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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

WA-Omic_LA.1.0 - Quantitative Lipidomics, Metabolomics, and Sequencing (16S/ITS) Publication Data DOI Package

Corresponding Data Publication: "Rapid remodeling of the soil lipidome in response to a drying-rewetting event." This study reveals specific changes in lipids and metabolites that are indicative of stress adaptation, substrate use, and cellular recovery during soil drying and subsequent rewetting. Drought induced nutrient limitation was reflected in the lipidome and polar metabalome, both of which rapidly shifted (within hours) upon rewet. Reduced nutrient access in dry soil caused the replacement of glycerophospholipids with phosphorus-free lipids and impeded resource-expensive osmolyte accumulation. Elevated levels of ceramides and lipids with long chain polyunsaturated fatty acids, in dry soil suggests that lipids play an important role in fungal drought tolerance. Increasing abundance of bacterial glycerophospholipids and triacylglycerols with fatty acids typical of bacteria and polar metabolites suggest metabolic recovery in representative bacteria once the environmental conditions are conducive for growth. These results underscore the importance of the soil lipidome as a robust indicator of microbial community responses, especially at the short time scales of cell-environment reactions. Data package contents reported here are the first version and contain pre- and post-processed data acquisition and subsequent downstream analysis files using various data source instrument method techniques and Mass Spectroscopy (MS) EMSL capabilities. This publication data package DOI is a comprehensive high-throughput multi-omics data lifecycle collection containing processed data method metadata. Support files include additional data download “Read Me” file containing data descriptor information and data source application ontologies (see data dictionary). Reported data download contents are structured for compliance with project data sharing guidelines, community standards initiatives, and sponsor stakeholder policies supporting FAIR data principles. For increased data availability and interoperability, GC-MS/LC-MS mass spectrometry datasets (Thermo .raw ) were deposited at the MassIVE database repository under the related data accession MSV000086931 and can be accessed by using the API. Statistical data processing software, analysis tools, and data workflows are listed below corresponding to the host repository long-term location.

Amplicon sequencing 16S ITS LC-MS/MS lipidomics mu↗
DOE OSTI2021

WA-Omic_LA.1.0 - Quantitative Lipidomics, Metabolomics, and Sequencing (16S/ITS) Publication Data DOI Package

Corresponding Data Publication: "Rapid remodeling of the soil lipidome in response to a drying-rewetting event." This study reveals specific changes in lipids and metabolites that are indicative of stress adaptation, substrate use, and cellular recovery during soil drying and subsequent rewetting. Drought induced nutrient limitation was reflected in the lipidome and polar metabalome, both of which rapidly shifted (within hours) upon rewet. Reduced nutrient access in dry soil caused the replacement of glycerophospholipids with phosphorus-free lipids and impeded resource-expensive osmolyte accumulation. Elevated levels of ceramides and lipids with long chain polyunsaturated fatty acids, in dry soil suggests that lipids play an important role in fungal drought tolerance. Increasing abundance of bacterial glycerophospholipids and triacylglycerols with fatty acids typical of bacteria and polar metabolites suggest metabolic recovery in representative bacteria once the environmental conditions are conducive for growth. These results underscore the importance of the soil lipidome as a robust indicator of microbial community responses, especially at the short time scales of cell-environment reactions. Data package contents reported here are the first version and contain pre- and post-processed data acquisition and subsequent downstream analysis files using various data source instrument method techniques and Mass Spectroscopy (MS) EMSL capabilities. This publication data package DOI is a comprehensive high-throughput multi-omics data lifecycle collection containing processed data method metadata. Support files include additional data download “Read Me” file containing data descriptor information and data source application ontologies (see data dictionary). Reported data download contents are structured for compliance with project data sharing guidelines, community standards initiatives, and sponsor stakeholder policies supporting FAIR data principles. For increased data availability and interoperability, GC-MS/LC-MS mass spectrometry datasets (Thermo .raw ) were deposited at the MassIVE database repository under the related data accession MSV000086931 and can be accessed by using the API. Statistical data processing software, analysis tools, and data workflows are listed below corresponding to the host repository long-term location.

