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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

Architecture, catalysis and regulation of methylthio-alkane reductase for bacterial sulfur acquisition from volatile organic compounds

Bacteria utilize methylthio-alkane reductase (MAR) to acquire sulfur from volatile organic sulfur compounds. Reductive cleavage of methylthio-ethanol and dimethylsulfide liberates methanethiol for methionine synthesis and concomitantly releases ethylene and methane, respectively. Here we show that the native MAR of Rhodospirillum rubrum is a two-component system composed of a MarH ATP-dependent reductase and a MarDK catalytic core, whose architecture parallels nitrogenase. MarS complexes with MarDK to downregulate MAR activity during cellular sulfate influx, based on chromatographic and activity analyses. MarDK possesses complex metallocofactors resembling, but not identical to, nitrogenase P- and iron-only M-clusters, designated as mar1 and mar2 clusters based on metal, spectroscopic and mutagenesis analyses. They exhibit electronic features similar to the iron-only nitrogenase under turnover and, remarkably, are matured by MarB or nitrogenase NifB, resulting in maturase-dependent activity profiles. Altogether, this suggests a broader scope of reactivity, mechanisms and regulation in microbial metabolism for the nitrogenase-like family of enzymes than previously considered.

09 BIOMASS FUELS↗
DOE OSTI2024

Harvest Initiated Volatile Organic Compound Emissions from In-Field Tall Wheatgrass

While crop and grassland usage continues to increase, the full diversity of plant-specific volatile organic compounds (VOCs) emitted from these ecosystems, including their implications for atmospheric chemistry and carbon cycling, remains poorly understood. It is particularly important to investigate VOCs in the context of potential biofuels: aside from the implications of largescale land use, harvest may shift both the flux and speciation of emitted VOCs. To this point, we evaluate the diversity of VOCs emitted both pre and postharvest from “Alkar” tall wheatgrass (Thinopyrum ponticum), a candidate biofuel that exhibits greater tolerance to frost and saline land compared to other grass varieties. Mature plants grown under field conditions (n = 6) were sampled for VOCs both pre- and postharvest (October 2022). Via hierarchical clustering of emitted VOCs from each plant, we observe distinct “volatilomes” (diversity of VOCs) specific to the pre- and postharvest conditions despite plant-to-plant variability. In total, 50 VOCs were found to be unique to the postharvest tall wheatgrass volatilome, and these unique VOCs constituted a significant portion (26%) of total postharvest signal. While green leaf volatiles (GLVs) dominate the speciation of postharvest emissions (e.g., 54% of unique postharvest VOC signal was due to 1-penten-3-ol), we demonstrate novel postharvest VOCs from tall wheatgrass that are under characterized in the context of carbon cycling and atmospheric chemistry (e.g., 3-octanone). Continuing evaluations will quantitatively investigate tall wheatgrass VOC fluxes, better informing the feasibility and environmental impact of tall wheatgrass as a biofuel.

09 BIOMASS FUELS↗
DOE OSTI2022

In Situ Probing and Investigation of the Crystal Growth of Highly Correlated Intermetallics

The proposal seeks to investigate the synthetic process of a new class of highly correlated intermetallics Ce n+1 Co n Ge 3n+1 (n = 1 – 6). This family of compounds is attractive as members of the series consist of subunits found in quantum materials. With our efforts to grow single crystals, we will address the fundamental questions of 1) how do crystals that are built from subunits form during crystallization and 2) what determines how these subunits arrange. We hypothesize that the complex intergrowth structures of Ce n+1 Co n Ge 3n+1 form upon cooling by the assembly of subunit-like clusters that exist prior to crystallization in the melt. The second hypothesis is layer-by-layer growth. The third hypothesis is an alternative growth mechanism, such as the conversion of metastable structure into a different structure. By understanding the assembly of subunits, strategies to affect process could emerge, which will ultimately lead to controlled heterostructural stacking of various subunits in the growth of bulk materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Bulk electronic structure of lanthanum hexaboride (LaB 6 ) by hard x-ray angle-resolved photoelectron spectroscopy

