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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Plasma modification through boron particulate injection in the full tungsten environment of WEST

Recent experiments have confirmed the compatibility of extended boron particulate injections with high performance plasma discharges in the full tungsten (W) environment of WEST. Utilizing an impurity powder dropper (IPD) equipped with boron (B) powders a series of extended experimental programs providing controlled injections have quantified plasma response to varying levels of injection rate and total injection quantity. Calibration of injection quantities confirmed through post-situ testing of the IPD and cross-correlated with both high-speed camera illumination and spectroscopic measurement have allowed for the first time a fine scale determination of the effects of powder introduction on plasma performance. Plasma enhancement, consistent with turbulence reduction through profile modification, has been observed with sustained increases in the stored energy (WMHD), by 18%, electron temperature (T e ) by 35%, and neutron rate (N n ) by up to 200%, all of which scale positively with increasing powder injection rates. These injections have also resulted in both prompt and extended reductions in native impurity content, decreases in post injection radiated power, and strong decreases in divertor deuterium signatures signifying a reduction in recycling suggesting enhanced boron layer formation which provides a reduction of source terms and leads to enhanced gettering of main ion and impurity sources.

Lunsford, R. [Princeton Plasma Physics Laboratory ↗
DOE OSTI2021

Salt Stress Induces Paramylon Accumulation and Fine-Tuning of the Macro-Organization of Thylakoid Membranes in Euglena gracilis Cells

The effects of salt stress condition on the growth, morphology, photosynthetic performance, and paramylon content were examined in the mixotrophic, unicellular, flagellate Euglena gracilis. We found that salt stress negatively influenced cell growth, accompanied by a decrease in chlorophyll (Chl) content. Circular dichroism (CD) spectroscopy revealed the changes in the macro-organization of pigment-protein complexes due to salt treatment, while the small-angle neutron scattering (SANS) investigations suggested a reduction in the thylakoid stacking, an effect confirmed by the transmission electron microscopy (TEM). At the same time, the analysis of the thylakoid membrane complexes using native-polyacrylamide gel electrophoresis (PAGE) revealed no significant change in the composition of supercomplexes of the photosynthetic apparatus. Salt stress did not substantially affect the photosynthetic activity, as reflected by the fact that Chl fluorescence yield, electron transport rate (ETR), and energy transfer between the photosystems did not change considerably in the salt-grown cells. We have observed notable increases in the carotenoid-to-Chl ratio and the accumulation of paramylon in the salt-treated cells. We propose that the accumulation of storage polysaccharides and changes in the pigment composition and thylakoid membrane organization help the adaptation of E. gracilis cells to salt stress and contribute to the maintenance of cellular processes under stress conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Small angle neutron scattering and lipidomic analysis of a native, trimeric PSI-SMALP from a thermophilic cyanobacteria

The use of styrene-maleic acid copolymers (SMAs) to produce membrane protein-containing nanodiscs without the initial detergent isolation has gained significant interest over the last decade. We have previously shown that a Photosystem I SMALP from the thermophilic cyanobacterium, Thermosynechococcus elongatus (PSI-SMALP), has much more rapid energy transfer and charge separation in vitro than detergent isolated PSI complexes. In this study, we have utilized small-angle neutron scattering (SANS) to better understand the geometry of these SMALPs. These techniques allow us to investigate the size and shape of these particles in their fully solvated state. Further, the particle's proteolipid core and detergent shell or copolymer belt can be interrogated separately using contrast variation, a capability unique to SANS. Here we report the dimensions of the Thermosynechococcus elongatus PSI-SMALP containing a PSI trimer. At ~1.5 MDa, PSI-SMALP is the largest SMALP to be isolated; our lipidomic analysis indicates it contains ~1300 lipids/per trimeric particle, >40-fold more than the PSI-DDM particle and > 100 fold more than identified in the 1JB0 crystal structure. Interestingly, the lipid composition to the PSI trimer in the PSI-SMALP differs significantly from bulk thylakoid composition, being enriched ~50 % in the anionic sulfolipid, SQDG. Finally, utilizing the contrast match point for the SMA 1440 copolymer, we also can observe the ~1 nm SMA copolymer belt surrounding this SMALP for the first time, consistent with most models of SMA organization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Protein sequence design with a learned potential

