present report summarizes several of the key findings from a 3-year Laboratory Directed Research and Development Program. The program set out to explore novel lattice topologies that can be designed to control, redirect, or dissipate energy from one or multiple insult environments relevant to Sandia missions, including crush, shock/impact, vibration, thermal, etc. In the first 4 sections, we document four novel lattice topologies stemming from this study: coulombic lattices, multi-morphology lattices, interpenetrating lattices, and pore-modified gyroid cellular solids, each with unique properties that had not been achieved by existing cellular/lattice metamaterials. The fifth section explores how unintentional lattice imperfections stemming from the manufacturing process, primarily sur face roughness in the case of laser powder bed fusion, serve to cause stochastic response but that in some cases such as elastic response the stochastic behavior is homogenized through the adoption of lattices. In the sixth section we explore a novel neural network screening process that allows such stocastic variability to be predicted. In the last three sections, we explore considerations of computational design of lattices. Specifically, in section 7 using a novel generative optimization scheme to design novel pareto-optimal lattices for multi-objective environments. In section 8, we use computational design to optimize a metallic lattice structure to absorb impact energy for a 1000 ft/s impact. And in section 9, we develop a modified micromorphic continuum model to solve wave propagation problems in lattices efficiently.

36 MATERIALS SCIENCE↗

NASA NTRS1972

Use of an infrared-imaging camera to obtain convective heating distributions.

The IR emission from the surface of a wind-tunnel model is determined as a function of time with the aid of an infrared-sensitive imaging camera. Prior calibration of the IR camera relates the emission to the surface temperature of the model. The time history of the surface temperature is then related to the heating rate by standard techniques. The output of the camera is recorded in analog form, digitized, and processed by a computer. In addition, real-time visual displays of the IR emissions are obtained as pictures on an oscilloscope screen.

Compton, D. L.↗

NASA NTRS1974

Displays

An experimental investigation made to determine the depth cue of a head movement perspective and image intensity as a function of depth is summarized. The experiment was based on the use of a hybrid computer generated contact analog visual display in which various perceptual depth cues are included on a two dimensional CRT screen. The system's purpose was to impart information, in an integrated and visually compelling fashion, about the vehicle's position and orientation in space. Results show head movement gives a 40% improvement in depth discrimination when the display is between 40 and 100 cm from the subject; intensity variation resulted in as much improvement as head movement.

Source record↗

NASA NTRS1980

Analysis of localized fringes in the holographic optical Schlieren system

The relation between localization of interference fringes in classical and holographic interferometry is reviewed and an application of holographic interferometry is considered for which the object is a transparent medium with nonhomogeneous refractive index. The technique is based on the analysis of the optical path length change of the object wave as it propagates through a transparent medium. Phase shifts due to variations of the speed of light within the medium give rise to an interference pattern. The resulting interferogram can be used to determine the physical properties of the medium or transparent object. Such properties include the mass density of fluids, electron densities of plasmas, the temperature of fluids, the chemical species concentration of fluids, and the state of stress in solids. The optical wave used can be either a simple plane or spherical wave, or it may be a complicated spatial wave scattered by a diffusing screen. The mathematical theory on the formation and analysis of localized fringes, the general theoretical concepts used, and a computer code for analysis are included along with the inversion of fringe order data.

Kurtz, R. L.↗

NASA NTRS1980

Interactive display of molecular models using a microcomputer system

A simple, microcomputer-based, interactive graphics display system has been developed for the presentation of perspective views of wire frame molecular models. The display system is based on a TERAK 8510a graphics computer system with a display unit consisting of microprocessor, television display and keyboard subsystems. The operating system includes a screen editor, file manager, PASCAL and BASIC compilers and command options for linking and executing programs. The graphics program, written in USCD PASCAL, involves the centering of the coordinate system, the transformation of centered model coordinates into homogeneous coordinates, the construction of a viewing transformation matrix to operate on the coordinates, clipping invisible points, perspective transformation and scaling to screen coordinates; commands available include ZOOM, ROTATE, RESET, and CHANGEVIEW. Data file structure was chosen to minimize the amount of disk storage space. Despite the inherent slowness of the system, its low cost and flexibility suggests general applicability.

