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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The MolSSI QCArchive project: An open-source platform to compute, organize, and share quantum chemistry data

The Molecular Sciences Software Institute's (MolSSI) Quantum Chemistry Archive (QCArchive) project is an umbrella name that covers both a central server hosted by MolSSI for community data and the Python-based software infrastructure that powers automated computation and storage of quantum chemistry (QC) results. The MolSSI-hosted central server provides the computational molecular sciences community a location to freely access tens of millions of QC computations for machine learning, methodology assessment, force-field fitting, and more through a Python interface. Facile, user-friendly mining of the centrally archived quantum chemical data also can be achieved through web applications found at the website. The software infrastructure can be used as a standalone platform to compute, structure, and distribute hundreds of millions of QC computations for individuals or groups of researchers at any scale. The QCArchiveInfrastructure is open-source (BSD-3C), code repositories can be found at github, and releases can be downloaded via PyPI and Conda. This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods Software > Quantum Chemistry Data Science > Computer Algorithms and Programming

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Genesis Data Card Schema, Template and Supporting Tools

Genesis Data Cards provide a standardized template and schema for documenting scientific datasets in support of discovery, access, interoperability, reusability, governed use, and AI usability. This release of the Genesis Data Card repository includes a versioned Markdown template, a LinkML schema with generated Pydantic and JSON artifacts, schema documentation, and example completed data cards. Validation tooling is provided to ensure that completed data cards conform to the schema prior to submission. Accompanying documentation for the structured metadata is provided as a Field Reference Guide. The schema and accompanying template provided in this repository address the call for actionable context that enables humans and AI systems to find, access, interpret, cite, and reuse data, and, when appropriate, integrate it into AI and machine learning workflows. The data card is intended to serve as a common metadata artifact intended to support standardized, cross-program dataset documentation across Department of Energy (DOE)-aligned efforts, including but not limited to Genesis Mission-related implementations, the Office of Science, National Nuclear Security Administration (NNSA), and Advanced Simulation and Computing (ASC) data governance and stewardship initiatives.

data card↗
DOE OSTI2022

Replication Data for: Decoding reactive structures in dilute alloy catalysts

The data underlying this published work have been made publicly available in this repository as part of the IMASC Data Management Plan. This work was supported as part of the Integrated Mesoscale Architectures for Sustainable Catalysis (IMASC), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award # DE-SC0012573.

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

A baseline structure inventory with critical attribution for the US and its territories

Leveraging high performance computing, remote sensing, geographic data science, machine learning, and computer vision, Oak Ridge National Laboratory has partnered with Federal Emergency Management Agency (FEMA) to build a baseline structure inventory covering the US and its territories to support disaster preparedness, response, and recovery. The dataset contains more than 125 million structures with critical attribution, and is ready to be used by federal agencies, local government and first responders to accelerate on-the-ground response to disasters, further identify vulnerable areas, and develop strategies to enhance the resilience of critical structures and communities. Data can be freely and openly accessed through Figshare data repository, ESRI’s Living Atlas or FEMA’s Geodata platform.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

NP-MRD: the Natural Products Magnetic Resonance Database

The Natural Products Magnetic Resonance Database (NP-MRD) is a comprehensive, freely available electronic resource for the deposition, distribution, searching and retrieval of nuclear magnetic resonance (NMR) data on natural products, metabolites and other biologically derived chemicals. NMR spectroscopy has long been viewed as the ‘gold standard’ for the structure determination of novel natural products and novel metabolites. NMR is also widely used in natural product dereplication and the characterization of biofluid mixtures (metabolomics). All of these NMR applications require large collections of high quality, well-annotated, referential NMR spectra of pure compounds. Unfortunately, referential NMR spectral collections for natural products are quite limited. It is because of the critical need for dedicated, open access natural product NMR resources that the NP-MRD was funded by the National Institute of Health (NIH). Since its launch in 2020, the NP-MRD has grown quickly to become the world's largest repository for NMR data on natural products and other biological substances. It currently contains both structural and NMR data for nearly 41,000 natural product compounds from >7400 different living species. All structural, spectroscopic and descriptive data in the NP-MRD is interactively viewable, searchable and fully downloadable in multiple formats. Extensive hyperlinks to other databases of relevance are also provided. The NP-MRD also supports community deposition of NMR assignments and NMR spectra (1D and 2D) of natural products and related meta-data. The deposition system performs extensive data enrichment, automated data format conversion and spectral/assignment evaluation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Hydration structure and energetics of iron-exchanged montmorillonite