Amplicon sequencing 16S ITS LC-MS/MS lipidomics mu↗
DOE OSTI2022

Astronauts Plasma-Derived Exosomes Induced Aberrant EZH2-Mediated H3K27me3 Epigenetic Regulation of the Vitamin D Receptor

There are unique stressors in the spaceflight environment. Exposure to such stressors may be associated with adverse effects on astronauts' health, including increased cancer and cardiovascular disease risks. Small extracellular vesicles (sEVs, i.e., exosomes) play a vital role in intercellular communication and regulate various biological processes contributing to their role in disease pathogenesis. To assess whether spaceflight alters sEVs transcriptome profile, sEVs were isolated from the blood plasma of 3 astronauts at two different time points: 10 days before launch (L-10) and 3 days after return (R+3) from the Shuttle mission. AC16 cells (human cardiomyocyte cell line) were treated with L-10 and R+3 astronauts-derived exosomes for 24 h. Total RNA was isolated and analyzed for gene expression profiling using Affymetrix microarrays. Enrichment analysis was performed using Enrichr. Furthermore, transcription factor (TF) enrichment analysis using the ENCODE/ChEA Consensus TF database identified gene sets related to the polycomb repressive complex 2 (PRC2) and Vitamin D receptor (VDR) in AC16 cells treated with R+3 compared to cells treated with L-10 astronauts-derived exosomes. Further analysis of the histone modifications using datasets from the Roadmap Epigenomics Project confirmed enrichment in gene sets related to the H3K27me3 repressive mark. Interestingly, analysis of previously published H3K27me3–chromatin immunoprecipitation sequencing (ChIP-Seq) ENCODE datasets showed enrichment of H3K27me3 in the VDR promoter. Collectively, our results suggest that astronaut-derived sEVs may epigenetically repress the expression of the VDR in human adult cardiomyocytes by promoting the activation of the PRC2 complex and H3K27me3 levels.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

National Energy Water Treatment and Speciation (NEWTS) Database & Dashboard

The Department of Energy's Office of Fossil Energy & Carbon Management (DOE/FECM) through the National Energy Technology Laboratory (NETL) has launched a free online tool, the National Energy Water Treatment and Speciation (NEWTS) Database and Dashboard, which can be utilized by community leaders and water researchers to better understand the composition of energy-related wastewater streams. The NEWTS Database and Dashboard provide public access to difficult-to-access datasets, including the original data sources and the processed data forms for input into aqueous chemistry modeling software. The data provided by the tool will help mitigate environmental risks and identify possible sources of valuable critical minerals (CM). The goal of this ASME Power presentation is to highlight the data and capabilities of this free online-tool for obtaining high quality water datasets in formats that are easy for modeling the treatment and recovery of valuable resources from effluent waste stream associated with energy operations.

Siefert, Nicholas↗
DOE OSTI2023

Cross-database comparisons on the greenhouse gas emissions, water consumption, and fossil-fuel use of plastic resin production and their post-use phase impacts

Resin production and post-use pathways have cross-database discrepancies due to different temporal/geographic representation, technologies, and assumptions. These differences can distort comparisons across alternatives and confound efforts to establish standards based on the plastics’ life-cycle impacts. Thus, this study quantifies the degree and identifies the sources of cross-database discrepancies across four LCA databases (GREET, USLCI, Ecoinvent, and GaBi) for five resin production pathways and three post-use phases. For resin production pathways, all resins showed significant cross-database discrepancy in their global warming impacts: the degree of discrepancy was significant to recommend a consistent choice of database to users any LCA comparisons across different products. For post-use phases, landfill datasets had relatively lower degree of cross-database discrepancy than incineration and mechanical recycling. Different metadata characteristics were the sources of some cross-database discrepancies while other parts could be explained by the original differences in the life-cycle inventory sourced from different producers and plants.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

FeGenie: a comprehensive tool for the identification of iron genes and iron gene neighborhoods in genomes and metagenome assemblies

