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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 OSTI2021

Assessing the future of global energy-for-water

This study incorporates the energy demands of water abstraction, treatment, distribution, and post-use (wastewater) treatment into the Global Change Assessment Model (GCAM), an integrated human-Earth systems model, and analyzes a range of scenarios that estimate the future evolution of this demand of energy. The study builds on prior research on the historical demands of energy-for-water, fitting these demands of energy into existing nation-level energy balances, where demands for energy-for-water have heretofore been aggregated with other energy use in the commercial and public services, industrial, agricultural, and/or electric power sectors. This development allows for improved projections of future energy demands in general, and in this study, allows for assessment of the energy implications of different scenarios of improvements in water access and water quality that are consistent with the Sustainable Development Goals. In our baseline scenario, energy-for-water approximately doubles from 2010 to 2050, and in the scenario with the greatest level of water access, standards for treatment of wastewater, and irrigation expansion, the consequent energy-for-water demands increase three-fold from 2010 to 2050. Note also that these increases do not consider future scarcity-driven increases in energy requirements per unit of water abstraction, treatment, and distribution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Changes in fire weather climatology under 1.5 °C and 2.0 °C warming

Abstract The 2015 Paris Agreement led to a number of studies that assessed the impact of the 1.5 °C and 2.0 °C increases in global temperature over preindustrial levels. However, those assessments have not actively investigated the impact of these levels of warming on fire weather. In view of a recent series of high-profile wildfire events worldwide, we access fire weather sensitivity based on a set of multi-model large ensemble climate simulations for these low-emission scenarios. The results indicate that the half degree difference between these two thresholds may lead to a significantly increased hazard of wildfire in certain parts of the world, particularly the Amazon, African savanna and Mediterranean. Although further experiments focused on human land use are needed to depict future fire activity, considering that rising temperatures are the most influential factor in augmenting the danger of fire weather, limiting global warming to 1.5 °C would alleviate some risk in these parts of the world.

Son, Rackhun (ORCID:000000023366495X)↗
DOE OSTI2021

Simulating quantum materials with digital quantum computers

Quantum materials exhibit a wide array of exotic phenomena and practically useful properties. A better understanding of these materials can provide deeper insights into fundamental physics in the quantum realm as well as advance technology for entertainment, healthcare, and sustainability. The emergence of digital quantum computers (DQCs), which can efficiently perform quantum simulations that are otherwise intractable on classical computers, provides a promising path forward for testing and analyzing the remarkable, and often counter-intuitive, behavior of quantum materials. Equipped with these new tools, scientists from diverse domains are racing towards achieving physical quantum advantage (i.e., using a quantum computer to learn new physics with a computation that cannot feasibly be run on any classical computer). The aim of this review, therefore, is to provide a summary of progress made towards this goal that is accessible to scientists across the physical sciences. We will first review the available technology and algorithms, and detail the myriad ways to represent materials on quantum computers. Next, we will showcase the simulations that have been successfully performed on currently available DQCs, emphasizing the variety of properties, both static and dynamic, that can be studied with this nascent technology. Finally, we work through two examples of how to map a materials problem onto a DQC, with full code included in the Supplementary Material. It is our hope that this review can serve as an organized overview of progress in the field for domain experts and an accessible introduction to scientists in related fields interested in beginning to perform their own simulations of quantum materials on DQCs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Continental-Scale Controls on Hyporheic Respiration Revealed by Knowledge-Guided Machine Learning

