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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 sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Towards exact finite temperature electronic structure in solids and molecules (Final Technical Report)

This report describes the University of Iowa portion of a project that is now continuing at Michigan State University. We are developing novel methods, algorithms, and software to enable simulations of molecules and materials at high temperature. This is a key challenge in chemistry and materials science. By refining an approach called Density Matrix Quantum Monte Carlo (DMQMC), we developed faster and more accurate ways to conduct these simulations. These advances will help us understand how temperature affects the behavior of electrons, chemical bonds, and phase transitions in solids and molecules. These breakthroughs are especially important for applications where light and heat drive chemical reactions, superconductivity, and materials used in energy and sensing. In addition, this project involved the development of the open-source HANDE-QMC software package, supporting the broader community in benchmarking and developing finite-temperature electronic structure methods.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Initial User Study Insights Clarified Community Requirements & Early Feedback on Conceptual Design

The HPDF User Experience (UX) team conducted eight semi-structured interviews with twelve individuals leading data and computing infrastructure work at DOE Office of Science (SC) user facilities or projects. This report presents key takeaways synthesizing community perspectives and needs, along with recommendations for the project. These insights should be considered as conceptual design work continues, early partnerships begin, workflow readiness activities evaluate and enhance key scientific tools, and early access systems are made available to the Office of Science (SC) community. Vigilance in meeting community requirements and ensuring workflow readiness will be needed to ensure HPDF’s success.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1981

Use of ordination and classification procedures to evaluate phytoplankton communities during Superflux II

Cluster analysis and an ordination procedure were performed on two data matrices to investigate real and environmental spatial relationships. Multiple regression analysis was used to relate the measured environmental variables to the phytoplankton community changes. Qualitative type phytoplankton data proved to be less structured in both of these spaces, relative to the biomass data. The salinity gradients of the northern transects covaried significantly with the phytoplankton association changes. In the southern transects the light variable was most important in explaining the variance in the ordination axes. These data suggest the close relationships between phytoplankton community changes and the physical hydrology of the area.

Rutledge, C. K.↗
NASA NTRS1992

Exobiology: The NASA program

The goal of NASA's Exobiology Program is to understand the origin, evolution, and distribution of life in the universe. To do this, the Exobiology Program seeks to provide a critical framework and some key research to allow NASA to bear the combined talents and capabilities of the agency and the scientific community, and the unique opportunities afforded by space exploration. To provide structure and direction to the quest for answers, the Exobiology Program has instituted a comprehensive research program divided into four elements which are being implemented at several of NASA's research centers and in the university community. These program elements correspond to the four major epochs in the evolution of living systems: (1) cosmic evolution of the biogenic compounds; (2) prebiotic evolution; (3) origin and early evolution of life; and (4) evolution of advanced life. The overall research program is designed to trace the pathways leading from the origin of the universe through the major epochs in the story of life.

Rummel, John D.↗
DOE OSTI2026

Contrasting Parametric Sensitivities in Two Global Vegetation Models Using Parameter Perturbation Ensembles

Uncertainty in land model projections remains high and the roles of parametric and structural uncertainty are difficult to disentangle. To compare parametric sensitivity across model structures we present two parameter perturbation ensembles using the Community Land Model (CLM) operating in satellite phenology mode. The ensembles contrast two vegetation modules: (a) the default CLM vegetation module and (b) the Functionally Assembled Terrestrial Ecosystem Simulator (CLM-FATES). We perturbed over 300 parameters and quantified their effects on biophysical fluxes globally and across biomes. Most parameters have minimal impact on biophysical fluxes, with only a few substantially influencing results. While both models exhibit similar parameter sensitivity for some fluxes, CLM-FATES shows larger spread in gross primary productivity (GPP), driven by strong sensitivity to carboxylation rate. CLM-FATES also shows a weaker GPP response to soil hydrology parameters and exhibits higher water use efficiency (WUE). Cross-model comparisons reveal similar sensitivities for some parameters (e.g., leaf dimension) but divergent responses to others (e.g., stomatal intercept), highlighting underlying structural differences. Differences in WUE and sensitivity to hydrology and stomatal conductance parameters underscore how model structure fundamentally alters parametric sensitivity. The data sets generated from these ensembles can be used to identify influential parameters and guide future calibration efforts.