The interaction between iron released from corroded steel canisters and bentonite is a key process influencing the long-term performance of nuclear waste repositories. In particular, the migration of Fe²⁺ into montmorillonite (Mnt) interlayers may alter its hydration, swelling, and ion-transport properties. In the present study, molecular dynamics simulations were performed to investigate the hydration behavior, structural response, and transport properties of Fe-exchanged montmorillonite (Fe-Mnt) under varying hydration states. The simulations focus on short- to intermediate-time-scale Fe 2+ and Fe 3+ interlayer exchange and hydration effects, and do not consider long-term structural substitution, Fe-bearing clay phase stabilization, or secondary iron mineral precipitation. Systems containing Na + -, Fe 2+ -, and Fe 3+ -Mnt were examined using both periodic and edge-exposed configurations to evaluate interlayer structure, ion exchange, and free energy of Fe intercalation. The results show that Fe ions influence the interlayer spacing primarily at low water contents (<1 bilayer), where Fe-Mnt exhibits a d-spacing 1–2 Å larger than Na-Mnt due to stronger hydration. The calculated hydration energies follow the order Fe 2+ $<$Fe 3+ $<$Na + . Both water and ion diffusion coefficients decrease upon Fe ion intercalation, with Fe 2+ ions diffusing an order of magnitude more slowly than those of Na + . Free energy profiles further confirm that Fe 2+ and Fe 3+ ions are thermodynamically favored in the interlayer, with Fe 3+ being the most stable. In conclusion, these findings provide molecular-scale insights into the mechanisms of Fe–Na exchange and their implications for bentonite alteration in repository environments.

clay↗
DOE OSTI2021

Potential structures - Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

This submission contains shapefiles, geotiffs, and symbology for the revised-from-Play-Fairway potential structures/structural settings used in the Nevada Geothermal Machine Learning project. Layers include potential structural setting ellipses, centroids, and distance-to-centroid raster. A submission linking the full GitHub repository for our machine learning Jupyter Notebooks will appear in the related datasets section of this page once available.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Atomistic Simulation of Glasses and Amorphous Materials: Challenges and Opportunities for the Next Decade

Atomistic simulations have become indispensable tools for understanding glass structure, dynamics, and properties, yet persistent challenges limit their predictive power. This perspective examines three interconnected issues, namely glass formation procedures, interatomic potential development, and machine learning applications, which emerged from the 5th International Workshop on Challenges of Atomistic Simulations of Glasses and Amorphous Materials. We identify convergent community priorities for (i) standardized validation protocols, (ii) curated benchmark datasets with complete metadata, and (iii) open repositories for glasses. A systematic was forward is provided by a hierarchical validation framework for assessing the structural fidelity, property prediction, and behavioral realism of simulation techniques. Looking ahead, transformative advances are promised by the fusion of classical techniques with machine learning based approaches, for instance, by integrating swap Monte Carlo with machine-learning (ML) potentials, leveraging foundation models through transfer learning, and finetuning ML potentials with experimental data. Progress depends on the community committing to validated models, reproducible protocols, and sustained data sharing.

Krishnan, N. M. Anoop↗
DOE OSTI2021

Numerical study of the chemo-mechanical behavior of FEBEX bentonite in nuclear waste disposal based on the Barcelona expansive model

Experimental studies show that compacted bentonite used as a backfill material for nuclear waste repository experiences strong coupling between chemical and mechanical processes. Here, we use a dual-structure expansive soil model, referred to as the Barcelona Expansive Model (BExM), to predict the behavior of bentonite buffer in subsurface emplacement tunnels for high-level radioactive waste. After emplacement, the bentonite is subjected to complex and coupled Thermal-Hydraulic-Mechanical-Chemical (THMC) processes. The BExM constitutive model is implemented in a multi-phase reactive transport and geomechanics simulator, TOUGHREACT-FLAC3D, and the model is verified with one benchmark test on FEBEX bentonite. We utilize a one-way Chemo-Mechanical (C-M) coupling approach, in which chemical changes affect the mechanical behavior of bentonite through the BExM linked with the evolution of mass fraction of smectite, exchangeable cation concentration, and ionic strength via osmotic suction. The parameters of the new coupled model for FEBEX bentonite are calibrated against a series of laboratory experiments with various salinity solutions. Finally, coupled THMC modeling is conducted for a generic argillite repository with bentonite buffer under high temperature, focusing on the long-term chemical change and its effect on the mechanical process.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Draft Experimental Plan for Commercial SNF Degradation in Repository Environments with a Focus on Fracture Matrix Degradation

