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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

PDBx/mmCIF Ecosystem: Foundational Semantic Tools for Structural Biology

PDBx/mmCIF, Protein Data Bank Exchange (PDBx) macromolecular Crystallographic Information Framework (mmCIF), has become the data standard for structural biology. With its early roots in the domain of small-molecule crystallography, PDBx/mmCIF provides an extensible data representation that is used for deposition, archiving, remediation, and public dissemination of experimentally determined three-dimensional (3D) structures of biological macromolecules by the Worldwide Protein Data Bank (wwPDB, wwpdb.org). Extensions of PDBx/mmCIF are similarly used for computed structure models by ModelArchive (modelarchive.org), integrative/hybrid structures by PDB-Dev (pdb-dev.wwpdb.org), small angle scattering data by Small Angle Scattering Biological Data Bank SASBDB (sasbdb.org), and for models computed generated with the AlphaFold 2.0 deep learning software suite (alphafold.ebi.ac.uk). Community-driven development of PDBx/mmCIF spans three decades, involving contributions from researchers, software and methods developers in structural sciences, data repository providers, scientific publishers, and professional societies. Having a semantically rich and extensible data framework for representing a wide range of structural biology experimental and computational results, combined with expertly curated 3D biostructure data sets in public repositories, accelerates the pace of scientific discovery. Herein, we describe the architecture of the PDBx/mmCIF data standard, tools used to maintain representations of the data standard, governance, and processes by which data content standards are extended, plus community tools/software libraries available for processing and checking the integrity of PDBx/mmCIF data. Use cases exemplify how the members of the Worldwide Protein Data Bank have used PDBx/mmCIF as the foundation for its pipeline for delivering Findable, Accessible, Interoperable, and Reusable (FAIR) data to many millions of users worldwide.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Cold crucible induction melter studies for making glass ceramic waste forms: A feasibility assessment

Glass ceramics are being developed to immobilize fission products, separated from used nuclear fuel by aqueous reprocessing, into a stable waste form suitable for disposal in a geological repository. This work documents the glass ceramic formulation at bench scale and for a scaled melter test performed in a pilot-scale (approximately 1/4 scale) cold crucible induction melter (CCIM). Melt viscosity, electrical conductivity, and crystallization behavior upon cooling were measured on a small set of compositions to select a formulation for melter testing. Property measurements also identified a temperature range for melter operation and cooling profiles necessary to crystallize the targeted phases in the waste form. Bench scale and melter run results successfully demonstrate the processability of the glass ceramic using the CCIM melter technology.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

The Use of Positrons to Survey Alteration Layers on Synthetic Nuclear Waste Glasses

In order to safeguard society and the environment, understanding radioactive waste glass alteration mechanisms in interactions with solutions and near-field materials, such as Fe, is essential to nuclear waste repository performance assessments. Alteration products are formed at the surface of glasses after reaction with solution. In this study, glass altered in the presence of Fe0 in aqueous solution formed two alteration layers: one embedded with Fe closer to the surface and one without Fe found deeper in the sample. Both layers were found to be thinner than the alteration layer found in glass altered in aqueous solution only. For the first time, Doppler Broadening Positron Annihilation Spectroscopy (DB-PAS) is used to non-destructively characterize the pore structures of glass altered in the presence of Fe0. Advantages and disadvantages of DB-PAS compared to other techniques used to analyze pore structures for altered glass samples are discussed. Ultimately, DB-PAS has shown to be an excellent choice for pore structure characterization for glasses with multiple alteration layers. Monte Carlo modeling predicted positron trajectories through the layers, and helped explain DB-PAS data, which showed that the deeper alteration layer without Fe had a similar composition and pore structure to layers on glass altered in water only.