Iron is a micronutrient for nearly all life on Earth. It can be used as an electron donor and electron acceptor by iron-oxidizing and iron-reducing microorganisms and is used in a variety of biological processes, including photosynthesis and respiration. While it is the fourth most abundant metal in the Earth’s crust, iron is often limiting for growth in oxic environments because it is readily oxidized and precipitated. Much of our understanding of how microorganisms compete for and utilize iron is based on laboratory experiments. However, the advent of next-generation sequencing and surge in publicly available sequence data has made it possible to probe the structure and function of microbial communities in the environment. To bridge the gap between our understanding of iron acquisition, iron redox cycling, iron storage, and magnetosome formation in model microorganisms and the plethora of sequence data available from environmental studies, we have created a comprehensive database of hidden Markov models (HMMs) based on genes related to iron acquisition, storage, and reduction/oxidation in Bacteria and Archaea. Along with this database, we present FeGenie, a bioinformatics tool that accepts genome and metagenome assemblies as input and uses our comprehensive HMM database to annotate provided datasets with respect to iron-related genes and gene neighborhood. An important contribution of this tool is the efficient identification of genes involved in iron oxidation and dissimilatory iron reduction, which have been largely overlooked by standard annotation pipelines. We validated FeGenie against a selected set of 28 isolate genomes and showcase its utility in exploring iron genes present in 27 metagenomes, 4 isolate genomes from human oral biofilms, and 17 genomes from candidate organisms, including members of the candidate phyla radiation. We show that FeGenie accurately identifies iron genes in isolates. Furthermore, analysis of metagenomes using FeGenie demonstrates that the iron gene repertoire and abundance of each environment is correlated with iron richness. While this tool will not replace the reliability of culture-dependent analyses of microbial physiology, it provides reliable predictions derived from the most up-to-date genetic markers. FeGenie’s database will be maintained and continually updated as new genes are discovered.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

MiR-205–5p suppresses angiogenesis in gastric cancer by downregulating the expression of VEGFA and FGF1

Highlights: • MiR-205-5p was commonly downregulated in GC tissues from TCGA database and our hospital, and these events were associated with a worse TNM stagedistant metastasis and poor survival. • MiR-205-5p and CD31 expressions were negatively inter-related within GC tissues from TCGA database and our hospital. • GC cell lines expressed lower level of miR-205-5p significantly as compared with the normal gastric cell line. • MiR-205-5p upregulation significantly impaired proliferation and colony formation of GC cells and neovascularization induced by GC cells in vitro and in vivo. • The angiogenesis and ERK-signaling were depressed by VEGFA and FGF1 downregulation induced by miR-205-5p overexpression. The miR-205-5p inhibitor promoted malignant phenotypes by enhancing VEGFA and FGF1 expressions, as well as the activation of ERK-signaling. Anti-angiogenic therapy represents one of the most promising treatment modalities for human cancers. However, the response to antiangiogenic therapy in gastric cancer (GC) remains dismal. To help identify new strategies for antiangiogenic therapy in GC, we evaluated miR-205–5p expression in GC tissues from TCGA database and our hospital, and its functions in angiogenesis were explored in vitro and in vivo. We investigated miR-205–5p expression and microvessel densities (MVDs) in GC tissues and liver metastases from patients. The function and mechanisms of miR-205–5p were examined in human cell lines and in xenograft mouse models. Associations between miR-205–5p expression and clinical characteristics were analyzed using either Pearson's χ{sup 2} test or Fisher's exact test. Differences in overall survival (OS) distributions were evaluated using the log-rank test. Differences in measurement data were compared using Student's t-test and one-way ANOVA. We found that miR-205–5p expression was downregulated in GC tissues and was negatively correlated with CD31 expression in both TCGA and our clinical samples. GC cell lines expressed low levels of miR-205–5p, and miR-205–5p upregulation significantly impaired the proliferation and angiogenesis of GC cells. Moreover, vascular endothelial growth factor A (VEGFA) and fibroblast growth factor 1 (FGF1) expression and activation of extracellular-related kinase (ERK) signaling were suppressed by miR-205–5p. MiR-205–5p inhibition promoted malignant phenotypes by enhancing VEGFA and FGF1 expression, as well as the activation of ERK signaling. Angiogenesis and ERK signaling were decreased in response to VEGFA and FGF1 downregulation induced by miR-205–5p overexpression. The dual-luciferase reporter assay showed that VEGFA and FGF1 were direct targets of miR-205–5p. Xenograft mouse models revealed that miR-205–5p suppressed tumor growth by inhibiting neovascularization. Altogether, these results demonstrate that miR-205–5p suppresses angiogenesis in GC by attenuating the expression of VEGFA and FGF1, indicating that upregulation of miR-205–5p may represent as an antiangiogenic therapy for GC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Structural Flexibility of Metal Chelate Complexes and Its Relation to Supramolecular Chemistry