This report documents work performed supporting US Department of Energy (DOE) Nuclear Energy Spent Fuel and Waste Disposition, Spent Fuel and Waste Science and Technology, under work breakdown structure element 1.08.01.03.04, “Inventory and Waste Form Characteristics and Performance.” In particular, this report fulfills the M3 milestone, M3SF-21OR010309072 "Draft Experimental Plan for Commercial SNF Degradation in Repository Environments” as described in work package SF-21OR01030907 "SNF Degradation Testing-ORNL".This experimental plan is a collaboration between ORNL, SNL, ANL, and PNNL. It is intended to support source term model development and spent fuel degradation testing in a range of generic repository conditions. Potential testing and experiments to support validation of the Fuel Matrix Dissolution Model (FMDM) and the overall development/validation of repository source term modeling are discussed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Physical characterization of fault rocks within the Opalinus Clay formation

Near-surface disposal of radioactive waste in shales is a promising option to safeguard the population and environment. However, natural faults intersecting these geological formations can potentially affect the long-term isolation of the repositories. This paper characterizes the physical properties and mineralogy of the internal fault core structure intersecting the Opalinus Clay formation, a host rock under investigation for nuclear waste storage at the Mont Terri Laboratory (Switzerland). We have performed porosity, density, microstructural and mineralogical measurements in different sections of the fault, including intact clays, scaly clays and fault gouge. Mercury intrusion porosimetry analysis reveal a gouge that has a pore network dominated by nanopores of less than 10 nm, yet a high-porosity (21%) and low grain density (2.62 g/cm 3 ) when compared to the intact rock (14.2%, and 2.69 g/cm 3 ). Thus, a more permeable internal fault core structure with respect to the surrounding rock is deduced. Further, we describe the OPA fault gouge as a discrete fault structure having the potential to act as a preferential, yet narrow, and localized channel for fluid-flow if compared to the surrounding rock. Since the fault gouge is limited to a millimetres-thick structure, we expect the barrier property of the geological formation is almost not affected.

58 GEOSCIENCES↗
DOE OSTI2022

Replication Data for: Dynamical Change of Valence States and Structure in NiCu 3 Nanoparticles during Redox Cycling

The data underlying this published work have been made publicly available in this repository as part of the IMASC Data Management Plan. This work was supported as part of the Integrated Mesoscale Architectures for Sustainable Catalysis (IMASC), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award # DE-SC0012573.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

RCSB Protein Data Bank tools for 3D structure-guided cancer research: human papillomavirus (HPV) case study

Abstract Atomic-level three-dimensional (3D) structure data for biological macromolecules often prove critical to dissecting and understanding the precise mechanisms of action of cancer-related proteins and their diverse roles in oncogenic transformation, proliferation, and metastasis. They are also used extensively to identify potentially druggable targets and facilitate discovery and development of both small-molecule and biologic drugs that are today benefiting individuals diagnosed with cancer around the world. 3D structures of biomolecules (including proteins, DNA, RNA, and their complexes with one another, drugs, and other small molecules) are freely distributed by the open-access Protein Data Bank (PDB). This global data repository is used by millions of scientists and educators working in the areas of drug discovery, vaccine design, and biomedical and biotechnology research. The US Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) provides an integrated portal to the PDB archive that streamlines access for millions of worldwide PDB data consumers worldwide. Herein, we review online resources made available free of charge by the RCSB PDB to basic and applied researchers, healthcare providers, educators and their students, patients and their families, and the curious public. We exemplify the value of understanding cancer-related proteins in 3D with a case study focused on human papillomavirus.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Electronic Structure and Mechanical Properties of Solvated Montmorillonite Clay Using Large-Scale DFT Method