Doppler Broadening Positron Annihilation Spectrosc↗
DOE OSTI2019

Approaches to multi-scale analyses of mechanically and thermally-driven migration of fluid inclusions in salt rocks

Fluid inclusions are found within mineral crystals or along grain boundaries in many sedimentary rocks, notably in evaporite formations, and can migrate along a thermal or hydro-mechanical gradient. Shale and salt rocks have been considered potential host rocks for radioactive waste disposal, due to their low permeability. Previously stagnant inclusions may become mobilised by a perturbation of the in situ state by a geotechnical installation or the emplacement of heat-generating waste. Here, the migration of fluid inclusions can thus have important impacts on the long-term performance of a geologic repository for high-level radioactive waste disposal. As a part of the international research project DECOVALEX-2019, two aspects of fluid inclusion migration in rock salt are currently investigated under different boundary conditions: a) altered hydro-mechanical conditions as a consequence of tunnel excavation or borehole drilling and b) coupled thermo-hydro-mechanical-chemical conditions during the heating period of the post-closure phase of a repository.

58 GEOSCIENCES↗
DOE OSTI2019

Radionuclide transport in brackish water through chalk fractures

Mobility of radionuclides originating from geological repositories in the subsurface has been shown to be facilitated by clay colloids. In brackish water, however, colloids may flocculate and act to immobilize radionuclides associated with them. Furthermore, little research has been conducted on radionuclide interactions with carbonate rocks. In this work, the impact of bentonite colloid presence on the transport of a cocktail of U(VI), Cs, Ce and Re through fractured chalk was investigated. Flow-through experiments were conducted with and without bentonite colloids, present as a mixture of bentonite and Ni-altered montmorillonite colloids. Ce was used as an analogue for reactive actinides in the (III) and (VI) redox states, and Re was considered an analogue for Tc. Filtered brackish groundwater (ionic strength = 170 mM) pumped from a fractured chalk aquitard in the northern Negev Desert of Israel, was used as a solution matrix. Rhenium transport was identical to that of the conservative tracer, uranine. The sorption coefficient (K d ) of U(VI), Cs and Re, calculated from batch experiments with crushed chalk, proved to be a good predictor of mass recovery in transport experiments conducted without bentonite colloids. A meaningful K d value for Ce could not be calculated due to its precipitation as a Ce-carbonate colloids. Transport of both U(VI) and Cs was indifferent to the presence of bentonite colloids. However, the addition of bentonite in the injection solution effectively immobilized Ce, decreasing its recovery from 17-41% to 0.8–1.4%. This indicates that radionuclides which interact with clay colloids that undergo flocculation and deposition may effectively be immobilized in brackish aquifers. Lastly, the results of this study have implications for the prediction of potential mobility of radionuclides in safety assessments for future geological repositories to be located in fractured carbonate rocks in general and in brackish groundwater in particular.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Recent Advances in Corrosion Science Applicable To Disposal of High-Level Nuclear Waste

High level radioactive waste is accumulating at temporary storage locations around the world and will eventually be placed in deep geological repositories. Many different types of geological formation are under consideration, but all will eventually allow water to contact the metallic waste containers considering that the period of performance required to allow sufficient decay of dangerous radionuclides is on the order of 105 – 106 years. Corrosion of the containers and waste forms in the aqueous repository environment is therefore a concern. This review describes the recent advances of the field of materials corrosion based on the work of the Center for Performance and Design of Nuclear Waste Forms and Containers (WastePD) to address the issues associated with the long-term performance assessment and the design of materials with improved performance, where performance is defined as resistance to aqueous corrosion. Glass, crystalline ceramics, and metals are discussed separately, and then the near field interactions of these different materials classes are addressed. Recommendations for future directions are provided.

Frankel, Gerald↗
DOE OSTI2020

A Quantum-Based Approach to Predict Primary Radiation Damage in Polymeric Networks