Hyporheic zone sediments regulate organic matter turnover and in-stream respiration, yet controls on sediment respiration remain poorly constrained across heterogeneous river networks, limiting prediction of stream metabolism and carbon processing at continental scales. Here, we integrate observations from ~90 river corridors across the United States in the WHONDRS consortium with a knowledge-guided machine learning (KGML) framework that couples thermodynamic rate theory with machine learning to identify dominant controls on hyporheic respiration. Diagnostic analyses show that organic matter concentration and thermodynamic favorability define an upper bound on respiration potential, whereas biological catalytic capacity and physical accessibility jointly govern realized respiration rates through interaction effects. To represent unmeasurable accessibility constraints, we use the mechanistic model as a scaffold for KGML, allowing machine learning to target residual structure not explained by process theory. This hybrid framework improves predictive skill relative to both the mechanistic model alone and fully data-driven models while preserving interpretability. These results indicate that variability in hyporheic respiration is largely mechanistically structured and demonstrate how integrating process theory with explainable AI enhances predictive performance while enabling scalable synthesis of river corridor observations.

Zheng, Jianqiu↗
DOE OSTI2025

Hosting downscaled decision-relevant community data products in ESGF2-US

As regionally-relevant high-resolution Earth system data is increasingly relied upon across scientific, policy, and practitioner communities, there is an urgent need for coordinated and federated infrastructure to store, manage, standardize, and distribute decision-relevant community data products. Substantial effort is required to ensure that these products, which are often critical for regional impact assessments and decision-making, are findable, accessible, interoperable, and reusable. The Earth System Grid Federation US project (ESGF2-US) is addressing this challenge by expanding its open-source, distributed platform to support the hosting and dissemination of downscaled Earth system datasets. This expansion includes aligning new downscaled datasets with developing community standards for metadata and file structure, consistent with existing ESGF archives. This includes ensuring CF-compliance, applying CMORization where appropriate, and developing tools to streamline user access. In this paper, we highlight the technical and coordination work required to bring downscaled data into ESGF2-US and aim to inform the broader Earth system data user community about the growing availability and utility of these curated resources.

ESGF↗
DOE OSTI2021

Three founding ancestral genomes involved in the origin of sugarcane

Modern sugarcane cultivars (Saccharum spp.) are high polyploids, aneuploids (2n = ~12 = ~120) derived from interspecific hybridizations between the domesticated sweet species Saccharum officinarum and the wild species S. spontaneum. To analyse the architecture and origin of such a complex genome, we analysed the sequences of all 12 hom(oe)ologous haplotypes (BAC clones) from two distinct genomic regions of a typical modern cultivar, as well as the corresponding sequence in Miscanthus sinense and Sorghum bicolor, and monitored their distribution among representatives of the Saccharum genus. The diversity observed among haplotypes suggested the existence of three founding genomes (A, B, C) in modern cultivars, which diverged between 0.8 and 1.3 Mya. Two genomes (A, B) were contributed by S. officinarum; these were also found in its wild presumed ancestor S. robustum, and one genome (C) was contributed by S. spontaneum. These results suggest that S. officinarum and S. robustum are derived from interspecific hybridization between two unknown ancestors (A and B genomes). The A genome contributed most haplotypes (nine or ten) while the B and C genomes contributed one or two haplotypes in the regions analysed of this typical modern cultivar. Interspecific hybridizations likely involved accessions or gametes with distinct ploidy levels and/or were followed by a series of backcrosses with the A genome. The three founding genomes were found in all S. barberi, S. sinense and modern cultivars analysed. None of the analysed accessions contained only the A genome or the B genome, suggesting that representatives of these founding genomes remain to be discovered. This evolutionary model, which combines interspecificity and high polyploidy, can explain the variable chromosome pairing affinity observed in Saccharum. It represents a major revision of the understanding of Saccharum diversity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

