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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Electrochemical ammonia synthesis via nitrate reduction on Fe single atom catalyst

Electrochemically converting nitrate, a widespread water pollutant, back to valuable ammonia is a green and delocalized route for ammonia synthesis, and can be an appealing and supplementary alternative to the Haber-Bosch process. However, as there are other nitrate reduction pathways present, selectively guiding the reaction pathway towards ammonia is currently challenged by the lack of efficient catalysts. Here we report a selective and active nitrate reduction to ammonia on Fe single atom catalyst, with a maximal ammonia Faradaic efficiency of ~ 75% and a yield rate of up to ~ 20,000 μg h –1 mg cat. –1 (0.46 mmol h –1 cm –2 ). Our Fe single atom catalyst can effectively prevent the N-N coupling step required for N 2 due to the lack of neighboring metal sites, promoting ammonia product selectivity. Density functional theory calculations reveal the reaction mechanisms and the potential limiting steps for nitrate reduction on atomically dispersed Fe sites.

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

Structure of orthoreovirus RNA chaperone σNS, a component of viral replication factories

Abstract The mammalian orthoreovirus (reovirus) σNS protein is required for formation of replication compartments that support viral genome replication and capsid assembly. Despite its functional importance, a mechanistic understanding of σNS is lacking. We conducted structural and biochemical analyses of a σNS mutant that forms dimers instead of the higher-order oligomers formed by wildtype (WT) σNS. The crystal structure shows that dimers interact with each other using N-terminal arms to form a helical assembly resembling WT σNS filaments in complex with RNA observed using cryo-EM. The interior of the helical assembly is of appropriate diameter to bind RNA. The helical assembly is disrupted by bile acids, which bind to the same site as the N-terminal arm. This finding suggests that the N-terminal arm functions in conferring context-dependent oligomeric states of σNS, which is supported by the structure of σNS lacking an N-terminal arm. We further observed that σNS has RNA chaperone activity likely essential for presenting mRNA to the viral polymerase for genome replication. This activity is reduced by bile acids and abolished by N-terminal arm deletion, suggesting that the activity requires formation of σNS oligomers. Our studies provide structural and mechanistic insights into the function of σNS in reovirus replication.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Uncovering hidden enhancers through unbiased in vivo testing

Chromatin signatures are widely used to identify tissue-specific in vivo enhancers, but their sensitivity and specificity remains unclear. Here we show that many developmental enhancers remain undetectable using currently available chromatin data. In an initial comparison of over 1200 developmental enhancers with tissue-matched chromatin data, 14% (n = 285) lacked canonical enhancer-associated chromatin signatures. To further assess the prevalence of enhancers missed by chromatin profiling approaches, we used a high-throughput transgenic enhancer assay to screen the regulatory landscapes of two key developmental genes at 5 kb resolution, spanning 1.3 Mb of mouse sequence in total. We observed that 23 of 88 (26%) in vivo enhancers discovered by this approach lacked enhancer-associated chromatin signatures in the respective tissue. Our findings suggest the existence of tens of thousands of enhancers that remain undiscovered by currently available chromatin data, underscoring the continued need for expanding resources for enhancer discovery.

