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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Structural models and functional annotations for the Sphagnum divinum proteome

This dataset contains the structural models for the primary transcripts of the Sphagnum divinum proteome. Additionally, for a subset of these proteins, sequence and structural alignment results are provided. This dataset represents the most thorough structural study of a Sphagnum species, also known as peat mosses, by providing three-dimensional atomic resolution structures of the majority of the encoded proteins as well as structural alignment results used in the application of annotating the proteome. References (DOI) AlphaFold v2 Monomer: https://doi.org/10.1038/s41586-021-03819-2. References (DOI) US-align2: https://doi.org/10.1038/s41592-022-01585-1

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Structural Models and Sequence Alignment Results of the Rhodospirillum rubrum Proteome

This dataset contains the structural models for the primary transcripts of the Rhodospirillum rubrum proteome as well as sequence alignment results for a subset of the encoded proteins. For each protein, the five models inferred from AlphaFold 2 are provided. The largest pTM-scoring model for each protein was energy minimized; this minimized structure as well as its AlphaFold pickle output file are also provided. This set of structures represent an alternate source of models for the R. rubrum proteome to those available in the AlphaFold Protein Structure Database. For proteins that have been annotated as hypothetical, sequence alignment results from the HHblits and SAdLSA alignment methods are provided. These methods are often more capable to resolve sequence homology than other methods. Therefore, the results from both HHblits and SAdLSA are provided to identify possible homologs for these challenging proteins. Numerous sequence databases are utilized for these alignments. References AlphaFold v2 Multimer: https://doi.org/10.1101/2021.10.04.463034. References HHBlits: https://doi.org/10.1186/s12859-019-3019-7. References SAdLSA: https://doi.org/10.3389/fbinf.2021.689960.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Structural Models and Sequence Alignment Results of the Desulfovibrio vulgaris Proteome

This dataset contains the structural models for the primary transcripts of the Desulfovibrio vulgaris proteome as well as sequence alignment results for a subset of the encoded proteins. For each protein, the five models inferred from AlphaFold 2 are provided. The largest pTM-scoring model for each protein was energy minimized; this minimized structure as well as its AlphaFold pickle output file are also provided. This set of structures represent an alternate source of models for the D. vulgaris proteome to those available in the AlphaFold Protein Structure Database (AFDB). This is a bit more complicated since the proteins reporting in the AFDB originate from an outdated form of the D. vulgaris sequence. The different versions of the D. vulgaris gene annotation are collected in the Chronology subdirectory; further consideration of these changes on the structural space of the proteome are currently underway. For proteins that have been annotated as hypothetical, sequence alignment results from the HHblits and SAdLSA alignment methods are provided. These methods are often more capable to resolve sequence homology than other methods. Therefore, the results from both HHblits and SAdLSA are provided to identify possible homologs for these challenging proteins. Numerous sequence databases are utilized for these alignments. References AlphaFold v2 Multimer: https://doi.org/10.1101/2021.10.04.463034. References HHblits: hhtps://doi.org/10.1186/s12859-019-3019-7. References SAdLSA: hhtps://doi.org/10.3389/fbinf.2021.689960.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Structural Models of the Rhodopseudomonas palustris Proteome

This dataset contains the structural models for the primary transcripts of the Rhodopseudomonas palustris proteome. For each protein, the five models inferred from AlphaFold 2 are provided. The largest pTM-scoring model for each protein was energy minimized; this minimized structure as well as its AlphaFold pickle output file are also provided. This set of structures represent an alternate source of models for the R. palustris proteome to those available in the AlphaFold Protein Structure Database.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Dataset for Role of electron correlation on the adenine dimer interaction for non-equilibrium geometries: a benchmark Quantum Monte Carlo study

Datasets for the calculations reported in "Role of electron correlation on the adenine dimer interaction for non-equilibrium geometries: A benchmark Quantum Monte Carlo study" by L. Washburn, A. Sedova, P. R. C. Kent. J. Chem. Phys. (2026) 165 (5): 054118. https://doi.org/10.1063/5.0332651. Includes the molecular geometries, QMCPACK, PySCF, and ORCA inputs and outputs, analysis scripts and files needed to reproduce all the figures and tables.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Environmental Monitoring Plan