Montmorillonite clay (MMT) has been widely used in engineering and environmental applications as a landfill barrier and toxic waste repository due to its unique property as an expandable clay mineral that can absorb water easily. This absorption process rendered MMT to be highly exothermic due to electrostatic interactions among molecules and hydrogen bonds between surface atoms. A detailed study of a large supercell model of structural clay enables us to predict long-term nuclear waste storage. Herein, a large solvent MMT model with 4071 atoms is studied using ab initio density functional theory. The DFT calculation and analysis clarify the important issues, such as bond strength, solvation effect, elasticity, and seismic wave velocities. These results are compared to our previous study on crystalline MMT (dry). The solvated MMT has reduced shear modulus (G), bulk modulus (K), and Young’s modulus (E). We observe that the conduction band (CB) in the density of states (DOS) of solvated MMT model has a single, conspicuous peak at –8.5 eV. Moreover, the atom-resolved partial density of states (PDOS) summarizes the roles played by each atom in the DOS. These findings illuminate numerous potential sophisticated applications of MMT clay.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Replication Data for: Atomic-Scale Surface Structure and CO Tolerance of NiCu Single-Atom Alloys

The data underlying this published work have been made publicly available in this repository as part of the IMASC Data Management Plan. This work was supported as part of the Integrated Mesoscale Architectures for Sustainable Catalysis (IMASC), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award # DE-SC0012573.

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

Shrinkage-induced deformations and creep of structural concrete: 1-year measurements and numerical prediction

Highlights: • Extensive experimental study on drying shrinkage, creep and microcracking of concrete • All specimens prepared from a single batch of ordinary-strength structural concrete • 1st year of measurements of (not only) non-uniformly drying beams with span up to 3-m • The database is downloadable from free-to-use research data repository • Modified MPS model for concrete creep used in blind prediction of all experiments The material models for creep and shrinkage operating on the material point level in FEM are usually intended for challenging complex applications and structures, where the average cross-sectional approach does not suffice. The identification of the growing number of material parameters induced by increasing model capabilities relies on very specific and narrow-oriented yet interconnected experiments which are scarce. The presented comprehensive experiments aim to provide a clearer image of the complicated interaction among the basic phenomena: drying, shrinkage, creep, and microcracking. The cornerstone of this ongoing research is a unique set of 30 partially-sealed unreinforced concrete beams with span 1.75–3.0 m subjected to drying. To minimize material variation, all specimens in this study were cast from a single batch of ordinary strength structural concrete with slag-blended binder. The resulting experimental database will be suitable both for validation and development of the constitutive models.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Closing the Gap between FAIR Data Repositories and Hierarchical Data Formats

Many in the scientific community, particularly in publicly funded research, are pushing to adhere to more accessible data standards to maximize the findability, accessibility, interoperability, and reusability (FAIR) of scientific data, especially with the growing prevalence of machine learning augmented research. Online FAIR data repositories, such as the Open Science Framework (OSF), help facilitate the adoption of these standards by providing frameworks for storage, access, search, APIs, and other features that create organized hubs of scientific data. However, the wider acceptance of such repositories is hindered by the lack of support of hierarchical data formats, such as Technical Data Management Streaming (TDMS) and Hierarchical Data Format 5 (HDF5), that many researchers rely on to organize their datasets. Various tools and strategies should be used to allow hierarchical data formats, FAIR data repositories, and scientific organizations to work more seamlessly together. A pilot project at Los Alamos National Laboratory (LANL) addresses the disconnect between them by integrating the OSF FAIR data repository with hierarchical data renderers, extending support for additional file types in their framework. The multifaceted interactive renderer displays a tree of metadata alongside a table and plot of the data channels in the file. This allows users to quickly and efficiently load large and complex data files directly in the OSF webapp. Users who are browsing files can quickly and intuitively see the files in the way they or their colleagues structured the hierarchical form and immediately grasp their contents. This solution helps bridge the gap between hierarchical data storage techniques and FAIR data repositories, making both of them more viable options for scientific institutions like LANL which have been put off by the lack of integration between them.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Replication Data for: Evolution of Metastable Structures at Bimetallic Surfaces from Microscopy and Machine-Learning Molecular Dynamics

The data underlying this published work have been made publicly available in this repository as part of the IMASC Data Management Plan. This work was supported as part of the Integrated Mesoscale Architectures for Sustainable Catalysis (IMASC), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award # DE-SC0012573.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