EcoPLOT: dynamic analysis of biogeochemical data

Motivation: We have created EcoPLOT (parameterized linkage of omics-driven technologies), a web-app for the dynamic, interactive analysis of biogeochemical datasets that combines state-of-the-art analysis tools to statistically and graphically explore environmental, geochemical and microbiome datasets. Using the iterative random forest, a machine learning algorithm, EcoPLOT allows for the de novo discovery of drivers which exhibit significant impact on plant, microbial or soil dynamics. Availability and implementation: EcoPLOT is built entirely within the R language. It can be accessed through any system where R is installed, including Windows, Mac and most Linux systems. EcoPLOT is free to use and can be accessed at https://github.com/cdsanchez18/EcoPLOT.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

kb_DRAM: annotation and metabolic profiling of genomes with DRAM in KBase

Microbial genome annotation is the process of identifying structural and functional elements in DNA sequences and subsequently attaching biological information to those elements. DRAM is a tool developed to annotate bacterial, archaeal, and viral genomes derived from pure cultures or metagenomes. DRAM goes beyond traditional annotation tools by distilling multiple gene annotations to genome level summaries of functional potential. Despite these benefits, a downside of DRAM is the requirement of large computational resources, which limits its accessibility. Further, it did not integrate with downstream metabolic modeling tools that require genome annotation. To alleviate these constraints, DRAM and the viral counterpart, DRAM-v, are now available and integrated with the freely accessible KBase cyberinfrastructure. With kb_DRAM users can generate DRAM annotations and functional summaries from microbial or viral genomes in a point-and-click interface, as well as generate genome-scale metabolic models from DRAM annotations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Thermally unstable roosts influence winter torpor patterns in a threatened bat species

Abstract Many hibernating bats in thermally stable, subterranean roosts have experienced precipitous declines from white-nose syndrome (WNS). However, some WNS-affected species also use thermally unstable roosts during winter that may impact their torpor patterns and WNS susceptibility. From November to March 2017–19, we used temperature-sensitive transmitters to document winter torpor patterns of tricolored bats (Perimyotis subflavus) using thermally unstable roosts in the upper Coastal Plain of South Carolina. Daily mean roost temperature was 12.9 ± 4.9°C SD in bridges and 11.0 ± 4.6°C in accessible cavities with daily fluctuations of 4.8 ± 2°C in bridges and 4.0 ± 1.9°C in accessible cavities and maximum fluctuations of 13.8 and 10.5°C, respectively. Mean torpor bout duration was 2.7 ± 2.8 days and was negatively related to ambient temperature and positively related to precipitation. Bats maintained non-random arousal patterns focused near dusk and were active on 33.6% of tracked days. Fifty-one percent of arousals contained passive rewarming. Normothermic bout duration, general activity and activity away from the roost were positively related to ambient temperature, and activity away from the roost was negatively related to barometric pressure. Our results suggest ambient weather conditions influence winter torpor patterns of tricolored bats using thermally unstable roosts. Short torpor bout durations and potential nighttime foraging during winter by tricolored bats in thermally unstable roosts contrasts with behaviors of tricolored bats in thermally stable roosts. Therefore, tricolored bat using thermally unstable roosts may be less susceptible to WNS. More broadly, these results highlight the importance of understanding the effect of roost thermal stability on winter torpor patterns and the physiological flexibility of broadly distributed hibernating species.

Biodiversity & Conservation↗
DOE OSTI2020

CamRegBase: a gene regulation database for the biofuel crop, Camelina sativa

Abstract Camelina is an annual oilseed plant from the Brassicaceae family that is gaining momentum as a biofuel winter cover crop. However, a significant limitation in further enhancing its utility as a producer of oils that can be used as biofuels, jet fuels or bio-based products is the absence of a repository for all the gene expression and regulatory information that is being rapidly generated by the community. Here, we provide CamRegBase (https://camregbase.org/) as a one-stop resource to access Camelina information on gene expression and co-expression, transcription factors, lipid associated genes and genome-wide orthologs in the close-relative reference plant Arabidopsis. We envision this as a resource of curated information for users, as well as a repository of new gene regulation information.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Physiological Adaptations to Progressive Endurance Exercise Training in Adult and Aged Rats: Insights from the Molecular Transducers of Physical Activity Consortium (MoTrPAC)