The purpose of environmental monitoring is to promote the early identification of, and response to, potential adverse environmental impacts associated with Lawrence Livermore National Laboratory (LLNL) operations. Environmental monitoring supports the Integrated Safety Management System (ISMS), International Organization for Standardization (ISO) 14001 Environmental Management Systems standard, and U. S. Department of Energy (DOE) Order 458.1, Radiation Protection of the Public and the Environment. Specifically, environmental monitoring enables LLNL to detect, characterize, and respond to releases from LLNL activities; assess impacts; estimate dispersal patterns in the environment; characterize the pathways of exposure to members of the public; characterize the exposures and doses to individuals and to the population; and to evaluate the potential impacts to the biota in the vicinity of LLNL. Environmental monitoring is also a major component of compliance demonstration for permits and other regulatory requirements.

Environmental sciences↗
DOE OSTI2020

UNITY: Unified Memory and Storage Space

UNITY is a 36-month project focused on providing design and evaluate a new distributed storage paradigm that unifies the traditionally distinct application views of memory- and file-based data storage into a single scalable and resilient environment. The project is a collaboration among Oak Ridge National Laboratory (ORNL, Lead institution), Los Alamos National Labs (LANL), and Georgia Tech (GT). The main contributions of the GT team have been around development of low level systems software for best leveraging the capabilities of new types of persistent memory technologies, and for development of methods for intelligent data management across memory/storage substrates with heterogeneous components. GT contributed the Phoenix library for optimized checkpoint/restart for HPC I/O for systems with non-volatile memory (NVM), the NVStream library for NVM-specialized streaming I/O for HPC workflows, the CoMerge, Mnemo and Kleio solutions for intelligent data management on NVM-based systems. These contributions result in significant improvements in both application performance and system efficiency.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Lawrence Livermore National Laboratory Annual Environmental Report 2019

The purposes of the Lawrence Livermore National Laboratory (LLNL) Environmental Report 2019 are to record LLNL's compliance with environmental standards and requirements, describe LLNL’s environmental protection and remediation programs, and present the results of environmental monitoring at the two LLNL sites—the Livermore Site and Site 300. The report is prepared for the U.S. Department of Energy (DOE) by LLNL’s Environmental Functional Area. Submittal of the report satisfies requirements under DOE Order 231.1B, “Environment, Safety and Health Reporting,” and DOE Order 458.1, “Radiation Protection of the Public and Environment.” The report begins with an executive summary, which provides the purpose of the report and an overview of LLNL’s compliance and monitoring results. The first three chapters provide background information: Chapter 1 is an overview of the location, meteorology, and hydrogeology of the two LLNL sites; Chapter 2 is a summary of LLNL’s compliance with environmental regulations; and Chapter 3 is a description of LLNL’s environmental programs with an emphasis on the Environmental Management System including pollution prevention. The majority of the report covers LLNL’s environmental monitoring programs and monitoring data for 2019: effluent and ambient air monitoring and dose assessment (Chapter 4); waters, including wastewater, storm water runoff, surface water, rain, and groundwater (Chapter 5); and terrestrial, including soil, sediment, vegetation, foodstuff, ambient radiation, and special status wildlife and plants (Chapter 6). The remaining two chapters discuss LLNL’s groundwater remediation program (Chapter 7), and quality assurance for the environmental monitoring programs (Chapter 8). Complete monitoring data, which are summarized in the body of the report, are provided in Appendix A.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Results of Late-Start LDRD Project "SHAZAM"

This report describes a Late-Start LDRD project on a self-healing power systems (SHePS) concept called SHAZAM. SHAZAM is designed to solve difficult challenges associated with creation of self-assembling, self-networking microgrids without high-speed networked communications. The report describes the SHAZAM concept, outlines the development of modeling tools and infrastructure supported by the Late-Start LDRD, gives examples of simulation results obtained to date, and discusses conclusions and proposed future work.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Lawrence Livermore National Laboratory Site Annual Environmental Report 2020

Lawrence Livermore National Laboratory (LLNL) is a premier research laboratory that is part of the National Nuclear Security Administration (NNSA) within the U.S. Department of Energy (DOE). As a national security laboratory, LLNL is responsible for ensuring that the nation’s nuclear weapons remain safe, secure, and reliable. The Laboratory also meets other pressing national security needs, including countering the proliferation of weapons of mass destruction and strengthening homeland security, and conducting major research in atmospheric, earth, and energy sciences, bioscience and biotechnology, and engineering, basic science, and advanced technology. The Laboratory is managed and operated by Lawrence Livermore National Security, LLC (LLNS), and serves as a scientific resource to the U.S. government and a partner to industry and academia.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Automated Vulnerability Detection (AVUD) for Compiled Smart Grid Software