Foster, A. C. [NSF National Center for Atmospheric↗
DOE OSTI2026

metagRoot: a comprehensive database of protein families associated with plant root microbiomes

The plant root microbiome is vital in plant health, nutrient uptake, and environmental resilience. To explore and harness this diversity, we present metagRoot, a specialized and enriched database focused on the protein families of the plant root microbiome. MetagRoot integrates metagenomic, metatranscriptomic, and reference genome-derived protein data to characterize 71 091 enriched protein families, each containing at least 100 sequences. These families are annotated with multiple sequence alignments, CRISPR elements, hidden Markov models, taxonomic and functional classifications, ecosystem and geolocation metadata, and predicted 3D structures using AlphaFold2. MetagRoot is a powerful tool for decoding the molecular landscape of root-associated microbial communities and advancing microbiome-informed agricultural practices by enriching protein family information with ecological and structural context. The database is available at https://pavlopoulos-lab.org/metagroot/ or https://www.metagroot.org.

Chasapi, Maria N↗
NASA NTRS2018

Microphysical Variability of Amazonian Deep Convective Cores Observed by CloudSat and Simulated by a Multi-Scale Modeling Framework

Recently launched cloud observing satellites provide information about the vertical structure of deep convection and its microphysical characteristics. In this study, CloudSat reflectivity data is stratified by cloud type, and the contoured frequency by altitude diagrams reveal a doublearc structure in deep convective cores (DCCs) above 8 km. This suggests two distinct hydrometeor modes (snow versus hail/graupel) controlling variability in reflectivity profiles. The day–night contrast in the double arcs is about four times larger than the wet–dry season contrast. Using QuickBeam, the vertical reflectivity structure of DCCs is analyzed in two versions of the Superparameterized Community Atmospheric Model (SP-CAM) with single-moment (no graupel) and double-moment (with graupel) microphysics. Doublemoment microphysics shows better agreement with observed reflectivity profiles; however, neither model variant captures the double-arc structure. Ultimately, the results show that simulating realistic DCC vertical structure and its variability requires accurate representation of ice microphysics, in particular the hail/graupel modes, though this alone is insufficient.

Dodson, J. Brant↗
DOE OSTI2021

Proceedings of RIKEN BNL Research Center Workshop: Small-x Physics in the EIC Era [Slides]

Understanding the high energy limit of hadronic and nuclear collisions is at the forefront of nuclear and particle physics. When boosted to ultrahigh energies, all hadrons and nuclei eventually transform into a universal form of matter called the Color Glass Condensate (CGC). The CGC is characterized by the high density (saturation) of small-x gluons which leads to distinct experimental signatures. Tantalizing hints of the CGC have been observed at HERA, RHIC and the LHC, but the prospects for the discovery of the CGC are more promising at future experiments such as the Electron-Ion Collider (EIC) at BNL Indeed, according to the National Science Academy report published in 2019, one of the three major goals of the EIC is to address the nature of the gluon saturation. (The other two are the mass and spin structure of the nucleons.) With this in mind, the small-x community is gearing up to meet the challenges of the EIC era. Over the past several years, there has been impressive progress in the next-to-leading order (NLO) calculations in the CGC framework of various observables such as single hadron production in proton-nucleus collisions, inclusive and exclusive dijet and trijet production in Deep Inelastic Scattering (DIS), jet-plus-photon production in DIS, etc. We expect that NLO calculations will be the standard tool to confront future experimental data at the EIC. Another emerging trend of the community is the interplay between small-x physics and spin physics. The RHIC result for the gluon helicity ΔG has underscored the necessity to understand the longitudinal spin structure of the proton at small-x. There have been theoretical indications that a significant fraction of spin and orbital angular momentum is stored in the small-x region. As for the transversely polarized proton, a surprising new connection between the gluon Sivers function at small-x and the QCD Odderon has been pointed out and its implications at the EIC has been discussed. In view of these developments, we think it is timely to organize a dedicated workshop on small-x physics to summarize the present status of the field and to discuss future directions. A major focus of this workshop will be to identify outstanding problems that could significantly benefit from collaborative efforts amongst scientists working on formal, phenomenological, and computational aspects of small-x physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