While regular physical activity is a cornerstone of health, wellness, and vitality, the impact of endurance exercise training on molecular signaling within and across tissues remains to be delineated. The Molecular Transducers of Physical Activity Consortium (MoTrPAC) was established to characterize molecular networks underlying the adaptive response to exercise. Here, we describe the endurance exercise training studies undertaken by the Preclinical Animal Sites Studies component of MoTrPAC, in which we sought to develop and implement a standardized endurance exercise protocol in a large cohort of rats. To this end, Adult (6-mo) and Aged (18-mo) female (n = 151) and male (n = 143) Fischer 344 rats were subjected to progressive treadmill training (5 d/wk, ~70%–75% VO 2 max) for 1, 2, 4, or 8 wk; sedentary rats were studied as the control group. A total of 18 solid tissues, as well as blood, plasma, and feces, were collected to establish a publicly accessible biorepository and for extensive omics-based analyses by MoTrPAC. Treadmill training was highly effective, with robust improvements in skeletal muscle citrate synthase activity in as little as 1–2 wk and improvements in maximum run speed and maximal oxygen uptake by 4–8 wk. For body mass and composition, notable age- and sex-dependent responses were observed. This work in mature, treadmill-trained rats represents the most comprehensive and publicly accessible tissue biorepository, to date, and provides an unprecedented resource for studying temporal-, sex-, and age-specific responses to endurance exercise training in a preclinical rat model.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Identification of genetic and environmental factors influencing aerial root traits that support biological nitrogen fixation in sorghum

Abstract Plant breeding and genetics play a major role in the adaptation of plants to meet human needs. The current requirement to make agriculture more sustainable can be partly met by a greater reliance on biological nitrogen fixation by symbiotic diazotrophic microorganisms that provide crop plants with ammonium. Select accessions of the cereal crop sorghum (Sorghum bicolor (L.) Moench) form mucilage-producing aerial roots that harbor nitrogen-fixing bacteria. Breeding programs aimed at developing sorghum varieties that support diazotrophs will benefit from a detailed understanding of the genetic and environmental factors contributing to aerial root formation. A genome-wide association study of the sorghum minicore, a collection of 242 landraces, and 30 accessions from the sorghum association panel was conducted in Florida and Wisconsin and under 2 fertilizer treatments to identify loci associated with the number of nodes with aerial roots and aerial root diameter. Sequence variation in genes encoding transcription factors that control phytohormone signaling and root system architecture showed significant associations with these traits. In addition, the location had a significant effect on the phenotypes. Concurrently, we developed F2 populations from crosses between bioenergy sorghums and a landrace that produced extensive aerial roots to evaluate the mode of inheritance of the loci identified by the genome-wide association study. Furthermore, the mucilage collected from aerial roots contained polysaccharides rich in galactose, arabinose, and fucose, whose composition displayed minimal variation among 10 genotypes and 2 fertilizer treatments. These combined results support the development of sorghums with the ability to acquire nitrogen via biological nitrogen fixation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

MINE: maximally informative next experiment—toward a new GWAS experimental design and methodology

Abstract The computational methodology of Genome Wide Association Studies (GWAS) currently has several limitations: (i) the number of observations (rows) on a quantitative trait tends to be smaller than the number of single nucleotide polymorphisms (SNPs) (columns) in the design matrix; (ii) each SNP is usually modeled separately, failing to acknowledge interaction between each other (ie epistasis); (iii) there is implicit linkage disequilibrium (LD) between neighboring SNPs due to their linkage. To overcome these issues, we developed a tool that uses ensemble methods to fit mixed linear models to GWAS data, and these ensemble methods include the development of a new experimental design approach in GWAS, which uses the resultant models and data to select the next informative experiment over time. This new adaptive and staged approach for GWAS experimental design was developed and tested in a 3 yr adaptive model-guided discovery experiment against a fixed classical design. In Sorghum bicolor a total of 79, 86, and 78 accessions were tested in years 1, 2, and 3, respectively out of 343 accessions available in the Bioenergy Association Panel (BAP) each identified for 232,303 SNPs, 1 every 2–3 kb in the genomes. We demonstrated the feasibility of MINE enacted with 8 people in the field per year over 3 yr vs in 1 large classical design enacted with 20 people in 1 yr. The MINE results for chromosomal regions identified controlling dry weight were confirmed against results from previous sorghum GWAS experiments and 1 large classical design for the BAP panel.