Initial atomistic-level radiation damage in chemically reactive materials is thought to induce reaction cascades that can result in undesirable degradation of macroscale properties. Ensembles of quantum-based molecular dynamics (QMD) simulations can accurately predict these cascades, but extracting chemical insights from the many underlying trajectories is a labor-intensive process that can require substantial a priori intuition. We develop here a general and automated graph-based approach to extract all chemically distinct structures sampled in QMD simulations and apply our approach to predict primary radiation damage of polydimethylsiloxane (PDMS), the main constituent of silicones. A postprocessing protocol is developed to identify underlying polymer backbone structures as connected components in QMD trajectories. Furthermore, these backbones form a repository of radiation-damaged structures. A scheme for extracting and updating a library of isomorphically distinct structures is proposed to identify the spanning set and aid chemical interpretation of the repository. The analyses are applied to ensembles of cascade QMD simulations in which the four element types in PDMS are selectively excited in primary knock-on atom events. Our approach reveals a much higher degree of combinatorial complexity in this system than was inferred through radiolysis experiments. Probabilities are extracted for radiation-induced network changes including formation of branch points, carbon linkages, cycles, bond scissions, and carbon uptake into the Si–O siloxane backbone network. The general analysis framework presented here is readily extendable to modeling chemical degradation of other polymers and molecular materials and provides a basis for future quantum-informed multiscale modeling of radiation damage.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 1. Characterizing Thermal–Hydrological–Mechanical Processes

Abstract Bentonite clay is widely used in engineered barrier systems for the permanent disposal of high‐level radioactive waste due to its low permeability, high swelling capacity, and thermal stability. However, the complex thermal‐hydrological‐mechanical (THM) processes induced by heating from decaying radioactive waste and hydration from surrounding rock can lead to heterogeneous changes that are difficult to measure and predict. This study develops an Electrical Resistivity Tomography (ERT)‐based framework for monitoring THM processes, progressing from sample‐scale to bench‐scale tests, to inform field‐scale applications. Sample‐scale tests analyzed small bentonite samples under controlled variations in water content, temperature, and porosity to establish fundamental resistivity relationships. Bench‐scale tests involved larger bentonite columns subjected to heating (up to 200°C) and hydration under controlled pressure, simulating repository conditions. ERT measurements, complemented by X‐ray CT imaging, temperature monitoring, and tracing sensors, revealed coupled THM processes, such as hydration‐induced compression, swelling, and thermal gradients, leading to complex resistivity patterns. The results demonstrate the potential of ERT for capturing THM‐induced resistivity changes, though challenges remain in upscaling and quantitative analysis. This study evaluates laboratory test capabilities and proposes future improvements for understanding THM‐induced resistivity responses. A conceptual framework for ERT implementation in field‐scale monitoring is presented, synthesizing findings from both scales and exploring how ERT data can inform long‐term modeling and reduce prediction uncertainties. Overall, this ERT‐based framework offers a robust method for monitoring bentonite buffers, aiding in early issue detection and supporting the safe long‐term disposal of radioactive waste in geological repositories, while highlighting the need for future development. Plain Language Summary Bentonite clay is crucial in engineered barrier systems (EBS) for containing high‐level radioactive waste due to its ability to absorb water, swell, seal and remain stable under high temperatures. When bentonite absorbs water and heats up from radioactive decay, it experiences complex changes in its physical and mechanical properties. Understanding these changes is important for ensuring the long‐term safety and effectiveness of EBS. This study used Electrical Resistivity Tomography (ERT), a non‐invasive method that measures electrical conductivity to monitor these changes during laboratory experiments. The ERT data revealed significant variations in resistivity corresponding to changes in water content, temperature, and density, providing detailed spatial and temporal insights into the behavior of bentonite. These findings enhance our ability to predict the long‐term performance of bentonite barriers, ensuring the safe containment of radioactive waste. By improving our understanding of bentonite's behavior, this research supports the development of more reliable and effective barrier systems for radioactive waste disposal, protecting the environment and public health. Key Points ERT monitoring was employed to capture resistivity changes in bentonite during controlled heating and hydration experiments, providing insights into THM processes ERT data reveal significant resistivity changes correlated with water content, temperature, and mechanical effects, enhancing the understanding of THM dynamics in bentonite This study explores the potential of the framework for application in field‐scale EBS monitoring, emphasizing the need for integrating additional geophysical methods for comprehensive subsurface imaging

Chen, Hang↗
DOE OSTI2012

A search model for topological insulators with high-throughput robustness descriptors