International network of nuclear structure and decay data evaluators

Compilation, evaluation and dissemination of nuclear data are arduous tasks that rely on contributions from experts in both the basic and applied sciences communities whose efforts are coordinated by the International Atomic Energy Agency (IAEA). The Evaluated Nuclear Structure Data File (ENSDF) includes the most extensive and comprehensive set of nuclear structure and decay data evaluations performed by the international network of Nuclear Structure and Decay Data evaluators (NSDD) under the auspices of the IAEA. In this report we describe the recent NSDD activities supported by the IAEA and provide some future perspectives.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

A modular and extensible CHARMM-compatible model for all-atom simulation of polypeptoids

Peptoids (N-substituted glycines) are a class of sequence-defined synthetic peptidomimetic polymers with applications including drug delivery, catalysis, and biomimicry. Classical molecular simulations have been used to predict and understand the conformational dynamics of single chains and their self-assembly into morphologies including sheets, tubes, spheres, and fibrils. The CGenFF-NTOID model based on the CHARMM General Force Field has demonstrated success in accurate all-atom molecular modeling of peptoid structure and thermodynamics. Extension of this force field to new peptoid side chains has historically required reparameterization of side chain bonded interactions against ab initio data. This fitting protocol improves the accuracy of the force field but is also burdensome and precludes modular extensibility of the model to arbitrary peptoid sequences. In this work, we develop and demonstrate a Modular Side Chain CGenFF-NTOID (MoSiC-CGenFF-NTOID) as an extension of CGenFF-NTOID employing a modular decomposition of the peptoid backbone and side chain parameterizations, wherein arbitrary side chains within the large family of substituted methyl groups (i.e., –CH 3 , –CH 2 R, –CHRR', and –CRR'R") are directly ported from CGenFF. We validate this approach against ab initio calculations and experimental data to develop a MoSiC-CGenFF-NTOID model for all 20 natural amino acid side chains along with 13 commonly used synthetic side chains and present an extensible paradigm to efficiently determine whether a novel side chain can be directly incorporated into the model or whether refitting of the CGenFF parameters is warranted. We make the model freely available to the community along with a tool to perform automated initial structure generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Xarray Climate Data Analysis Tools

xCDAT is an extension of xarray for climate data analysis on structured grids. It serves as a modern successor to the Community Data Analysis Tools (CDAT) library. Xarray is an "open source project and Python package that introduces labels in the form of dimensions, coordinates, and attributes on top of raw NumPy-like arrays, which allows for more intuitive, more concise, and less error-prone user experience. Xarray includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures" (source: https://xarray.dev/). The goal of xCDAT is to provide generalizable features and utilities for simple and robust analysis of climate data. xCDAT's design philosophy is focused on reducing the overhead required to accomplish certain tasks in xarray. Some key xCDAT features are inspired by or ported from the core CDAT library, while others leverage powerful libraries in the xarray ecosystem (e.g., xESMF and cf_xarray) to deliver robust APIs.