Epigenomics↗
DOE OSTI2024

JARVIS-Leaderboard: a large scale benchmark of materials design methods

Abstract Lack of rigorous reproducibility and validation are significant hurdles for scientific development across many fields. Materials science, in particular, encompasses a variety of experimental and theoretical approaches that require careful benchmarking. Leaderboard efforts have been developed previously to mitigate these issues. However, a comprehensive comparison and benchmarking on an integrated platform with multiple data modalities with perfect and defect materials data is still lacking. This work introduces JARVIS-Leaderboard, an open-source and community-driven platform that facilitates benchmarking and enhances reproducibility. The platform allows users to set up benchmarks with custom tasks and enables contributions in the form of dataset, code, and meta-data submissions. We cover the following materials design categories: Artificial Intelligence (AI), Electronic Structure (ES), Force-fields (FF), Quantum Computation (QC), and Experiments (EXP). For AI, we cover several types of input data, including atomic structures, atomistic images, spectra, and text. For ES, we consider multiple ES approaches, software packages, pseudopotentials, materials, and properties, comparing results to experiment. For FF, we compare multiple approaches for material property predictions. For QC, we benchmark Hamiltonian simulations using various quantum algorithms and circuits. Finally, for experiments, we use the inter-laboratory approach to establish benchmarks. There are 1281 contributions to 274 benchmarks using 152 methods with more than 8 million data points, and the leaderboard is continuously expanding. The JARVIS-Leaderboard is available at the website: https://pages.nist.gov/jarvis_leaderboard/

36 MATERIALS SCIENCE↗
DOE OSTI2020

Impacts of Climate Change on Energy Systems in Global and Regional Scenarios

A growing number of studies report the impact of climate change on the supply, demand, transport, and cost of energy. However, there is lack of comprehensive overview and understanding of climate change impacts on energy across technologies and scales. Here, we conduct a systematic assessment of results from 186 papers on potential impacts of climate change on energy. Results show that increased cooling demand and decreased heating demand is anticipated globally. Similarly, increases in bio-energy and hydro power and a possible decrease in thermal electricity supply is projected. Overall changes in heating and cooling demand, increased thermal cooling, and reduced hydropower supply in Europe, India and Latin America are projected 35 at the regional scale. Furthermore, our review revealed that studies use a wide range of inconsistent methods and data sources. To move forward, the study proposes a consistent multi-model assessment framework for a comprehensive understanding of climate impacts on energy.

Yalew, Seleshi G.↗
DOE OSTI2021

Understanding Co roles towards developing Co-free Ni-rich cathodes for rechargeable batteries

Reduction on cobalt reliance is an urgent requirement in the development of sustainable cathode materials for Li-ion batteries. Here the authors analyse the roles of cobalt and its interplay with other ions in high-nickel layered oxides, and deduce a material formula for promising cobalt-free cathodes. Current bottlenecks in cobalt (Co) supply have negatively impacted commercial battery production and inspired the development of cathode materials that are less reliant on Co. However, complete Co elimination is prevented by the lack of fundamental understanding of the impact of Co on cathode capacity and structural stability, as well as the lack of effective substitute components in practice. Here we investigate the roles of Co in purposely designed systems that include both Co-rich and Mn-substituted Co-free cathodes. Our results affirmed that Co plays an undeniable role in fast capacity and/or structural degradation, and found that Co is more destructive than Ni at high potentials, which offers unexpected but encouraging perspectives for Co reduction. Moreover, Mn substitution effectively alleviates the destructive effects of Co and enables a high potential functionality. Finally, with these fundamental discoveries, we demonstrated a series of LiNi α Mn β X γ O 2 (X = single or multiple dopants) as a promising candidate for Co-free cathodes.

25 ENERGY STORAGE↗
DOE OSTI2023

Genome expansion by a CRISPR trimmer-integrase

CRISPR–Cas adaptive immune systems capture DNA fragments from invading mobile genetic elements and integrate them into the host genome to provide a template for RNA-guided immunity. CRISPR systems maintain genome integrity and avoid autoimmunity by distinguishing between self and non-self, a process for which the CRISPR/Cas1–Cas2 integrase is necessary but not sufficient. In some microorganisms, the Cas4 endonuclease assists CRISPR adaptation, but many CRISPR–Cas systems lack Cas4. Here we show here that an elegant alternative pathway in a type I-E system uses an internal DnaQ-like exonuclease (DEDDh) to select and process DNA for integration using the protospacer adjacent motif (PAM). The natural Cas1–Cas2/exonuclease fusion (trimmer-integrase) catalyses coordinated DNA capture, trimming and integration. Five cryo-electron microscopy structures of the CRISPR trimmer-integrase, visualized both before and during DNA integration, show how asymmetric processing generates size-defined, PAM-containing substrates. Before genome integration, the PAM sequence is released by Cas1 and cleaved by the exonuclease, marking inserted DNA as self and preventing aberrant CRISPR targeting of the host. Together, these data support a model in which CRISPR systems lacking Cas4 use fused or recruited exonucleases for faithful acquisition of new CRISPR immune sequences.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Twisted-layer boron nitride ceramic with high deformability and strength