Topological insulators (TI) are becoming one of the most studied classes of novel materials because of their great potential for applications ranging from spintronics to quantum computers. To fully integrate TI materials in electronic devices, high-quality epitaxial single-crystalline phases with sufficiently large bulk bandgaps are necessary. Current efforts have relied mostly on costly and time-consuming trial-and-error procedures. Here we show that by defining a reliable and accessible descriptor {cflx X}TI, which represents the topological robustness or feasibility of the candidate, and by searching the quantum materials repository aflowlib.org, we have automatically discovered 28 TIs (some of them already known) in five different symmetry families. These include peculiar ternary halides, Cs{l_brace}Sn,Pb,Ge{r_brace}{l_brace}Cl,Br,I{r_brace}{sub 3}, which could have been hardly anticipated without high-throughput means. Our search model, by relying on the significance of repositories in materials development, opens new avenues for the discovery of more TIs in different and unexplored classes of systems.

36 MATERIALS SCIENCE↗
DOE OSTI2017

WastePD, an innovative center on materials degradation

The US Department of Energy recently awarded funds to create the Center for Performance and Design of Nuclear Waste Forms and Containers (WastePD) as part of the Energy Frontier Research Center (EFRC) program. EFRCs are multi-investigator collaborations of universities, national labs and companies that “conduct fundamental research focusing on one or more “grand challenges” and use-inspired “basic research needs” identified in major strategic planning efforts by the scientific community.” The major performance parameter of nuclear waste forms is their ability to isolate the radionuclides by withstanding degradation in a repository environment over very long periods of time. So WastePD is at heart a center focused on materials degradation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Accelerated, scalable and reproducible AI-driven gravitational wave detection

The development of reusable artificial intelligence (AI) models for wider use and rigorous validation by the community promises to unlock new opportunities in multi-messenger astrophysics. Here we develop a workflow that connects the Data and Learning Hub for Science, a repository for publishing AI models, with the Hardware-Accelerated Learning (HAL) cluster, using funcX as a universal distributed computing service. Using this workflow, an ensemble of four openly available AI models can be run on HAL to process an entire month's worth (August 2017) of advanced Laser Interferometer Gravitational-Wave Observatory data in just seven minutes, identifying all four binary black hole mergers previously identified in this dataset and reporting no misclassifications. This approach combines advances in AI, distributed computing and scientific data infrastructure to open new pathways to conduct reproducible, accelerated, data-driven discovery. By combining a repository for artificial intelligence models and a supercomputing cluster, an entire month's worth of advanced LIGO data is analysed in just 7 min, finding all binary black hole mergers previously identified in this dataset and reporting no misclassifications.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Emerging materials intelligence ecosystems propelled by machine learning

We report that the age of cognitive computing and artificial intelligence (AI) is just dawning. Inspired by its successes and promises, several AI ecosystems are blossoming, many of them within the domain of materials science and engineering. These materials intelligence ecosystems are being shaped by several independent developments. Machine learning (ML) algorithms and extant materials data are utilized to create surrogate models of materials properties and performance predictions. Materials data repositories, which fuel such surrogate model development, are mushrooming. Automated data and knowledge capture from the literature (to populate data repositories) using natural language processing approaches is being explored. The design of materials that meet target property requirements and of synthesis steps to create target materials appear to be within reach, either by closed-loop active-learning strategies or by inverting the prediction pipeline using advanced generative algorithms. AI and ML concepts are also transforming the computational and physical laboratory infrastructural landscapes used to create materials data in the first place. Surrogate models that can outstrip physics-based simulations (on which they are trained) by several orders of magnitude in speed while preserving accuracy are being actively developed. Automation, autonomy and guided high-throughput techniques are imparting enormous efficiencies and eliminating redundancies in materials synthesis and characterization. The integration of the various parts of the burgeoning ML landscape may lead to materials-savvy digital assistants and to a human-machine partnership that could enable dramatic efficiencies, accelerated discoveries and increased productivity. Here, we review these emergent materials intelligence ecosystems and discuss the imminent challenges and opportunities. The materials research landscape is being transformed by the infusion of approaches based on machine learning. This Review discusses the emerging materials intelligence ecosystems and the potential of human-machine partnerships for fast and efficient virtual materials screening, development and discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A database of refractive indices and dielectric constants auto-generated using ChemDataExtractor