Genetics & Heredity↗
DOE OSTI2022

Multiple origins, one evolutionary trajectory: gradual evolution characterizes distinct lineages of allotetraploid Brachypodium

The “genomic shock” hypothesis posits that unusual challenges to genome integrity such as whole genome duplication may induce chaotic genome restructuring. Decades of research on polyploid genomes have revealed that this is often, but not always the case. While some polyploids show major chromosomal rearrangements and derepression of transposable elements in the immediate aftermath of whole genome duplication, others do not. Nonetheless, all polyploids show gradual diploidization over evolutionary time. To evaluate these hypotheses, we produced a chromosome-scale reference genome for the natural allotetraploid grass Brachypodium hybridum, accession “Bhyb26.” We compared 2 independently derived accessions of B. hybridum and their deeply diverged diploid progenitor species Brachypodium stacei and Brachypodium distachyon. The 2 B. hybridum lineages provide a natural timecourse in genome evolution because one formed 1.4 million years ago, and the other formed 140 thousand years ago. The genome of the older lineage reveals signs of gradual post-whole genome duplication genome evolution including minor gene loss and genome rearrangement that are missing from the younger lineage. In neither B. hybridum lineage do we find signs of homeologous recombination or pronounced transposable element activation, though we find evidence supporting steady post-whole genome duplication transposable element activity in the older lineage. Gene loss in the older lineage was slightly biased toward 1 subgenome, but genome dominance was not observed at the transcriptomic level. We propose that relaxed selection, rather than an abrupt genomic shock, drives evolutionary novelty in B. hybridum, and that the progenitor species’ similarity in transposable element load may account for the subtlety of the observed genome dominance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

LinkML: an open data modeling framework

Background Scientific research relies on well-structured, standardized data; however, much of it is stored in formats such as free-text lab notebooks, nonstandardized spreadsheets, or data repositories. This lack of structure challenges interoperability, making data integration, validation, and reuse difficult. Findings LinkML (Linked Data Modeling Language) is an open framework that simplifies the process of authoring, validating, and sharing data. LinkML can describe a range of data structures, from flat, list-based models to complex, interrelated, and normalized models that utilize polymorphism and compound inheritance. It offers an approachable syntax that is not tied to any one technical architecture and can be integrated seamlessly with many existing frameworks. The LinkML syntax provides a standard way to describe schemas, classes, and relationships, allowing modelers to build well-defined, stable, and optionally ontology-aligned data structures. Once defined, LinkML schemas may be imported into other LinkML schemas. These key features make LinkML an accessible platform for interdisciplinary collaboration and a reliable way to define and share data semantics. Conclusions LinkML helps reduce heterogeneity, complexity, and the proliferation of single-use data models while simultaneously enabling compliance with FAIR (Findable, Accessible, Interoperable, and Reusable) data standards. LinkML has seen increasing adoption in various fields, including biology, chemistry, biomedicine, microbiome research, finance, electrical engineering, transportation, and commercial software development. In short, LinkML makes implicit models explicitly computable and allows data to be standardized at their origin. LinkML documentation and code are available at https://linkml.io/.