Moiré superlattices formed by twisted stacking in van der Waals materials have emerged as a new platform for exploring the physics of strongly correlated materials and other emergent phenomena. However, there remains a lack of research on the mechanical properties of twisted-layer van der Waals materials, owing to a lack of suitable strategies for making three-dimensional bulk materials. Here we report the successful synthesis of a polycrystalline boron nitride bulk ceramic with high room-temperature deformability and strength. This ceramic, synthesized from an onion-like boron nitride nanoprecursor with conventional spark plasma sintering and hot-pressing sintering, consists of interlocked laminated nanoplates in which parallel laminae are stacked with varying twist angles. The compressive strain of this bulk ceramic can reach 14% before fracture, about one order of magnitude higher compared with traditional ceramics (less than 1% in general), whereas the compressive strength is about six times that of ordinary hexagonal boron nitride layered ceramics. The exceptional mechanical properties are due to a combination of the elevated intrinsic deformability of the twisted layering in the nanoplates and the three-dimensional interlocked architecture that restricts deformation from propagating across individual nanoplates. The advent of this twisted-layer boron nitride bulk ceramic opens a gate to the fabrication of highly deformable bulk ceramics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A unified catalog of 204,938 reference genomes from the human gut microbiome

Comprehensive, high-quality reference genomes are required for functional characterization and taxonomic assignment of the human gut microbiota. We present the Unified Human Gastrointestinal Genome (UHGG) collection, comprising 204,938 nonredundant genomes from 4,644 gut prokaryotes. These genomes encode >170 million protein sequences, which we collated in the Unified Human Gastrointestinal Protein (UHGP) catalog. The UHGP more than doubles the number of gut proteins in comparison to those present in the Integrated Gene Catalog. More than 70% of the UHGG species lack cultured representatives, and 40% of the UHGP lack functional annotations. Intraspecies genomic variation analyses revealed a large reservoir of accessory genes and single-nucleotide variants, many of which are specific to individual human populations. The UHGG and UHGP collections will enable studies linking genotypes to phenotypes in the human gut microbiome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Monthly hydropower generation data for Western Canada to support Western-US interconnect power system studies

Hydroelectric power generation in Western Canada significantly contributes to power grid operations of the North American Western Interconnection through substantial generation, some of which is exported to the United States (U.S.). However, the lack of publicly available hydropower generation datasets poses challenges for future market projections and resource adequacy evaluations. We present a simulation-based monthly power system model-ready hydropower generation dataset for 110 facilities in British Columbia and Alberta from 1981 to 2019. These monthly hydropower generation estimates are developed from integrated hydrologic model simulations of runoff and reservoir-operated streamflow, followed by scaling that considers diversion inflow constraints based on hydropower water license information. To address the lack of comparable hydropower generation records, we conduct step-by-step evaluations for simulated runoff, regulated streamflow, and hydropower generation using available observations or estimates. The presented hydropower dataset aims to enhance the representation of hydropower resources in Western Canada, supporting power grid system studies for the Western Interconnection of the U.S. and Canada.