The task of protein sequence design is central to nearly all rational protein engineering problems, and enormous effort has gone into the development of energy functions to guide design. Here, we investigate the capability of a deep neural network model to automate design of sequences onto protein backbones, having learned directly from crystal structure data and without any human-specified priors. The model generalizes to native topologies not seen during training, producing experimentally stable designs. We evaluate the generalizability of our method to a de novo TIM-barrel scaffold. The model produces novel sequences, and high-resolution crystal structures of two designs show excellent agreement with in silico models. Our findings demonstrate the tractability of an entirely learned method for protein sequence design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Community-Scale Solar Deployment in the Northwest Arctic

NANA Regional Corporation (NRC, or NANA) was formed as an Alaska Native Corporation (ANC) pursuant to the Alaska Native Claims Settlement Act of 1971. Our lands cover 39,000 square miles of the Northwest Arctic region of Alaska. We partner closely with the Northwest Arctic Borough (NAB) and our 11 remote communities on numerous projects and activities, especially around clean energy initiatives that improve quality of life and help to reduce extremely high energy costs experienced by the communities in our region. Collectively, the regional partnership has developed numerous successful solar, wind, biomass, and energy storage, distribution upgrade, and efficiency projects. To further progress, we created the Northwest Arctic Energy Steering Committee to share and replicate these benefits across the region. NANA’s mission is to provide economic opportunities for our more than 13,500 Iñupiat shareholders and to protect and enhance NANA lands.

14 SOLAR ENERGY↗
DOE OSTI2022

Community-Scale AHA Go Solar Initiative and Net Zero Initiative

The Saint Regis Mohawk Tribe is a sovereign, federally acknowledged Indian Tribe. The Tribal Council created the Akwesasne Housing Authority (AHA) by ordinance in July 1984 and has designated the AHA as its agency for purposes of administering the Tribe’s Indian Housing Block Grant under the Native American Housing and Self-Determination Act of 1996. The Go Solar project will install approximately 615 kilowatts (kW) of solar photovoltaic (PV) facilities to serve housing related buildings on the Tribe’s reservation and use net metering programs to reduce the energy costs for AHA and Tribal members by up to $\$$4,417,501 over the life of the project. AHA will initiate four (4) net zero buildings: two (2) new net zero low-income housing buildings located at Sunrise Acres III, which include the Veterans Supportive Housing Building and the Seniors Supportive Housing building, and one (1) older, existing net zero building used by the Akwesasne Boys & Girls Club (ABGC Building), and (1) Tribal Administration Building.

14 SOLAR ENERGY↗
DOE OSTI2021

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells - increasing or decreasing the fluid flow rates across the wells - and drilling new wells at appropriate locations. The latter is expensive, time-consuming, and subject to many engineering constraints, but the former is a viable mechanism for periodic adjustment of the available fluid allocations. Data and supporting literature from a study describing a new approach combining reservoir modeling and machine learning to produce models that enable strategies for the mitigation of decreased heat and power production rates over time for geothermal power plants. The computational approach used enables translation of sets of potential flow rates for the active wells into reservoir-wide estimates of produced energy and discovery of optimal flow allocations among the studied sets. In our computational experiments, we utilize collections of simulations for a specific reservoir (which capture subsurface characterization and realize history matching) along with machine learning models that predict temperature and pressure timeseries for production wells. We evaluate this approach using an "open-source" reservoir we have constructed that captures many of the characteristics of Brady Hot Springs, a commercially operational geothermal field in Nevada, USA. Selected results from a reservoir model of Brady Hot Springs itself are presented to show successful application to an existing system. In both cases, energy predictions prove to be highly accurate: all observed prediction errors do not exceed 3.68% for temperatures and 4.75% for pressures. In a cumulative energy estimation, we observe prediction errors that are less than 4.04%. A typical reservoir simulation for Brady Hot Springs completes in approximately 4 hours, whereas our machine learning models yield accurate 20-year predictions for temperatures, pressures, and produced energy in 0.9 seconds. This paper aims to demonstrate how the models and techniques from our study can be applied to achieve rapid exploration of controlled parameters and optimization of other geothermal reservoirs. Includes a synthetic, yet realistic, model of a geothermal reservoir, referred to as open-source reservoir (OSR). OSR is a 10-well (4 injection wells and 6 production wells) system that resembles Brady Hot Springs (a commercially operational geothermal field in Nevada, USA) at a high level but has a number of sufficiently modified characteristics (which renders any possible similarity between specific characteristics like temperatures and pressures as purely random). We study OSR through CMG simulations with a wide range of flow allocation scenarios. Includes a dataset with 101 simulated scenarios that cover the period of time between 2020 and 2040 and a link to the published paper about this project, where we focus on the Machine Learning work for predicting OSR's energy production based on the simulation data, as well as a link to the GitHub repository where we have published the code we have developed (please refer to the repository's readme file to see instructions on how to run the code). Additional links are included to associated work led by the USGS to identify geologic factors associated with well productivity in geothermal fields. Below are the high-level steps for applying the same modeling + ML process to other geothermal reservoirs: 1. Develop a geologic model of the geothermal field. The location of faults, upflow zones, aquifers, etc. need to be accounted for as accurately as possible 2. The geologic model needs to be converted to a reservoir model that can be used in a reservoir simulator, such as, for instance, CMG STARS, TETRAD, or FALCON 3. Using native state modeling, the initial temperature and pressure distributions are evaluated, and they become the initial conditions for dynamic reservoir simulations 4....