AI-ready data↗
DOE OSTI2021

Winter roosting ecology of tricolored bats ( Perimyotis subflavus ) in trees and bridges

Abstract Tricolored bats (Perimyotis subflavus) that roost in subterranean hibernacula have experienced precipitous declines from white-nose syndrome (WNS); however, understudied populations also use during winter non-subterranean roosts such as tree cavities, bridges, and foliage. Our objectives were to determine winter roost use by tricolored bats in an area devoid of subterranean roosts, determine roost microclimates to relate them to growth requirements of the fungal causal agent of WNS, and determine habitat factors influencing winter tree selection. From November to March 2017–2019, we used radiotelemetry to track 15 bats to their day roosts in the upper Coastal Plain of South Carolina and recorded microclimates in accessible tree cavities and bridges. We also characterized habitat and tree characteristics of 24 used trees and 153 random, available trees and used discrete choice models to determine selection. Roost structures included I-beam bridges, cavities in live trees, and foliage. Bridges were warmer and less humid than cavities. Roost temperatures often were amenable to fungal growth (< 19.5°C) but fluctuated widely depending on ambient temperatures. Bats used bridges on colder days (8.7°C ± 5.0 SD) and trees on warmer days (11.3°C ± 5.4). Bats selected low-decay trees closer to streams in areas with high canopy closure and cavity abundance. Bats also appeared to favor hardwood forests and avoid pine forests. Our results suggest that access to multiple roost microclimates might be important for tricolored bats during winter, and forest management practices that retain live trees near streams and foster cavity formation in hardwood forests likely will benefit this species. Our results also suggest tricolored bats using bridge and tree roosts might be less susceptible to WNS than bats using subterranean hibernaculum roosts. Thus, forests in areas without subterranean hibernacula in the southeastern United States that support bats during winter might represent important refugia from WNS for multiple species.

Zoology↗
DOE OSTI2021

Scaling pair count to next galaxy surveys

ABSTRACT Counting pairs of galaxies or stars according to their distance is at the core of real-space correlation analyses performed in astrophysics and cosmology. Upcoming galaxy surveys (LSST, Euclid) will measure properties of billions of galaxies challenging our ability to perform such counting in a minute-scale time relevant for the usage of simulations. The problem is only limited by efficient access to the data, hence belongs to the big data category. We use the popular Apache Spark framework to address it and design an efficient high-throughput algorithm to deal with hundreds of millions to billions of input data. To optimize it, we revisit the question of non-hierarchical sphere pixelization based on cube symmetries and develop a new one dubbed the ‘Similar Radius Sphere Pixelization’ (SARSPix) with very close to square pixels. It provides the most adapted indexing over the sphere for all distance-related computations. Using LSST-like fast simulations, we compute autocorrelation functions on tomographic bins containing between a hundred million to one billion data points. In each case, we achieve the construction of a standard pair-distance histogram in about 2 min, using a simple algorithm that is shown to scale, over a moderate number of nodes (16–64). This illustrates the potential of this new techniques in the field of astronomy where data access is becoming the main bottleneck. They can be easily adapted to other use-cases as nearest-neighbours search, catalogue cross-match or cluster finding. The software is publicly available from https://github.com/astrolabsoftware/SparkCorr.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

RCSB Protein Data Bank: powerful new tools for exploring 3D structures of biological macromolecules for basic and applied research and education in fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences

Abstract The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), the US data center for the global PDB archive and a founding member of the Worldwide Protein Data Bank partnership, serves tens of thousands of data depositors in the Americas and Oceania and makes 3D macromolecular structure data available at no charge and without restrictions to millions of RCSB.org users around the world, including >660 000 educators, students and members of the curious public using PDB101.RCSB.org. PDB data depositors include structural biologists using macromolecular crystallography, nuclear magnetic resonance spectroscopy, 3D electron microscopy and micro-electron diffraction. PDB data consumers accessing our web portals include researchers, educators and students studying fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences. During the past 2 years, the research-focused RCSB PDB web portal (RCSB.org) has undergone a complete redesign, enabling improved searching with full Boolean operator logic and more facile access to PDB data integrated with >40 external biodata resources. New features and resources are described in detail using examples that showcase recently released structures of SARS-CoV-2 proteins and host cell proteins relevant to understanding and addressing the COVID-19 global pandemic.

59 BASIC BIOLOGICAL SCIENCES↗