In the last decade rare-earth hexaborides have been investigated for their fundamental importance in condensed matter, and for their applications in advanced technological fields. Among these compounds, LaB 6 has a special place, being a traditional d-band metal without additional f- bands. In order to understand the bulk electronic structure of the more complex rare-earth hexaborides, in this paper we investigate the bulk electronic structure of LaB 6 using tender/hard x-ray photoemission spectroscopy, measuring both core-level and angle-resolved valence-band spectra. Furthermore, we compare the La 3d core level spectrum to cluster model calculations in order to understand the bulk-like core-hole screening effects. The results show that the La 3d well-screened peak is at a lower binding energy compared to the main poorly-screened peak; the relative intensity between these peaks depends on how strong the hybridization is between La and B atoms. Here, we show that the recoil effect, negligible in the soft x-ray regime, becomes prominent at higher kinetic energies for lighter elements, such as boron, but is still negligible for heavy elements, such as lanthanum. In addition, we report the bulk-like band structure of LaB6 determined by tender/hard x-ray angle-resolved photoemission spectroscopy (HARPES). We compare HARPES experimental results to the free-electron final-state calculations and to the more precise one-step photoemission theory including matrix element and phonon excitation effects. The agreement between the features present in the experimental ARPES data and the theoretical calculations is very good. In addition, we consider the nature and the magnitude of phonon excitations in order to interpret HARPES experimental data measured at different temperatures and excitation energies. We demonstrate that one step theory of photoemission and HARPES experiments provide, at present, the only approach capable of probing, both experimentally and theoretically, true “bulk-like” electronic band structure of rare-earth hexaborides and strongly correlated materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Microbial Community Field Surveys Reveal Abundant Pseudomonas Population in Sorghum Rhizosphere Composed of Many Closely Related Phylotypes

While the root-associated microbiome is typically less diverse than the surrounding soil due to both plant selection and microbial competition for plant derived resources, it typically retains considerable complexity, harboring many hundreds of distinct bacterial species. Here, we report a time-dependent deviation from this trend in the rhizospheres of field grown sorghum. In this study, 16S rRNA amplicon sequencing was used to determine the impact of nitrogen fertilization on the development of the root-associated microbiomes of 10 sorghum genotypes grown in eastern Nebraska. We observed that early rhizosphere samples exhibit a significant reduction in overall diversity due to a high abundance of the bacterial genus Pseudomonas that occurred independent of host genotype in both high and low nitrogen fields and was not observed in the surrounding soil or associated root endosphere samples. When clustered at 97% identity, nearly all the Pseudomonas reads in this dataset were assigned to a single operational taxonomic unit (OTU); however, exact sequence variant (ESV)-level resolution demonstrated that this population comprised a large number of distinct Pseudomonas lineages. Furthermore, single-molecule long-read sequencing enabled high-resolution taxonomic profiling revealing further heterogeneity in the Pseudomonas lineages that was further confirmed using shotgun metagenomic sequencing. Finally, field soil enriched with specific carbon compounds recapitulated the increase in Pseudomonas, suggesting a possible connection between the enrichment of these Pseudomonas species and a plant-driven exudate profile.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Inelastic Neutron Scattering Data for Ba₃Zn(Ru₀.₁Sb₁.₉)O₉

This dataset contains inelastic neutron scattering measurements on the magnetically dilute compound Ba₃Zn(Ru₀.₁Sb₁.₉)O₉, collected at the Spallation Neutron Source using the Cold Neutron Chopper Spectrometer (CNCS) and the SEQUOIA Fine-Resolution Fermi Chopper Spectrometer. The sample consists of nominally 5% magnetic Ru⁵⁺ ions (S = 3/2) randomly substituted into a diamagnetic Sb⁵⁺ matrix. Measurements were performed at base temperature (2–5 K) and 300 K using multiple incident energies (1.00, 3.32, 12.0, and 100 meV) to resolve magnetic excitations from isolated monomers and small Ru clusters (dimers, trimers, etc.). The dataset includes raw event-mode files, momentum- and energy-resolved spectra, and supporting metadata for instrument configuration, sample environment, and reduction parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Water mediated growth of oriented single crystalline SrCO3 nanorod arrays on strontium compounds

Abstract Morphology-controlled strontianite nanostructures have attracted interest in various fields, such as electrocatalyst and photocatalysts. Basic additives in aqueous strontium solutions is commonly used in controlling strontianite nanostructures. Here, we show that trace water also serves an important role in forming and structuring vertically oriented strontianite nanorod arrays on strontium compounds. Using in situ Raman spectroscopy, we monitored the structural evolution from hydrated strontium to strontianite nanorods, demonstrating the epitaxial growth by vapor–liquid–solid mechanism. Water molecules cause not only the exsolution of Sr liquid droplets on the surface but also the uptake of airborne CO 2 followed by its ionization to CO 3 2− . The existence of intermediate SrHO + –OCO 2 2− phase indicates the interaction of CO 3 2− with SrOH + in Sr(OH) x (H 2 O) y cluster to orient strontianite crystals. X-ray diffraction simulation and transmission electron microscopy identify the preferred-orientation plane of the 1D nanostructures as the (002) plane, i.e., the growth along the c-axis. The anisotropic growth habit is found to be affected by the kinetics of carbonation. This study paves the way for designing and developing 1D architecture of alkaline earth metal carbonates by a simple method without external additives at room temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2023