This project developed and implemented a system for conducting cybersecurity vulnerability detection of smart grid components and systems by performing static analysis of compiled software (“firmware”). The resulting system for automated vulnerability detection (AVUD) was implemented as part of Oak Ridge National Laboratory’s existing test bed for smart meters, the Sustainable Campus Initiative. The work consisted of two phases: the first phase implemented the necessary software and computational models to perform the analysis, and the second phase demonstrated the system on example firmware in partnership with smart meter manufacturer Sensus USA, Inc. The resulting system won an R&D 100 award and has been successfully commercialized, winning a National Laboratory Consortium Commercialization Award.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Lawrence Livermore National Laboratory Environmental Report 2021

The purposes of the Lawrence Livermore National Laboratory Environmental Report 2021 are to record Lawrence Livermore National Laboratory’s (LLNL’s) compliance with environmental standards and requirements, describe LLNL’s environmental protection and remediation programs, and present the results of environmental monitoring at the two LLNL sites—the Livermore Site and Site 300. The report is prepared for the U.S. Department of Energy (DOE) by LLNL’s Environmental Functional Area. Submittal of the report satisfies requirements under DOE Order 231.1B, “Environment, Safety and Health Reporting,” and DOE Order 458.1, “Radiation Protection of the Public and Environment.” The report is distributed electronically and is available at https://saer.llnl.gov/, the website for the LLNL annual environmental report. Previous LLNL annual environmental reports beginning with 1994 are also on the website. Some references in the electronic report text are underlined, which indicates that they are clickable links. Clicking on one of these links will open the related document, data workbook, or website. Sampling location maps throughout this report were created using ArcGIS® software by Esri. The report begins with an executive summary, which provides the purpose of the report and an overview of LLNL’s compliance and monitoring results. The first three chapters provide background information: Chapter 1 is an overview of the location, meteorology, and hydrogeology of the two LLNL sites; Chapter 2 is a summary of LLNL’s compliance with environmental regulations; and Chapter 3 is a description of LLNL’s environmental programs with an emphasis on the Environmental Management System including pollution prevention. The majority of the report covers LLNL’s environmental monitoring programs and monitoring data for 2021: effluent and ambient air monitoring and dose assessment (Chapter 4); waters, including wastewater, storm water runoff, surface water, rain, and groundwater (Chapter 5); and terrestrial, including soil, sediment, vegetation, foodstuff, ambient radiation, and special status wildlife and plants (Chapter 6). The remaining two chapters discuss LLNL’s groundwater remediation program (Chapter 7), and quality assurance for the environmental monitoring programs (Chapter 8). Complete monitoring data, which are summarized in the body of the report, are provided in Appendix A. The report uses Système International units, consistent with the federal Metric Conversion Act of 1975 and Executive Order 12770, “Metric Usage in Federal Government Programs” (1991). For ease of comparison to environmental reports issued prior to 1991, dose values and many radiological measurements are given in both metric and U.S. customary units. A conversion table is provided in the glossary. The report is the responsibility of LLNL’s Environmental Functional Area. Monitoring data were obtained through the combined efforts of the Environmental Functional Area; Environmental Restoration Department; Physical and Life Sciences Environmental Monitoring Radiological Laboratory; and the Radiation Protection Functional Area.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

High throughput, accurate gene annotation through AI and HPC-enabled structural analysis

With the advances in next generation sequencing technologies, the number of sequenced genomes is growing exponentially, resulting in a technology bottleneck for the translation of sequence information into usable hypotheses about the function of each gene. We have proposed leveraging our leadership high-performance computing (HPC) resources to help break this annotation bottleneck. Here we design an HPC-based framework to infer gene function from gene sequence by incorporating information about protein structure and interactions predicted by deep learning approaches. Accurate functional prediction and gene annotation using computational methods will facilitate breakthroughs in the genomic sciences essential to understanding and harnessing life processes in bacteria, fungi and plants. The development and applications of the state-of-the-art deep neural networks to protein structural modeling, interaction prediction, sequence comparison, and quality assessment of protein structural models will be made possible by leadership computational resources. These HPC-enabled bioinformatics and molecular modeling tools will provide powerful insights into molecular functions of genes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Self-healing, self-assembling islanded power systems using only local measurements