13 HYDRO ENERGY↗
DOE OSTI2021

A machine-learning inverse model framework for rapid forecasting and history matching in unconventional reservoirs

Model-based optimization for real-time forecasting in unconventional reser-voirs requires novel methods and work?ows since the strategies and work?ows used in conventional reservoirs are either inapplicable, or prohibitively expen-sive and time-consuming. Insu?cient site data and computational expense of high-?delity simulations mean that work?ows with high-?delity simulations are not ideal for usage in comprehensive uncertainty quanti?cation stud-ies that require 1000s of forward model runs. We present an alternative, novel work?ow for unconventional reservoirs, based on the interplay between reduced-order models and machine-learning. Our physics-informed machine-learning (PIML) work?ow addresses the challenges to real-time reservoir management in uncoventionals, namely lack of data (the time-frame for which the wells have been producing), and computational expense of high-?delity modeling. We use the machine-learning paradigm of transfer-learning to bind together fast but less accurate reduced-order models with slow, but accurate high-?delity models and circumvent the di?culties inherent in the current state-of-the-art for unconventionals. Such a PIML work?ow, grounded in physics, is a viable candidate for real-time history matching and production forecasting in a fractured shale gas reservoir. The signi?cance of our approach is that while it is developed for a particu-lar well and site in the Marcelus Shale gas reservoir of the Appalachian basin (MSEEL), it is not wedded to it. We expect the same work?ow can be ap-plied to other shale formations (e.g., Woodford, Barnett, Utica, EagleFord) should site-data become available, using the same set of machine-learning techniques from transfer learning. Some ?ne-tuning (or minimal retraining of the neural networks) will be required to transfer knowledge across shale gas sites/formations but it is a clearly superior alternative to developing a new machine-learning model altogether when considering a di?erent site.

Srinivasan, Shriram↗
DOE OSTI2021

n-Butanol production by Rhodopseudomonas palustris TIE-1

Anthropogenic carbon dioxide (CO 2 ) release in the atmosphere from fossil fuel combustion has inspired scientists to study CO 2 to biofuel conversion. Oxygenic phototrophs such as cyanobacteria have been used to produce biofuels using CO 2 . However, oxygen generation during oxygenic photosynthesis adversely affects biofuel production efficiency. To produce n-butanol (biofuel) from CO 2 , here we introduce an n-butanol biosynthesis pathway into an anoxygenic (non-oxygen evolving) photoautotroph, Rhodopseudomonas palustris TIE-1 (TIE-1). Using different carbon, nitrogen, and electron sources, we achieve n-butanol production in wild-type TIE-1 and mutants lacking electron-consuming (nitrogen-fixing) or acetyl-CoA-consuming (polyhydroxybutyrate and glycogen synthesis) pathways. The mutant lacking the nitrogen-fixing pathway produce the highest n-butanol. Coupled with novel hybrid bioelectrochemical platforms, this mutant produces n-butanol using CO 2 , solar panel-generated electricity, and light with high electrical energy conversion efficiency. Overall, this approach showcases TIE-1 as an attractive microbial chassis for carbon-neutral n-butanol bioproduction using sustainable, renewable, and abundant resources.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

CryoTRANS: predicting high-resolution maps of rare conformations from self-supervised trajectories in cryo-EM

Cryogenic electron microscopy (cryo-EM) has revolutionized structural biology, enabling efficient determination of structures at near-atomic resolutions. However, a common challenge arises from the severe imbalance among various conformations of vitrified particles, leading to low-resolution reconstructions in rare conformations due to a lack of particle images in these quasi-stable states. We introduce CryoTRANS, a method that predicts high-resolution maps of rare conformations by constructing a self-supervised pseudo-trajectory between density maps of varying resolutions. This trajectory is represented by an ordinary differential equation parameterized by a deep neural network, ensuring retention of detailed structures from high-resolution density maps. By leveraging a single high-resolution density map, CryoTRANS significantly improves the reconstruction of rare conformations and has been validated on four real-world datasets: alpha-2-macroglobulin, actin-binding protein complexes, SARS-CoV-2 spike glycoprotein, and the 70S ribosome. CryoTRANS can also predict high-resolution structures in cryogenic electron tomography maps using a high-resolution cryo-EM map.Cryogenic electron microscopy (cryo-EM) has revolutionized structural biology, enabling efficient determination of structures at near-atomic resolutions. However, a common challenge arises from the severe imbalance among various conformations of vitrified particles, leading to low-resolution reconstructions in rare conformations due to a lack of particle images in these quasi-stable states. We introduce CryoTRANS, a method that predicts high-resolution maps of rare conformations by constructing a self-supervised pseudo-trajectory between density maps of varying resolutions. This trajectory is represented by an ordinary differential equation parameterized by a deep neural network, ensuring retention of detailed structures from high-resolution density maps. By leveraging a single high-resolution density map, CryoTRANS significantly improves the reconstruction of rare conformations and has been validated on four real-world datasets: alpha-2-macroglobulin, actin-binding protein complexes, SARS-CoV-2 spike glycoprotein, and the 70S ribosome. CryoTRANS can also predict high-resolution structures in cryogenic electron tomography maps using a high-resolution cryo-EM map.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Mycobacterium tuberculosis CitA activity is modulated by cysteine oxidation and pyruvate binding