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Molecular mechanism of secreted amyloid-β precursor protein in binding and modulating GABABR1a

A recent phenomenal study discovered that the extension domain of secreted amyloid-β precursor protein (sAPP) can bind to the intrinsically disordered sushi 1 domain of the γ-aminobutyric acid type B receptor subunit 1a (GABA B R1a) and modulate its synaptic transmission. The work provided an important structural foundation for the modulation of GABA B R1a; however, the detailed molecular interaction mechanism, crucial for future drug design, remains elusive. Here, we further investigated the dynamical interactions between sAPP peptides and the natively unstructured sushi 1 domain using all-atom molecular dynamics simulations, for both the 17-residue sAPP peptide (APP 17-mer) and its minimally active 9 residue segment (APP 9-mer). We then explored mutations of the APP 9-mer with rigorous free energy perturbation (FEP) calculations. Our in silico mutagenesis studies revealed key residues (D4, W6, and W7) responsible for the binding with the sushi 1 domain. More importantly, one double mutation based on different vertebrate APP sequences from evolution exhibited a stronger binding (ΔΔG = -1.91 ± 0.66 kcal mol -1 ), indicating a potentially enhanced GABA B R1a modulator. These large-scale simulations may provide new insights into the binding mechanism between sAPP and the sushi 1 domain, which could open new avenues in the development of future GABA B R1a-specific therapeutics.

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

Simulating the Phonon Collection Efficiency in KIPMDs

Kinetic inductance phonon-mediated (KIPM) detectors use microwave kinetic inductance detectors (MKIDs) to read out phonon signals in the substrate. They are a promising class of detectors to be used in light dark matter (DM) searches due to their potential eV-scale sensitivity and native frequency-domain multiplexability. In order to improve upon the design of these detectors, simulations are needed to understand the effects of detector design on measurable physical parameters including the phonon collection efficiency, $\eta_{ph}$, which is defined as the ratio of phonon energy detected by the sensitive target element to the incident energy deposited in the substrate. This work simulates the phonon collection efficiency for a KIPMD currently operated at the Northwestern EXperimental Underground Site (NEXUS).

Dang, Stella Q.↗
DOE OSTI2024

Simulating the Phonon Collection Efficiency in Kinetic Inductance Phonon-Mediated Detectors

Kinetic inductance phonon-mediated (KIPM) detectors use microwave kinetic inductance detectors (MKIDs) to read out phonon signals in the substrate. They are a promising class of detectors to be used in light dark matter (DM) searches due to their potential eV-scale sensitivity and native frequency-domain multiplexability. In order to improve upon the design of these detectors, simulations are needed to understand the effects of detector design on measurable physical parameters including the phonon collection efficiency, $\eta_{ph}$, which is defined as the ratio of phonon energy detected by the sensitive target element to the incident energy deposited in the substrate. This work simulates the phonon collection efficiency for two existing detector architectures to study phonon absorption at substrate-sensor interfaces and phonon loss to non-sensitive detector elements.

Dang, Stella Q.↗
DOE OSTI2023

Promising approaches for the assembly of the catalytically active, recombinant Desulfomicrobium baculatum hydrogenase with substitutions at the active site