This SAND report collects the results from the LDRD project “SHAZAM”, which aimed to push the limits of performance for self-healing, self-assembling power systems whose sectionalizing and load-control agents rely on local measurements only (i.e., only what they can measure at their own terminals, with no data sharing between agents). This work includes self-networking microgrids. The key objectives of this work were a) to demonstrate how high the performance of local-measurement-only self-assembling power systems can be; and b) to solve certain technical problems associated with such systems, such as their inability to prevent the accidental formation of closed loops and their tendency to thermally overload some conductors. “SHAZAM” investigators a) demonstrated that the performance of such systems can be surprisingly high, b) demonstrated that such systems are quite robust to all kinds of variations, and c) developed and demonstrated solutions to several key challenges associated with this type of system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Restoring Homes After Wildfires, Interviews with Practitioners about Common Cleanup Approaches and Knowledge Gaps

This document summarizes the key themes from our interviews with 10 remediation companies regarding common approaches used to remove odor and contaminants from homes impacted by fire and smoke damage Remediation companies are in agreement that thorough cleaning is the first step. Cleaning and removing contaminants from homes impacted by wildfires may be sufficient to eliminate smoke odor, which is the most important step when it comes to reducing exposure to any residues that may pose health risks to residents. Remediation companies differ in their approaches to addressing odors, such as using ozone generators, hydroxyl generators, chlorine dioxide treatment, thermal fogging and applying sealants. Their opinions of what works and why differs. There is little consensus on efficacy, safety, or application protocols. For example, some view ozone very favorably, while others would prefer using other methods. The influence of insurance companies in their coverage for some methods but not others also impact the decision about the approaches used. Remediation companies differ in their view on laboratory testing for contaminants, which may be partly influenced by insurance companies as well.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Optimizing Metadata Exchange: Leveraging DAOS for ADIOS Metadata I/O

In HPC I/O middleware like the Adaptable I/O System (ADIOS) often mediates data transfers between applications. The metadata I/O generated by such systems often presents significant scaling and performance limitations. This work seeks improvement opportunities for metadata I/O by leveraging the DAOS storage systems, a recent storage system solution deployed on high-end systems such as the Aurora supercomputer. We investigate the tradeoffs and the design space for integrating I/O engines for the ADIOS middleware based on the different storage mechanisms supported by DAOS. We present a new DAOS-Array-ChunkSize-aligned engine which provides up to 2.3× improved performance than when using the existing DAOS-POSIX interface, without requiring any application modifications.

Venkatesh, Ranjan Sarpangala↗
DOE OSTI2014

Impact of Amorphous SiO{sub 2} Nanoparticles on a Living Organism: Morphological, Behavioral, and Molecular Biology Implications

It is generally accepted that silica (SiO{sub 2}) is not toxic. But the increasing use of silica nanoparticles (SiO{sub 2}NPs) in many different industrial fields has prompted the careful investigation of their toxicity in biological systems. In this report, we describe the effects elicited by SiO{sub 2}NPs on animal and cell physiology. Stable and monodisperse amorphous silica nanoparticles, 25 nM in diameter, were administered to living Hydra vulgaris (Cnidaria). The dose-related effects were defined by morphological and behavioral assays. The results revealed an all-or-nothing lethal toxicity with a rather high threshold (35 nM NPs) and a LT50 of 38 h. At sub lethal doses, the morphophysiological effects included: animal morphology alterations, paralysis of the gastric region, disorganization and depletion of tentacle specialized cells, increase of apoptotic and collapsed cells, and reduction of the epithelial cell proliferation rate. Transcriptome analysis (RNAseq) revealed 45 differentially expressed genes, mostly involved in stress response and cuticle renovation. Our results show that Hydra reacts to SiO{sub 2}NPs, is able to rebalance the animal homeostasis up to a relatively high doses of SiO{sub 2}NPs, and that the physiological modifications are transduced to gene expression modulation.

60 APPLIED LIFE SCIENCES↗