On the potentially transformative role of auxiliary-field quantum Monte Carlo in quantum chemistry: A highly accurate method for transition metals and beyond

Approximate solutions to the ab initio electronic structure problem have been a focus of theoretical and computational chemistry research for much of the past century, with the goal of predicting relevant energy differences to within “chemical accuracy” (1 kcal/mol). For small organic molecules, or in general, for weakly correlated main group chemistry, a hierarchy of single-reference wave function methods has been rigorously established, spanning perturbation theory and the coupled cluster (CC) formalism. For these systems, CC with singles, doubles, and perturbative triples is known to achieve chemical accuracy, albeit at O(N7) computational cost. In addition, a hierarchy of density functional approximations of increasing formal sophistication, known as Jacob’s ladder, has been shown to systematically reduce average errors over large datasets representing weakly correlated chemistry. However, the accuracy of such computational models is less clear in the increasingly important frontiers of chemical space including transition metals and f-block compounds, in which strong correlation can play an important role in reactivity. A stochastic method, phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC), has been shown to be capable of producing chemically accurate predictions even for challenging molecular systems beyond the main group, with relatively low O(N3 − N4) cost and near-perfect parallel efficiency. Herein, we present our perspectives on the past, present, and future of the ph-AFQMC method. We focus on its potential in transition metal quantum chemistry to be a highly accurate, systematically improvable method that can reliably probe strongly correlated systems in biology and chemical catalysis and provide reference thermochemical values (for future development of density functionals or interatomic potentials) when experiments are either noisy or absent. Finally, we discuss the present limitations of the method and where we expect near-term development to be most fruitful.

Chemistry↗
DOE OSTI2022

MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters

Abstract With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Atomic-scale probing of short-range order and its impact on electrochemical properties in cation-disordered oxide cathodes

Abstract Chemical short-range-order has been widely noticed to dictate the electrochemical properties of Li-excess cation-disordered rocksalt oxides, a class of cathode based on earth abundant elements for next-generation high-energy-density batteries. Existence of short-range-order is normally evidenced by a diffused intensity pattern in reciprocal space, however, derivation of local atomic arrangements of short-range-order in real space is hardly possible. Here, by a combination of aberration-corrected scanning transmission electron microscopy, electron diffraction, and cluster-expansion Monte Carlo simulations, we reveal the short-range-order is a convolution of three basic types: tetrahedron, octahedron, and cube. We discover that short-range-order directly correlates with Li percolation channels, which correspondingly affects Li transport behavior. We further demonstrate that short-range-order can be effectively manipulated by anion doping or post-synthesis thermal treatment, creating new avenues for tailoring the electrochemical properties. Our results provide fundamental insights for decoding the complex relationship between local chemical ordering and properties of crystalline compounds.

25 ENERGY STORAGE↗
DOE OSTI2024

Subsurface microbial community structure shifts along the geological features of the Central American Volcanic Arc

Subduction of the Cocos and Nazca oceanic plates beneath the Caribbean plate drives the upward movement of deep fluids enriched in carbon, nitrogen, sulfur, and iron along the Central American Volcanic Arc (CAVA). These compounds fuel diverse subsurface microbial communities that in turn alter the distribution, redox state, and isotopic composition of these compounds. Microbial community structure and functions vary according to deep fluid delivery across the arc, but less is known about how microbial communities differ along the axis of a convergent margin as geological features (e.g., extent of volcanism and subduction geometry) shift. Here, we investigate changes in bacterial 16S rRNA gene amplicons and geochemical analysis of deeply-sourced seeps along the southern CAVA, where subduction of the Cocos Ridge alters the geological setting. We find shifts in community composition along the convergent margin, with communities in similar geological settings clustering together independently of the proximity of sample sites. Microbial community composition correlates with geological variables such as host rock type, maturity of hydrothermal fluid and slab depth along different segments of the CAVA. This reveals tight coupling between deep Earth processes and subsurface microbial activity, controlling community distribution, structure and composition along a convergent margin.