Background: Hydrogenases (H2ases) are metalloenzymes capable of the reversible conversion of protons and electrons to molecular hydrogen. Exploiting the unique enzymatic activity of H2ases can lead to advancements in the process of biohydrogen evolution and green energy production. Results: Here we created of a functional, optimized operon for rapid and robust production of recombinant [NiFe] Desulfomicrobium baculatum hydrogenase (Dmb H2ase). The conversion of the [NiFeSe] Dmb H2ase to [NiFe] type was performed on genetic level by site-directed mutagenesis. The native dmb operon includes two structural H2ase genes, coding for large and small subunits, and an additional gene, encoding a specific maturase (protease) that is essential for the proper maturation of the enzyme. Dmb, like all H2ases, needs intricate bio-production machinery to incorporate its crucial inorganic ligands and cofactors. Strictly anaerobic, sulfate reducer D. baculatum bacteria are distinct, in terms of their biology, from E. coli. Thus, we introduced a series of alterations within the native dmb genes. As a result, more than 100 elements, further compiled into 32 operon variants, were constructed. The initial requirement for a specific maturase was omitted by the artificial truncation of the large Dmb subunit. The assembly of the produced H2ase subunit variants was investigated both, in vitro and in vivo. This approach resulted in 4 recombinant [NiFe] Dmb enzyme variants, capable of H 2 evolution. The aim of this study was to overcome the gene expression, protein biosynthesis, maturation and ligand loading bottlenecks for the easy, fast, and cost-effective delivery of recombinant [NiFe] H2ase, using a commonly available E. coli strains. Conclusion: The optimized genetic constructs together with the developed growth and purification procedures appear to be a promising platform for further studies toward fully-active and O 2 tolerant, recombinant [NiFeSe] Dmb H2ase, resembling the native Dmb enzyme. It could likely be achieved by selective cysteine to selenocysteine substitution within the active site of the [NiFe] Dmb variant.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Accelerated screening of functional atomic impurities in halide perovskites using high-throughput computations and machine learning

The pressing need for novel materials that can serve rising demands in solar cell and optoelectronic technologies makes the nexus of halide perovskites, high-throughput computations, and machine learning, very promising. Ever increasing amounts of data on the structure, fundamental properties, and device performance of halide perovskites provide opportunities for learning chemical rules and design principles that make these materials attractive, and applying them across wide chemical spaces. In this work, we show that impurity properties of halide perovskites computed using density functional theory (DFT) can be combined with machine learning (ML) to deliver predictive models and quick identification of optoelectronically active impurity atoms. Our computation lead to the largest reported dataset of the formation energies and charge transition levels of Pb-site impurities in methylammonium lead halide (MAPbX 3 ) perovskites. Descriptors are defined to uniquely represent any impurity atom in any MAPbX 3 compound and mapped to the computed impurity properties using regression techniques such as Gaussian process regression, neural networks, and random forests. We use the best optimized predictive models to make predictions for hundreds of impurities across 9 MAPbX 3 compounds and create lists of dominating impurities, that is, impurities that can shift the equilibrium Fermi level in the perovskite as determined by native point defects. Finally, this accelerated screening powered by computations and machine learning can guide the identification of problematic impurities that may cause undesired recombination of charge carriers, as well as impurities that can be deliberately introduced to tune the perovskite conductivity and resulting photovoltaic absorption.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Lessons Learned Using in-situ TEM Liquid Corrosion of Al Alloys

Al and Al alloys are of interest in energy applications due to their strength and low weight [1] in addition to their electrochemical properties for aluminum-air batteries for energy storage [2]. However, Al alloys also are susceptible to corrosion in a variety of environments including liquid electrolytes and in solar panels [3], which has led to a great deal of research to understand and improve corrosion resistance in these materials. Al metal forms a native, passivating oxide layer in the presence of ambient air, which slows corrosion initiation. However, pitting still occurs as this protective layer breaks down in the presence of electrolytes. Thin metal Al films were used in these experiments to observe initiation and growth of pitting, which can be used as an approximation of corrosion initiation behavior in bulk samples.

alluminum alloys↗
DOE OSTI2020

Native defects in antiferromagnetic topological insulator MnBi 2 Te 4

Using scanning tunneling microscopy and spectroscopy, in this study we visualized the native defects in antiferromagnetic topological insulator MnBi 2 Te 4 . Two native defects, Mn Bi and Bi Te antisites, can be well resolved in the topographic images. Mn Bi tend to suppress the density of states at the conduction band edge. Spectroscopy imaging reveals a localized peaklike local density of state at ~ 80 meV below the Fermi energy. A careful inspection of topographic and spectroscopic images, combined with density functional theory calculation, suggests this results from Bi Mn antisites at Mn sites. The random distribution of Mn Bi and Bi Mn antisites results in spatial fluctuation of local density of states near the Fermi level in MnBi 2 Te 4 .

