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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Diverse Organic-Mineral Associations in Jezero Crater, Mars

The presence and distribution of preserved organic matter on the surface of Mars can provide key information about the Martian carbon cycle and the potential of the planet to host life throughout its history. Several types of organic molecules have been previously detected in Martian meteorites1 and at Gale crater, Mars. Evaluating the diversity and detectability of organic matter elsewhere on Mars is important for understanding the extent and diversity of Martian surface processes and the potential availability of carbon sources1,5,6. Here we report the detection of Raman and fluorescence spectra consistent with several species of aromatic organic molecules in the Máaz and Séítah formations within the Crater Floor sequences of Jezero crater, Mars. We report specific fluorescence-mineral associations consistent with many classes of organic molecules occurring in different spatial patterns within these compositionally distinct formations, potentially indicating different fates of carbon across environments. Our findings suggest there may be a diversity of aromatic molecules prevalent on the Martian surface, and these materials persist despite exposure to surface conditions. These potential organic molecules are largely found within minerals linked to aqueous processes, indicating that these processes may have had a key role in organic synthesis, transport or preservation.

Sunanda Sharma↗
NASA NTRS2017

The Transcriptional Response of Diverse Saccharomyces Cerevisiae Strains to Simulated Microgravity

Spaceflight imposes multiple stresses on biological systems resulting in genome-scale adaptations. Understanding these adaptations and their underlying molecular mechanisms is important to clarifying and reducing the risks associated with spaceflight. One such risk is infection by microbes present in spacecraft and their associated systems and inhabitants. This risk is compounded by results suggesting that some microbes may exhibit increased virulence after exposure to spaceflight conditions. The yeast, S. cerevisiae, is a powerful microbial model system, and its response to spaceflight has been studied for decades. However, to date, these studies have utilized common lab strains. Yet studies on trait variation in S. cerevisiae demonstrate that these lab strains are not representative of wild yeast and instead respond to environmental stimuli in an atypical manner. Thus, it is not clear how transferable these results are to the wild S. cerevisiae strains likely to be encountered during spaceflight. To determine if diverse S. cerevisiae strains exhibit a conserved response to simulated microgravity, we will utilize a collection of 100 S. cerevisiae strains isolated from clinical, environmental and industrial settings. We will place selected S. cerevisiae strains in simulated microgravity using a high-aspect rotating vessel (HARV) and document their transcriptional response by RNA-sequencing and quantify similarities and differences between strains. Our research will have a strong impact on the understanding of how genetic diversity of microorganisms effects their response to spaceflight, and will serve as a platform for further studies.

yeast↗
NASA NTRS2017

The Transcriptional Response of Diverse Saccharomyces Cerevisiae Strains to Simulated Microgravity

Spaceflight imposes multiple stresses on biological systems resulting in genome-scale adaptations. Understanding these adaptations and their underlying molecular mechanisms is important to clarifying and reducing the risks associated with spaceflight. One such risk is infection by microbes present in spacecraft and their associated systems and inhabitants. This risk is compounded by results suggesting that some microbes may exhibit increased virulence after exposure to spaceflight conditions. The yeast, S. cerevisiae, is a powerful microbial model system, and it's response to spaceflight has been studied for decades. However, to date, these studies have utilized common lab strains. Yet studies on trait variation in S. cerevisiae demonstrate that these lab strains are not representative of wild yeast and instead respond to environmental stimuli in an atypical manner. Thus, it is not clear how transferable these results are to the wild S. cerevisiae strains likely to be encountered during spaceflight. To determine if diverse S. cerevisiae strains exhibit a conserved response to simulated microgravity, we will utilize a collection of 100 S. cerevisiae strains isolated from clinical, environmental and industrial settings. We will place selected S. cerevisiae strains in simulated microgravity using a high-aspect rotating vessel (HARV) and document their transcriptional response by RNA-sequencing and quantify similarities and differences between strains. Our research will have a strong impact on the understanding of how genetic diversity of microorganisms effects their response to spaceflight, and will serve as a platform for further studies.

genetic diversity↗
NASA NTRS2018

The Transcriptional Response of Diverse Saccharomyces cerevisiae Strains to Simulated Microgravity

Spaceflight imposes multiple stresses on biological systems resulting in genome-scale adaptations. Understanding these adaptations and their underlying molecular mechanisms is important to clarifying and reducing the risks associated with spaceflight. One such risk is infection by microbes present in spacecraft and their associated systems and inhabitants. This risk is compounded by results suggesting that some microbes may exhibit increased virulence after exposure to spaceflight conditions. The yeast, S. cerevisiae, is a powerful microbial model system, and it's response to spaceflight has been studied for decades. However, to date, these studies have utilized common lab strains. Yet studies on trait variation in S. cerevisiae demonstrate that these lab strains are not representative of wild yeast and instead respond to environmental stimuli in an a typical manner. Thus, it is not clear how transferable these results are to the wild S. cerevisiae strains likely to be encountered during spaceflight. To determine if diverse S. cerevisiae strains exhibit a conserved response to simulated microgravity, we will utilize a collection of 100 S. cerevisiae strains isolated from clinical, environmental and industrial settings. We will place selected S. cerevisiae strains in simulated microgravity using a high-aspect rotating vessel (HARV) and document their transcriptional response by RNA-sequencing and quantify similarities and differences between strains. Our research will have a strong impact on the understanding of how genetic diversity of microorganisms effects their response to spaceflight, and will serve as a platform for further studies.

spaceflight↗
DOE OSTI2025

Is a Malleable Active Site Loop the Key to High Substrate Promiscuity? Hybrid, Biocatalytic Route to Structurally Diverse Taxoid Side Chains with Remarkable Dual Stereocontrol