As an adaptation for survival during infection, Mycobacterium tuberculosis becomes dormant, reducing its metabolism and growth. Two types of citrate synthases have been identified in Mycobacterium tuberculosis, GltA2 and CitA. Previous work shows that overexpression of CitA, the secondary citrate synthase, stimulates the growth of Mycobacterium tuberculosis under hypoxic conditions without showing accumulation of triacylglycerols and makes mycobacteria more sensitive to antibiotics, suggesting that CitA may play a role as a metabolic switch during infection and may be an interesting TB drug target. To assess the druggability and possible mechanisms of targeting CitA with small-molecule compounds, the CitA crystal structure was solved to 2.1 Å by X-ray crystallography. The solved structure shows that CitA lacks an NADH binding site that would afford allosteric regulation, which is atypical of most citrate synthases. However, a pyruvate molecule is observed within the analogous domain, suggesting pyruvate may instead be the allosteric regulator for CitA. Further, the R149 and R153 residues forming the charged portion of the pyruvate binding pocket were mutated to glutamate and methionine, respectively, to assess the effect of mutations on activity. Protein thermal shift assay shows thermal stabilization of CitA in the presence of pyruvate compared to the two CitA variants designed to decrease pyruvate affinity. Solved crystal structures of both variants show no significant structural changes. However, the catalytic efficiency of the R153M variant increases by 2.6-fold. Additionally, we show that covalent modification of C143 of CitA by Ebselen completely arrests enzyme activity. Similar inhibition is observed using two spirocyclic Michael acceptor containing compounds, which inhibit CitA with IC app 50 values of 6.6 and 10.9 μM. A crystal structure of CitA modified by Ebselen was solved, but significant structural changes were lacking. Considering that covalent modification of C143 inactivates CitA and the proximity of C143 to the pyruvate binding site, this suggests that structural and/or chemical changes in this sub-domain are responsible for regulating CitA enzymatic activity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Open-source generation of sigma profiles: impact of quantum chemistry and solvation treatment on machine learning performance

The combination of machine learning (ML) models with chemistry-related tasks requires the description of molecular structures in a machine-readable way. The nature of these so-called molecular descriptors has a direct and major impact on the performance of ML models and remains an open problem in the field. Structural descriptors like SMILES strings or molecular graphs lack size-independence and can be memory intensive. Machine-learned descriptors can be of low dimensionality and constant size but lack physical significance and human interpretability. Sigma profiles, which are unnormalized histograms of the surface charge distributions of solvated molecules, combine physical significance with low dimensionality and size-independence, making them a suitable candidate for a universal molecular descriptor. However, their widespread adoption in ML applications requires open access to sigma profile generation, which is currently not available. This work details the development of OpenSPGen – an open-source tool for generating sigma profiles. Also presented are studies on the effect of different settings on the efficacy of the generated sigma profiles at predicting thermophysical material properties when used as inputs to a Gaussian process as a simple surrogate ML model. We find that a higher level of theory does not translate to more accurate results. We also provide further recommendations for sigma profile calculation and use in ML models.