Science & Technology - Other Topics↗
DOE OSTI2020

Generation of a chromosome-scale genome assembly of the insect-repellent terpenoid-producing Lamiaceae species, Callicarpa americana

Plants exhibit wide chemical diversity due to the production of specialized metabolites that function as pollinator attractants, defensive compounds, and signaling molecules. Lamiaceae (mints) are known for their chemodiversity and have been cultivated for use as culinary herbs, as well as sources of insect repellents, health-promoting compounds, and fragrance. We report the chromosome-scale genome assembly of Callicarpa americana L. (American beautyberry), a species within the early-diverging Callicarpoideae clade of Lamiaceae, known for its metallic purple fruits and use as an insect repellent due to its production of terpenoids. Using long-read sequencing and Hi-C scaffolding, we generated a 506.1-Mb assembly spanning 17 pseudomolecules with N50 contig and N50 scaffold sizes of 7.5 and 29.0 Mb, respectively. In all, 32,164 genes were annotated, including 53 candidate terpene synthases and 47 putative clusters of specialized metabolite biosynthetic pathways. Our analyses revealed 3 putative whole-genome duplication events, which, together with local tandem duplications, contributed to gene family expansion of terpene synthases. Kolavenyl diphosphate is a gateway to many of the bioactive terpenoids in C. americana; experimental validation confirmed that CamTPS2 encodes kolavenyl diphosphate synthase. Syntenic analyses with Tectona grandis L. f. (teak), a member of the Tectonoideae clade of Lamiaceae known for exceptionally strong wood resistant to insects, revealed 963 collinear blocks and 21,297 C. americana syntelogs. Access to the C. americana genome provides a road map for rapid discovery of genes encoding plant-derived agrichemicals and a key resource for understanding the evolution of chemical diversity in Lamiaceae.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Ultra broadband yellow emitting lead-free metal halide perovskite like compounds with near-unity emission quantum yields

Metal halide perovskites (MHPs) are interesting semiconductor materials with potential for use in optoelectronic and photonic devices. Their practical applications are hindered due to the negative environmental effects of the lead ions (Pb 2+ ) used in these materials and stability issues. Exploring new environmentally friendly materials with lead-free metal halides and investigating the factors affecting their optical properties and stability are essential. The broadband emission and high (near-unity; ~100%) photoluminescence quantum yield (PLQY) of low-dimensional copper(I) halides make them great candidates for the next-generation luminescent materials for lighting applications. Here, a Cu(I) iodide based organic/inorganic hybrid halide (benzo-15-crown-5) 2 NaH 2 OCu 4 I 6 (BCNCI) with a zero-dimensional (0D) cluster was prepared. The BCNCI has a broadband yellow emission peaked at 548 nm with a near-unity PLQY (99.1%) upon excitation at 365 nm (ultraviolet). Upon excitation at 450 nm (blue), a high PLQY of 82% was also achieved. The luminescence mechanism was discussed in detail. Interestingly, BCNCI exhibits ultra-broad band excitation in the 300–500 nm range, which matches commercially available UV and blue-emitting chips. Compared to commercial YAG:Ce 3+ phosphors, the emission spectrum is sufficiently broad to cover the visible spectral region. This work illustrates a good example of developing an environmentally friendly white light source, using high-performance copper halides with adequate broadband excitation and emission.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Overview of Diverse Methyl/Alkyl-Coenzyme M Reductases and Considerations for Their Potential Heterologous Expression

Methyl-coenzyme M reductase (MCR) is an archaeal enzyme that catalyzes the final step of methanogenesis and the first step in the anaerobic oxidation of methane, the energy metabolisms of methanogens and anaerobic methanotrophs (ANME), respectively. Variants of MCR, known as alkyl-coenzyme M reductases, are involved in the anaerobic oxidation of short-chain alkanes including ethane, propane, and butane as well as the catabolism of long-chain alkanes from oil reservoirs. MCR is a dimer of heterotrimers (encoded by mcrABG) and requires the nickel-containing tetrapyrrole prosthetic group known as coenzyme F430. MCR houses a series of unusual post-translational modifications within its active site whose identities vary depending on the organism and whose functions remain unclear. Methanogenic MCRs are encoded in a highly conserved mcrBDCGA gene cluster, which encodes two accessory proteins, McrD and McrC, that are believed to be involved in the assembly and activation of MCR, respectively. The requirement of a unique and complex coenzyme, various unusual post-translational modifications, and many remaining questions surrounding assembly and activation of MCR largely limit in vitro experiments to native enzymes with recombinant methods only recently appearing. Production of MCRs in a heterologous host is an important step toward developing optimized biocatalytic systems for methane production as well as for bioconversion of methane and other alkanes into value-added compounds. This review will first summarize MCR catalysis and structure, followed by a discussion of advances and challenges related to the production of diverse MCRs in a heterologous host.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Q-BEEP: Quantum Bayesian Error Mitigation Employing Poisson Modeling over the Hamming Spectrum