The ability to auto-generate databases of optical properties holds great potential for advancing optical research, especially with regards to the data-driven discovery of optical materials. An optical property database of refractive indices and dielectric constants is presented, which comprises a total of 49,076 refractive index and 60,804 dielectric constant data records on 11,054 unique chemicals. The database was auto-generated using the state-of-the-art natural language processing software, ChemDataExtractor, using a corpus of 388,461 scientific papers. The data repository offers a representative overview of the information on linear optical properties that resides in scientific papers from the past 30 years. Public availability of these data will enable a quick search for the optical property of certain materials. The large size of this repository will accelerate data-driven research on the design and prediction of optical materials and their properties. To the best of our knowledge, this is the first auto-generated database of optical properties from a large number of scientific papers. We provide a web interface to aid the use of our database.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Network Analysis of Academic Medical Center Websites in the United States

Healthcare resources are published annually in repositories such as the AHA Annual Survey Database TM . However, these data repositories are created via manual surveying techniques which are cumbersome in collection and not updated as frequently as website information of the respective hospital systems represented. Also, this resource is not widely available to patients in an easy-to-use format. Network analysis techniques have the potential to create topological maps which serve to aid in pathfinding for patients in their search for healthcare services. This study explores the topological structure of forty United States academic health center websites. Network analysis is utilized to analyze and visualize 48,686 webpages. Several elements of network structure are examined including basic network properties, and centrality measures distributions. The Louvain community detection algorithm is used to examine the extent to which these techniques allow identification of healthcare resources within networks. The results indicate that websites with related healthcare services tend to form observable clusters useful in mapping key resources within a hospital system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A database of hourly wind speed and modeled generation for US wind plants based on three meteorological models

Abstract In 2022, wind generation accounted for ~10% of total electricity generation in the United States. As wind energy accounts for a greater portion of total energy, understanding geographic and temporal variation in wind generation is key to many planning, operational, and research questions. However, in-situ observations of wind speed are expensive to make and rarely shared publicly. Meteorological models are commonly used to estimate wind speeds, but vary in quality and are often challenging to access and interpret. The Plant-Level US multi-model WIND and generation (PLUSWIND) data repository helps to address these challenges. PLUSWIND provides wind speeds and estimated generation on an hourly basis at almost all wind plants across the contiguous United States from 2018–2021. The repository contains wind speeds and generation based on three different meteorological models: ERA5, MERRA2, and HRRR. Data are publicly accessible in simple csv files. Modeled generation is compared to regional and plant records, which highlights model biases and errors and how they differ by model, across regions, and across time frames.

17 WIND ENERGY↗
DOE OSTI2024

A compendium of multi-omics data illuminating host responses to lethal human virus infections

Human infections caused by viral pathogens trigger a complex gamut of host responses that limit disease, resolve infection, generate immunity, and contribute to severe disease or death. Here, we present experimental methods and multi-omics data capture approaches representing the global host response to infection generated from 45 individual experiments involving human viruses from the Orthomyxoviridae, Filoviridae, Flaviviridae, and Coronaviridae families. Analogous experimental designs were implemented across human or mouse host model systems, longitudinal samples were collected over defined time courses, and global multi-omics data (transcriptomics, proteomics, metabolomics, and lipidomics) were acquired by microarray, RNA sequencing, or mass spectrometry analyses. For comparison, we have included transcriptomics datasets from cells treated with type I and type II human interferon. Raw multi-omics data and metadata were deposited in public repositories, and we provide a central location linking the raw data with experimental metadata and ready-to-use, quality-controlled, statistically processed multi-omics datasets not previously available in any public repository. This compendium of infection-induced host response data for reuse will be useful for those endeavouring to understand viral disease pathophysiology and network biology.

60 APPLIED LIFE SCIENCES↗