Egan, J. T.↗

NASA NTRS1988

Sensitivity study of the monogroove with screen heat pipe design

The present sensitivity study of design variable effects on the performance of a monogroove-with-screen heat pipe obtains performance curves for maximum heat-transfer rates vs. operating temperatures by means of a computer code; performance projections for both 1-g and zero-g conditions are obtainable. The variables in question were liquid and vapor channel design, wall groove design, and the number of feed lines in the evaporator and condenser. The effect on performance of three different working fluids, namely ammonia, methanol, and water, were also determined. Greatest sensitivity was to changes in liquid and vapor channel diameters.

Evans, Austin L.↗

NASA NTRS1992

Characterization of ion accelerating systems on NASA LeRC's ion thrusters

An investigation is conducted regarding ion-accelerating systems for two NASA thrusters to study the limits of ion-extraction capability or perveance. A total of nine two-grid ion-accelerating systems are tested with the 30- and 50-cm-diam ring-cusp inert-gas ion thrusters emphasizing the extension of ion-extraction. The vacuum-tank testing is described using xenon, krypton, and argon propellants, and thruster performance is computed with attention given to theoretical design considerations. Reductions in perveance are noted with decreasing accelerator-hole-to-screen-hole diameter ratios. Perveance values vary indirectly with the ratio of discharge voltage to total accelerating voltage, and screen/accelerator electrode hole-pair alignment is also found to contribute to perveance values.

Rawlin, Vincent K.↗

NASA NTRS2006

Processing TES Level-1B Data

TES L1B Subsystem is a computer program that performs several functions for the Tropospheric Emission Spectrometer (TES). The term "L1B" (an abbreviation of "level 1B"), refers to data, specific to the TES, on radiometric calibrated spectral radiances and their corresponding noise equivalent spectral radiances (NESRs), plus ancillary geolocation, quality, and engineering data. The functions performed by TES L1B Subsystem include shear analysis, monitoring of signal levels, detection of ice build-up, and phase correction and radiometric and spectral calibration of TES target data. Also, the program computes NESRs for target spectra, writes scientific TES level-1B data to hierarchical- data-format (HDF) files for public distribution, computes brightness temperatures, and quantifies interpixel signal variability for the purpose of first-order cloud and heterogeneous land screening by the level-2 software summarized in the immediately following article. This program uses an in-house-developed algorithm, called "NUSRT," to correct instrument line-shape factors.

DeBaca, Richard C.↗

DOE OSTI2023

acCRISPR: an activity-correction method for improving the accuracy of CRISPR screens

Abstract High throughput CRISPR screens are revolutionizing the way scientists unravel the genetic underpinnings of engineered and evolved phenotypes. One of the critical challenges in accurately assessing screening outcomes is accounting for the variability in sgRNA cutting efficiency. Poorly active guides targeting genes essential to screening conditions obscure the growth defects that are expected from disrupting them. Here, we develop acCRISPR, an end-to-end pipeline that identifies essential genes in pooled CRISPR screens using sgRNA read counts obtained from next-generation sequencing. acCRISPR uses experimentally determined cutting efficiencies for each guide in the library to provide an activity correction to the screening outcomes via calculation of an optimization metric, thus determining the fitness effect of disrupted genes. CRISPR-Cas9 and -Cas12a screens were carried out in the non-conventional oleaginous yeast Yarrowia lipolytica and acCRISPR was used to determine a high-confidence set of essential genes for growth under glucose, a common carbon source used for the industrial production of oleochemicals. acCRISPR was also used in screens quantifying relative cellular fitness under high salt conditions to identify genes that were related to salt tolerance. Collectively, this work presents an experimental-computational framework for CRISPR-based functional genomics studies that may be expanded to other non-conventional organisms of interest.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