In this study, crystal structures of metal chelate and related complexes in the Cambridge Structural Database have been analyzed, with respect to their use as components in supramolecular metal-organic compounds. In β-diketonate complexes, the distribution of angles between ligands is relatively broad; other ligands, such as 2,2'-bipyridine, yield significantly narrower distributions. According to the principle of structure correlation, these distributions reflect the ease of distorting the various families of complexes. A comparison through density functional theory calculations also indicates that angular distortions require significantly less energy for M(β-diketonate) 3 than for M(2,2'-bipyridine) 3 . The differences are likely to affect the construction of supramolecular systems from different combinations of metals and ligands, including the likelihood that the desired structures will be obtained.

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

Large-scale computational polymer solubility predictions and applications to dissolution-based plastic recycling

Dissolution-based plastic recycling is a promising approach to separate and recover high quality pure polymer resins from multicomponent plastic waste by exploiting differences in polymer solubility. The design of a dissolution-based polymer recycling process requires the selection of appropriate solvent systems and operating temperatures to dissolve only target polymers. Determining these parameters experimentally is challenging due to the wide range of solvents and temperatures possible for a given set of target polymers. In this work, we report a computational scheme that employs molecular dynamics simulations and the Conductor-like Screening Model for Realistic Solvents to predict polymer solubilities. Using this scheme, we established a computational solubility database for 8 common polymers and 1007 solvents at multiple temperatures and measured selected solubilities experimentally to validate computational predictions. Analysis of functional groups within this large database then provides chemical heuristics relating the molecular structures of good and non-solvents for selected polymers. We further developed a tool that automates the selection of solvents for all possible sequences in which target polymers can be selectively dissolved to guide the design of dissolution-based plastic recycling processes. Here, we demonstrate the application of these methods via multiple experimental case studies of representative dissolution-based polymer recycling processes in which pure polymer resins were successfully recovered from physical mixtures of polymers.

42 ENGINEERING↗
DOE OSTI2022

Check the Storage Stack: Comparing Behind-the-Meter Energy Storage State Policy Stacks in the United States

A variety of studies and disparate datasets track state energy storage polices, but these datasets do not cover all BTM-related storage policy. Moreover, these databases do not align these policies with the policy stacking framework. Thus, it is unclear what BTM storage policies are adopted across the country, what should comprise a complete storage policy framework or stack, and how states policies compare against that stack. This report addresses this gap in the literature by developing a state policy stack for BTM battery storage that we compare across all fifty states. This first-of-its-kind BTM storage policy stack includes 11 parent policy categories, and 31 associated policies divided across the market preparation, creation, and expansion policy components.

25 ENERGY STORAGE↗
DOE OSTI2022

Behind-the-Meter Storage Policy Stack

A variety of studies and disparate data sets track state energy storage policies, but these datasets do not cover all BTM-related storage policy. Moreover, these databases do not align policies with the policy stacking framework. Thus, it is unclear which BTM storage policies are adopted across the country, what should comprise a complete storage policy framework or stack, or how states policies compare with that stack. This first-of-its-kind BTM storage policy stack includes 11 parent policy categories and 31 policies across the market preparation, creation, and expansion policy components.

25 ENERGY STORAGE↗
DOE OSTI2021

Analysis of Spectral Lines in Large Databases of Synthetic Spectra for Massive Stars

In this paper, we describe a program that identifies in the optical spectrum the main parameters of a spectral line, namely the initial and final wavelengths, and the line depth. Moreover, using numerical calculations, it identifies and removes adjacent lines. Next, the program calculates the equivalent width and the FWHM. The software was tested in a sample of 300 lines in two databases of synthetic spectra generated by the CMFGEN and PoWR codes, and 300 lines in observed spectra from the IACOB database, showing a Gaussian distribution of relative errors, from which it is inferred that 80% of the measured lines have errors less than 17% and only 5% of the lines have errors greater than 26%. The program was also run on the entire database of 45,000 CMFGEN and 202 POWR synthetic spectra, generating a library of H i, He i, and He ii lines necessary to feed the FITspec code for the derivation of stellar parameters: effective temperature, surface gravity, and luminosity.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Advances in Metallic Fuel Database Development and Data Qualification