Vo, Tom↗
DOE OSTI2023

The direct and indirect drivers shaping RNA viral communities in grassland soil

Recent studies have revealed diverse RNA viral communities in soils. Yet, how environmental factors influence soil RNA viruses remains largely unknown. Here, we recovered RNA viral communities from 24 metatranscriptomes sequenced from grassland soils managed under a range of environmental conditions including 1) water content: 100% and 25% water holding capacity, 2) plant presence: planted with tall wheatgrass (Thinopyrum ponticum) and bare soil, 3) cultivar type: Alkar and Jose, and 4) soil depth: 0-5 cm and 15-25 cm. The recovered RNA viral communities were novel with nearly one-third of the RNA viral contigs uniquely detected in the studied grassland. The classified RNA viral contigs are mostly known as eukaryotic RNA viruses (74.7%) belonging to Phyla Duplornaviricota, Kitrinoviricota, Lenarviricota, and Pisuviricota. Eukaryotic RNA viruses of Family Mitoviridae as well as their natural hosts, Fungi, are one of the most dominant taxa. Consistent with the results of nonmetric multidimensional scaling analysis, the four environmental conditions (water content, plant presence, cultivar, and soil depth) significantly influence the assemblages of soil RNA viral communities as suggested by the correlation analysis and the random forest algorithm. The modularity analysis of the factor network and the structural equation modeling further support the hierarchical associations among the four environmental factors and the community factors representing the co-existing eukaryotic, prokaryotic, and RNA viral communities. The soil water content, plant presence, and type of cultivar demonstrate a significant positive impact on eukaryotic RNA viral richness directly as well as indirectly on eukaryotic RNA viral abundance via influencing the co-existing eukaryotic members in this soil. Our data also provide statistical support for the negative influence of soil depth on soil eukaryotic richness and abundances resulting in its indirect impact on soil eukaryotic RNA viral communities. This study provides field-relevant information on how environmental and community factors collectively shape soil RNA communities and contribute to ecological understanding of RNA viral survival under various environmental conditions and virus-host interactions in soil.

Wu, Ruonan↗
NASA NTRS2012

An Efficient and Versatile Means for Assembling and Manufacturing Systems in Space

Within NASA Space Science, Exploration and the Office of Chief Technologist, there are Grand Challenges and advanced future exploration, science and commercial mission applications that could benefit significantly from large-span and large-area structural systems. Of particular and persistent interest to the Space Science community is the desire for large (in the 10- 50 meter range for main aperture diameter) space telescopes that would revolutionize space astronomy. Achieving these systems will likely require on-orbit assembly, but previous approaches for assembling large-scale telescope truss structures and systems in space have been perceived as very costly because they require high precision and custom components. These components rely on a large number of mechanical connections and supporting infrastructure that are unique to each application. In this paper, a new assembly paradigm that mitigates these concerns is proposed and described. A new assembly approach, developed to implement the paradigm, is developed incorporating: Intelligent Precision Jigging Robots, Electron-Beam welding, robotic handling/manipulation, operations assembly sequence and path planning, and low precision weldable structural elements. Key advantages of the new assembly paradigm, as well as concept descriptions and ongoing research and technology development efforts for each of the major elements are summarized.

Dorsey, John T.↗
DOE OSTI2020

The Center for Integrated Nanotechnologies (CINT)

The Center for Integrated Nanotechnologies (CINT) offers world-leading scientific expertise and specialized capabilities to create, characterize, and integrate nanostructured materials at a range of length scales, from nano- to meso-scale. CINT helps scientists perform cutting-edge research in the areas of nanoscience and nanotechnology, providing FREE ACCESS for nonproprietary research. CINT facilities are open to the international research community, including government, academic, and industry researchers. One of CINT's core research areas is in-situ S/TEM experiments. Early capabilities focused on electrical and electrochemical property measurements of materials during high-resolution imaging. More recently, the staff has expanded the available techniques to include gaseous environments (ETEM), liquid-cell, mechanics, ion irradiation, laser ablation, cryogenic, heating, and air-free transfer. In-situ investigations have focused on coupled structure-property measurements on real materials, with the CINT user community expanding many of the in-situ method developments.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Machine learning bridges local static structure with multiple properties in metallic glasses

A long-standing challenge in the metallic glass (MG) community has been how to quantitatively gauge the influence of the intricate local packing environment on the response (such as the propensity for atomic rearrangement) of the atomic configuration to external stimuli. Here we establish this structure–property relation by representing the complex amorphous structure using a single, flexibility-orientated structural quantity. This structural flexibility (SF) couples to a bona fide structural representation, the pair distribution function (PDF) of individual atoms, through a weighting function that reflects what matters in the static atomic configuration to dynamic responses. Machine learning is used, employing microscopic flexibility volume as the supervisory signal, to establish via direct regression an optimized weighting vector, which is proven robust for all quenching rates, deformation conditions, and different compositions in a given (e.g., Cu x Zr 100-x ) alloy system. Additionally, the SF is evaluated solely from the particle positions (PDF), for any structure variation, from the atomic scale up to sample average. Strong correlations are demonstrated between SF and a broad range of properties, including vibrational, diffusional, as well as elastic and plastic relaxation responses.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Roadmap on methods and software for electronic structure based simulations in chemistry and materials