Quantum computing technology has grown rapidly in recent years, with new technologies being explored, error rates being reduced, and quantum processor’s qubit capacity growing. However, near-term quantum algorithms are still unable to be induced without compounding consequential levels of noise, leading to non-trivial erroneous results. Quantum Error Correction (in-situ error mitigation) and Quantum Error Mitigation (post-induction error mitigation) are promising fields of research within the quantum algorithm scene, aiming to alleviate quantum errors, increasing the overall fidelity and hence the overall quality of circuit induction. Earlier this year, a pioneering work, namely HAMMER, published in ASPLOS-22 demonstrated the existence of a latent structure regarding post-circuit induction errors when mapping to the Hamming spectrum. However, they intuitively assumed that errors occur in local clusters, and that at higher average Hamming distances this structure falls away. In this work, we show that such a correlation structure is not only local but extends certain non-local clustering patterns which can be precisely described by a Poisson distribution model taking the input circuit, the device run time status (i.e., calibration statistics) and qubit topology into consideration. Using this quantum error characterizing model, we developed an iterative algorithm over the generated Bayesian network state-graph for post-induction error mitigation. Thanks to more precise modeling of the error distribution latent structure and the new iterative method, our Q-Beep approach provides state of the art performance and can boost circuit execution fidelity by up to 234.6% on Bernstein-Vazirani circuits and on average 71.0% on QAOA solution quality, using 16 practical IBMQ quantum processors. For other benchmarks such as those in QASMBench, the fidelity improvement is up to 17.8%. Q-Beep is a light-weight post-processing technique that can be performed offline and remotely, making it a useful tool for quantum vendors to integrate and provide more reliable circuit induction results.

Stein, Samuel A.↗
DOE OSTI2022

Multiple ferroelectric nematic phases of a highly polar liquid crystal compound

Ferroelectric nematic liquid crystals represent not only fascinating, fundamental science, but they also hold promise for new technologies including high-density power storage or sub-millisecond switching information displays. In this work, we describe the synthesis and measurements of the physical properties of a new compound, 4-nitrophenyl 4-[(2,4-dimethoxylbenzoyl)oxy]-2-fluorobenzoate (RT11001). This material exhibits multiple, highly polar, ferroelectric nematic phases that have not been previously reported. Here we employ a wide range of physical characterisation methods including differential scanning calorimetry (DSC), mass density measurement, optical birefringence, polarising optical microscopy (POM), dielectric spectroscopy, electric current analysis, electro-optical switching, small-angle and wide-angle x-ray scattering measurements to show that RT11001 has multiple, distinct ferroelectric phases. We argue that the highest temperature phase is a polar nematic fluid with non-polar smectic clusters. Directly below appears to be a transition to another polar nematic phase containing polar positionally ordered clusters. Lastly, there are indications of an additional, polar biaxial liquid crystal phase at lower temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Systematic characterization of unknown compounds via dimensionality reduction of time series

Analysis of ambient aerosols provides valuable insight into particle sources and formation chemistry. However, due to the complexity of atmospheric data and the dynamic nature of aerosol composition, a substantial fraction of data often become discarded by conventional analysis methods. Furthermore, a large fraction of chemical species within those data are unidentifiable due to a lack of matching spectral information, resulting in suboptimal characterization of chemical composition. Previous work has demonstrated techniques for cataloging analytes in a chromatographic dataset by deconvolution of mass spectra, but integration of these analytes throughout a large dataset remains time consuming. Here, we present a method to automatically identify an ion for quantitation for single-ion chromatogram based peak fitting and integration, enabling comprehensive integration of analytes with minimal user interaction. The resulting time series are clustered with a machine-learning based dimensionality reduction technique to systematically investigate the underlying characteristics of the categorized analytes and gain new insights into the chemical composition and physicochemical properties of the unidentifiable analytes. We apply these methods to existing atmospheric datasets collected in Manacapuru, Brazil during the GoAmazon2014/5 campaign to identify new analytes and interpret their variability and transformations in the atmosphere. The analysis results generate 408 time series from cataloged analytes of interest, and the clustering of those time series with spherical k-means results in 8 distinct clusters. We find the analytes form clusters based on their distinct physicochemical properties, demonstrating the method’s ability to systematically identify and selectively filter contaminants and instrumental analytes and characterize the unidentifiable analytes.

54 ENVIRONMENTAL SCIENCES↗