The Fuels Irradiation and Physics Database (FIPD [1]) is a comprehensive repository of data and documents related to Uranium-Zirconium based metallic fuel test pins. This database stores operational conditions of these pins, calculated using a suite of Argonne National Laboratory analysis codes developed during the Integral Fast Reactor (IFR) program. Key calculated data include axial distributions of power, temperature, fluence, burnup, and isotopic densities. Additionally, the FIPD holds post-irradiation examination (PIE) data such as fission gas release, gas chemistry measurements, and axial distributions derived from profilometry, gamma scanning, and neutron radiography. Complementing these data is an extensive archive of documents related to various pins and experiments. These include raw PIE records, design details, safety analyses, and operational reports. More detail about FIPD can be found in ref. [2]. The database development is an ongoing effort covering metallic fuel experiments from the Experimental Breeder Reactor II (EBR-II) and the Fast Flux Test Facility (FFTF). The recent improvements to the database and the data QA status are summarized in this paper.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Glass formulation and composition optimization with property models: A review

Abstract Glass is a versatile material with a remarkable history and many practical applications. It plays a critical role in our everyday lives, the advancement of science, and the development of many technologies. The Edisonian type trial‐and‐error method was commonly used for conventional design of glass compositions, which was time‐consuming and costly. With the urgent need to develop new glass compositions for technology applications rapidly, it has become necessary to develop precise property models with predictive powers using large databases and efficient formulation approaches. This paper reviews the design of glass compositions using these analytical and numerical models of composition–structure–property relations of glasses, some based on large databases and machine learning approaches. Aspects of data collection, model fitting, feature extraction, model evaluation, and uncertainty quantification will be covered. Furthermore, advances in the glass optimization framework and available tools are summarized with examples. The outlook and perspective for further glass property model development and formulation approaches are discussed.

Lu, Xiaonan↗
DOE OSTI2024

FatPlants: a comprehensive information system for lipid-related genes and metabolic pathways in plants

Abstract FatPlants, an open-access, web-based database, consolidates data, annotations, analysis results, and visualizations of lipid-related genes, proteins, and metabolic pathways in plants. Serving as a minable resource, FatPlants offers a user-friendly interface for facilitating studies into the regulation of plant lipid metabolism and supporting breeding efforts aimed at increasing crop oil content. This web resource, developed using data derived from our own research, curated from public resources, and gleaned from academic literature, comprises information on known fatty-acid-related proteins, genes, and pathways in multiple plants, with an emphasis on Glycine max, Arabidopsis thaliana, and Camelina sativa. Furthermore, the platform includes machine-learning based methods and navigation tools designed to aid in characterizing metabolic pathways and protein interactions. Comprehensive gene and protein information cards, a Basic Local Alignment Search Tool search function, similar structure search capacities from AphaFold, and ChatGPT-based query for protein information are additional features. Database URL: https://www.fatplants.net/

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Multiresolution classification of turbulence features in image data through machine learning

During large-scale simulations, intermediate data products such as image databases have become popular due to their low relative storage cost and fast in-situ analysis. Serving as a form of data reduction, these image databases have become more acceptable to perform data analysis on. In this work, we present an image-space detection and classification system for extracting vortices at multiple scales through wavelet-based filtering. A custom image-space descriptor is used to encode a large variety of vortex-types and a machine learning system is trained for fast classification of vortex regions. By combining a radial-based histogram descriptor, a bag of visual words feature descriptor, and a support vector machine, our results show that we are able to detect and classify vortex features at various sizes at multiple scales. Once trained, our framework enables the fast extraction of vortices on new, unknown image datasets for flow analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Open database for GPD analyses

This article summarizes the main ideas behind creating an open database proposed for use in the exploration of generalized parton distributions (GPDs). This lightweight database is well suited for GPD phenomenology and is designed to store both experimental and lattice-QCD data. It can also aid in benchmarking GPD-related developments, such as GPD models. The database utilizes a new data format based on the YAML serialization language, enabling the storage of essential information for modern analyses, such as replica values. It includes interfaces for both Python and C++, allowing straightforward integration with analysis codes.

Burkert, V. D. [Thomas Jefferson National Accelera↗