This Roadmap article provides a succinct, comprehensive overview of the state of electronic structure methods and software for molecular and materials simulations. Seventeen distinct sections collect insights by 51 leading scientists in the field. Each contribution addresses the status of a particular area, as well as current challenges and anticipated future advances, with a particular eye towards software related aspects and providing key references for further reading. Foundational sections cover density functional theory and its implementation in real-world simulation frameworks, Green's function based many-body perturbation theory, wave-function based and stochastic electronic structure approaches, relativistic effects and semiempirical electronic structure theory approaches. Subsequent sections cover nuclear quantum effects, real-time propagation of the electronic structure, challenges for computational spectroscopy simulations, and exploration of complex potential energy surfaces. The final sections summarize practical aspects, including computational workflows for complex simulation tasks, the impact of current and future high-performance computing architectures, software engineering practices, education and training to maintain and broaden the community, as well as the status of and needs for electronic structure based modeling from the vantage point of industry environments. Overall, the field of electronic structure software and method development continues to unlock immense opportunities for future scientific discovery, based on the growing ability of computations to reveal complex phenomena, processes and properties that are determined by the make-up of matter at the atomic scale, with high precision.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Engineering evaluation of the EQSIM simulated ground-motion database: The San Francisco Bay Area region

Ground-motion simulations for infrequent earthquake scenarios are gaining increasing interest in the engineering community for their potential to inform performance-based structural design and assessment, particularly in regions where major earthquakes are expected, but recordings from consistent historical events are not available. However, the absence of empirical data makes the evaluation of such scenarios and the interpretation of the simulation results very challenging. In this context, this paper presents the evaluation of the first EQSIM (v.1.1.0) ground-motion simulations generated for the San Francisco Bay Area (SFBA) region. The current database, which is at the first stages of development, includes eight realizations of a Hayward Fault M w 7 event. The evaluation of the simulated motions is first conducted on the average ground-motion amplitudes through comparison against the NGA-W2 GMPEs and a selected population of real records. A methodology for selecting a population of real records consistent with the simulated event is proposed. The objective of the proposed evaluation is twofold: (1) build confidence in the realistic character of the simulated motions for their use in engineering applications and (2) offer a critical physics-based interpretation of the simulation results that can help improve key features of the simulation models. To further investigate the implications of using the simulated ground motions for site-specific structural assessments, the ASCE7-16 approach is employed for the analysis of two hazard-consistent near-field sites in the SFBA. Results are discussed. Furthermore, this study offers a critical review of the EQSIM (v.1.1.0) SFBA ground-motion simulations and suggestions for improving the earthquake rupture models.

58 GEOSCIENCES↗
DOE OSTI2022

How to Get the Best Gas Separation Membranes from State-of-the-Art Glassy Polymers

Herein we focus on fundamental polymer science factors in membrane-based gas separation to open another chapter on this important topic. Realistically thinking about nano and angstrom scale matrix attributes that are translatable into higher performance thin glassy polymer asymmetric membrane layers in practical large-scale devices is crucial. Such thinking should be guided by expertise in both polymer and membrane communities to advance the state of the art. Polymer structures, membrane morphologies and effects of operating conditions are discussed here, using specific examples to illustrate key issues. Rubbery polymers are not the focus of this discussion, since they lack diffusive discrimination for size-similar penetrants, which glassy polymers provide and make them the focus here. Four scalable subtopics guide necessary thinking: (i) plasticization; (ii) anti-plasticization†2; (iii) dual-mode transport involving saturation of unrelaxed free volume, and (iv) non-uniform free volume and stress profiles in thin skin glassy polymer asymmetric or composite membranes. Furthermore, using these subtopics in the context of macromolecular science we discuss issues needed to expand the state-of-the-art in gas separation membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