High-throughput design of high-performance lightweight high-entropy alloys

Developing affordable and light high-temperature materials alternative to Ni-base superalloys has significantly increased the efforts in designing advanced ferritic superalloys. However, currently developed ferritic superalloys still exhibit low high-temperature strengths, which limits their usage. Here we use a CALPHAD-based high-throughput computational method to design light, strong, and low-cost high-entropy alloys for elevated-temperature applications. Through the high-throughput screening, precipitation-strengthened lightweight high-entropy alloys are discovered from thousands of initial compositions, which exhibit enhanced strengths compared to other counterparts at room and elevated temperatures. The experimental and theoretical understanding of both successful and failed cases in their strengthening mechanisms and order-disorder transitions further improves the accuracy of the thermodynamic database of the discovered alloy system. This study shows that integrating high-throughput screening, multiscale modeling, and experimental validation proves to be efficient and useful in accelerating the discovery of advanced precipitation-strengthened structural materials tuned by the high-entropy alloy concept.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Studying the Collective Functional Response of a Receptor in Alchemical Ligand Binding Free Energy Simulations with Accelerated Solvation Layer Dynamics

Ligand binding free energy simulations (LB-FES) that involve sampling of protein functional conformations have been longstanding challenges in research on molecular recognition. Particularly, modeling of the conformational transition pathway and design of the heuristic biasing mechanism are severe bottlenecks for the existing enhanced configurational sampling (ECS) methods. Inspired by the key role of hydration in regulating conformational dynamics of macromolecules, this report proposes a novel ECS approach that facilitates binding-associated structural dynamics by accelerated hydration transitions in combination with the lambda-exchange of free energy perturbation (FEP). Further, two challenging protein-ligand binding processes involving large configurational transitions of the receptor are studied, with hydration transitions at binding sites accelerated by Hamiltonian-simulated annealing of the hydration layer. Without the need for pathway analysis or ad hoc barrier flattening potential, LB-FES were performed with FEP/lambda-exchange molecular dynamics simulation at a minor overhead for annealing of the hydration layer. The LB-FES studies showed that the accelerated rehydration significantly enhances the collective conformational transitions of the receptor, and convergence of binding affinity calculations is obtained at a sweet-spot simulation time scale. Alchemical LB-FES with the proposed ECS strategy is free from the effort of trial and error for the setup and realizes efficient on-the-fly sampling for the collective functional response of the receptor and bound water and therefore presents a practical approach to high-throughput screening in drug discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Tailoring Microbial Fitness Through Computational Steering and CRISPRi-Driven Robustness Regulation

The widespread application of genetically modified microorganisms (GMMs) across diverse sectors underscores the pressing need for robust strategies to mitigate the risks associated with their potential uncontrolled escape. This study merges computational modeling with CRISPR interference (CRISPRi) to refine GMM metabolic robustness. Utilizing ensemble modeling, we achieved high-throughput in silico screening for enzymatic targets susceptible to expression alterations. Translating these insights, we developed functional CRISPRi, boosting fitness control via multiplexed gene knockdown. Our method, enhanced by an insulator-improved gRNA structure and an off-switch circuit controlling a compact Cas12m, resulted in rationally engineered strains with escape frequencies below National Institutes of Health standards. The effectiveness of this approach was confirmed under various conditions, showcasing its ability for secure GMM management. This research underscores the resilience of microbial metabolism, strategically modifying key nodes to halt growth without provoking significant resistance, thereby enabling more reliable and precise GMM control. A record of this paper's transparent peer review process is included in the supplemental information.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

High throughput screening of high entropy spinel electrolytes for multivalent batteries

High-entropy (HE) design emerged as a promising path for discovering multivalent superionic conductors. This work provides a computational exploration of the synthesizability of HE spinel-based electrolytes among the typical chemical space. Design principles have been established, while experimental synthesis has supported the stability rules predicted by computational data.

25 ENERGY STORAGE↗