Salih, Fathya Y. M. [University of Notre Dame, IN ↗
DOE OSTI2021

Conservation of endo -glucanase 16 (EG16) activity across highly divergent plant lineages

Plant cell walls are highly dynamic structures that are composed predominately of polysaccharides. As such, endogenous carbohydrate active enzymes (CAZymes) are central to the synthesis and subsequent modification of plant cells during morphogenesis. The endo-glucanase 16 (EG16) members constitute a distinct group of plant CAZymes, angiosperm orthologs of which were recently shown to have dual β-glucan/xyloglucan hydrolase activity. Molecular phylogeny indicates that EG16 members comprise a sister clade with a deep evolutionary relationship to the widely studied apoplastic xyloglucan endo-transglycosylases/hydrolases (XTH). A cross-genome survey indicated that EG16 members occur as a single ortholog across species and are widespread in early diverging plants, including the non-vascular bryophytes, for which functional data were previously lacking. Remarkably, enzymological characterization of an EG16 ortholog from the model moss Physcomitrella patens (PpEG16) revealed that EG16 activity and sequence/structure are highly conserved across 500 million years of plant evolution, vis-à-vis orthologs from grapevine and poplar. Ex vivo biomechanical assays demonstrated that the application of EG16 gene products caused abrupt breakage of etiolated hypocotyls rather than slow extension, thereby indicating a mode-of-action distinct from endogenous expansins and microbial endo-glucanases. As a result, the biochemical data presented here will inform future genomic, genetic, and physiological studies of EG16 enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Issues in Bi-Directional Interoperability between BIM and BEM

The state-of-the-art interoperability between Building Information Modeling (BIM) and Building Energy Modeling (BEM) is mainly one-way. BEM software like EnergyPlus takes design input from BIM and simulates the energy consumption of the building. BIM, however, is unable to leverage energy simulation results from BEM smoothly. This lack of bi-directional interoperability between BIM and BEM prevents buildings from seeking more energy-efficient design options and limits BIM applications in optimal generative design. In this research, the authors have conducted the following activities related to two-way interoperability between BIM and BEM: (1) surveyed its current status through literature review, (2) investigated barriers to the bi-directional interoperability, and (3) suggested possible approaches to enable bi-directional interoperability and research outlook in the field. As a result, the authors have identified three main barriers to BIM BEM interoperability, namely, inefficient collaboration, limited scope in information transformation, and lack of BEM to BIM transformation. Future directions are suggested to address these barriers.

building design↗
DOE OSTI2025

Life Cycle Cost Analysis of Prestressed Concrete Poles Subjected to Wind, Surges, and Waves

Prestressed concrete (PC) poles are becoming popular choices to support coastal power transmission systems. However, the existing literature does not offer a detailed analysis of the effectiveness of PC poles in terms of long-term vulnerabilities and the direct and indirect costs. This is due to (1) lack of fragility models for PC poles and (2) lack of probabilistic wind, storm surge, and wave models in coastal settings. In this study, we address these gaps through a series of Monte Carlo simulations to estimate fragility of PC poles as a function of age and hazard (wind, surges, and waves) intensity, and the development of a probabilistic hazard model based on 10,000 years of synthetic tropical cyclone data. The probabilistic hazard model is used in conjunction with high-resolution hydrodynamic models to generate realizations of coastal wind, storm surges, and waves for the Louisiana and Mississippi coasts. A comprehensive life cycle cost analysis for a service life of 70 years considering direct and indirect losses is conducted to compare the performance of a transmission line located in Pascagoula, Mississippi, when wood poles are replaced by PC poles. Results showed that aging has a minor effect on the reliability of PC poles, highlighting the advantages of replacing wood poles with PC poles, especially in coastal areas. In addition, PC poles are significantly more cost-effective compared with wood poles over their life cycle, leading to an estimated saving of $11.55 million (68.17% reduction). The results of this study provide key insight to inform decision-making processes to keep the coastal power grids resilient and cost-effective against future storm hazards.

natural disasters↗