36 MATERIALS SCIENCE↗
DOE OSTI2020

Decoy selection for protein structure prediction via extreme gradient boosting and ranking

Background: Identifying one or more biologically-active/native decoys from millions of non-native decoys is one of the major challenges in computational structural biology. The extreme lack of balance in positive and negative samples (native and non-native decoys) in a decoy set makes the problem even more complicated. Consensus methods show varied success in handling the challenge of decoy selection despite some issues associated with clustering large decoy sets and decoy sets that do not show much structural similarity. Recent investigations into energy landscape-based decoy selection approaches show promises. However, lack of generalization over varied test cases remains a bottleneck for these methods. Results: We propose a novel decoy selection method, ML-Select, a machine learning framework that exploits the energy landscape associated with the structure space probed through a template-free decoy generation. The proposed method outperforms both clustering and energy ranking-based methods, all the while consistently offering better performance on varied test-cases. Moreover, ML-Select shows promising results even for the decoy sets consisting of mostly low-quality decoys. Conclusions: ML-Select is a useful method for decoy selection. This work suggests further research in finding more effective ways to adopt machine learning frameworks in achieving robust performance for decoy selection in template-free protein structure prediction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Suppressed paramagnetism in amorphous Ta 2 O 5 − x oxides and its link to superconducting-qubit performance

Amorphous-oxide layers in thin-film capacitors are linked to reduced transmon-qubit T 1 coherence times. Ta -based capacitors outperform Nb -based ones, suggesting that amorphous Ta 2 O 5 − x is less lossy than Nb 2 O 5 − x . We investigate the microscopic features of these amorphous oxides using ab initio molecular dynamics and density functional theory, revealing the origins of the superior performance of Ta 2 O 5 − x . We establish that oxygen deficiency is less likely to occur in amorphous Ta 2 O 5 − x than in Nb 2 O 5 − x for 0 ≤ x ≤ 0.25 and that for a given oxygen deficiency x , metal Ta — Ta bond formation is enhanced. Such bonds, which are accommodated by structural flaws in the amorphous network, capture electrons better than in amorphous Nb 2 O 5 − x . These thermochemical differences quench or highly suppress magnetic moments in amorphous Ta 2 O 5 − x and eliminate a potential source of quasiparticles and magnetic flux noise. We also show that hyperfine couplings between Nb nuclei and local magnetic moments in Nb 2 O 5 − x can form “two-level systems” (TLSs) or “two-level fluctuators” with energy splittings of 100–1000 MHz or higher. This reveals a TLS mechanism in amorphous Nb 2 O 5 − x oxide layers that is likely inactive in Ta 2 O 5 − x . Our work provides a fundamental understanding of the materials chemistry and limitations imposed by native oxides of superconducting qubits that can be used to guide materials selection and processing.

Pritchard, P. Graham [Northwestern U.] (ORCID:0000↗
DOE OSTI2022

Thioester synthesis by a designed nickel enzyme models prebiotic energy conversion

The formation of carbon–carbon bonds from prebiotic precursors such as carbon dioxide represents the foundation of all primordial life processes. In extant organisms, this reaction is carried out by the carbon monoxide dehydrogenase (CODH)/acetyl coenzyme A synthase (ACS) enzyme, which performs the cornerstone reaction in the ancient Wood–Ljungdahl metabolic pathway to synthesize the key biological metabolite, acetyl-CoA. Despite its significance, a fundamental understanding of this transformation is lacking, hampering efforts to harness analogous chemistry. To address these knowledge gaps, we have designed an artificial metalloenzyme within the azurin protein scaffold as a structural, functional, and mechanistic model of ACS. We demonstrate the intermediacy of the Ni I species and requirement for ordered substrate binding in the bioorganometallic carbon–carbon bond-forming reaction from the one-carbon ACS substrates. The electronic and geometric structures of the nickel-acetyl intermediate have been characterized using time-resolved optical, electron paramagnetic resonance, and X-ray absorption spectroscopy in conjunction with quantum chemical calculations. Moreover, we demonstrate that the nickel-acetyl species is chemically competent for selective acyl transfer upon thiol addition to biosynthesize an activated thioester. Drawing an analogy to the native enzyme, a mechanism for thioester generation by this ACS model has been proposed. The fundamental insight into the enzymatic process provided by this rudimentary ACS model has implications for the evolution of primitive ACS-like proteins. Ultimately, these findings offer strategies for development of highly active catalysts for sustainable generation of liquid fuels from one-carbon substrates, with potential for broad applications across diverse fields ranging from energy storage to environmental remediation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