Abstract These studies reveal the first structure ofClostridium acetobutylicumalcohol dehydrogenase (CaADH), a protein exhibiting remarkable substrate promiscuity and stereochemical fidelity. The CaADH enzyme is utilized here for synthesizing 20 potential aryl isoserine side chains for the Taxotere family of tubulin‐binding chemotherapeutics. The approach involves dynamic reductive kinetic resolution (DYRKR) upon the corresponding α‐chloro‐β‐keto esters, showing high D‐synstereoselectivity, including those leading to the clinically relevant milataxel (Ar = 2‐furyl) and simotaxel (Ar = 2‐thienyl) side chains. Furthermore, various cross‐coupling chemistries performed on thep‐bromophenyl isoserine side chain significantly enhance the structural diversity of the taxoid side chain library obtained (16 additional taxoid side chains). The CaADH structure is notable: (i) the nicotinamide cofactor is bound in ananti‐conformation, with the amide carbonyl occupying the ketone binding pocket, and (ii) a flexible loop near the active site likely contributes to the remarkable substrate promiscuity observed in CaADH. We present our perspective on the dynamic nature of the CaADH active site through molecular dynamics simulation, proposing a halogen bonding model as a potential mechanism for the remarkable selectivity for an (S)‐configured C─Cl bond, in addition to the D‐facial selectivity, demonstrated across 20 diverse substrates by this remarkable short‐chain dehydrogenase enzyme.

Chemistry↗
DOE OSTI2026

Metalloborophenes: Structural Diversity and Emerging Properties of Metal–Boron Two‐Dimensional Frameworks

Metalloborophenes, an emerging subclass of 2D materials, have attracted growing attention owing to their exceptional structural diversity and highly tunable electronic and magnetic properties. Constructed from vacancy‐rich borophene frameworks stabilized by electron donation from incorporated metal atoms, metalloborophenes merge the chemical versatility of boron with the functional richness of metal dopants. The first experimental realization of Cu–borophene nanoribbons in 2024 marked a pivotal advance, confirming long‐standing theoretical predictions and revitalizing interest in this new frontier of boron‐based 2D chemistry. Despite this progress, most studies to date remain conceptual and theoretical, constrained by challenges in scalable synthesis, dopant precision, and substrate control. Computational investigations have revealed a broad landscape of stable metalloborophene structures, exhibiting metallic, semiconducting, and magnetic behavior across diverse dopant families, including alkali, alkaline‐earth, transition, and lanthanide elements. These tunable characteristics open promising avenues for applications in spintronics, catalysis, and hydrogen storage. This review provides a comprehensive overview of metalloborophenes, emphasizing the interplay between structure, stability, and functionality, and outlining future directions toward bridging predictive modeling with experimental realization of this rapidly evolving class of 2D materials.

2D materials↗
DOE OSTI2025

Alpha ketoacid decarboxylases: Diversity, structures, reaction mechanisms, and applications for biomanufacturing of platform chemicals and fuels

In living cells, alpha-ketoacid decarboxylases (KDCs, EC 4.1.1.-) are a class of enzymes that convert alpha-ketoacids into aldehydes through decarboxylation. These aldehydes serve as either drop-in chemicals or precursors for the biosynthesis of alcohols, carboxylic acids, esters, and alkanes. These compounds play crucial roles in cellular metabolism and fitness and the bioeconomy, facilitating the sustainable and renewable biomanufacturing of platform chemicals and fuels. This review explores the diversity and classification of KDCs, detailing their structures, mechanisms, and functions. We highlight recent advancements in repurposing KDCs to enhance their efficiency and robustness for biomanufacturing. Additionally, we present modular KDC-dependent metabolic pathways for the microbial biosynthesis of aldehydes, alcohols, carboxylic acids, esters, and alkanes. Lastly, we discuss recent developments in the modular cell engineering technology that can potentially be applied to harness the diversity of KDC-dependent pathways for biomanufacturing platform chemicals and fuels.

09 BIOMASS FUELS↗
DOE OSTI2024

A Structurally Diverse Compound Screening Library to Identify Substrates for Diamine, Polyamine, and Related Acetyltransferases

Spermidine/spermine N-acetyltransferases (SSATs) and other types of polyamine acetyltransferases (PAATs) acetylate diamines and/or polyamines. These enzymes are evolutionarily related and belong to the Gcn5-related N-acetyltransferase (GNAT) superfamily, yet we lack a fundamental understanding of their substrate specificity and/or promiscuity toward different compounds. Many of these enzymes are known or are predicted to acetylate polyamines, but in the cell there are other types of compounds that contain moieties derived from polyamines that may be the native substrates for these enzymes. To learn more about the identity of substrates that are acetylated, we selected and screened 17 different GNAT enzymes for activity toward a set of structurally diverse compounds that contained different types of amine moieties (e.g., aminopropyl, aminobutyl, etc.). These compounds included diamines, triamines, and polyamines containing primary amino groups, and they had structural diversity with variation of the chain length and presence or absence of internal amino groups and other functional groups. We found 12 of the 17 enzymes acetylated at least one of the compounds. Some enzymes were selective toward acetylating only one compound while others exhibited substrate promiscuity toward numerous compounds. Our experimental results ultimately allowed us to pinpoint specific substrates that could be further investigated to more fully understand substrate specificity versus promiscuity of GNAT enzymes and the role of acetylated small molecules in cells.

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

Exploring the Structural, Biochemical, and Functional Diversity of Glycoside Hydrolase Family 12 from Penicillium subrubescens

Glycoside hydrolases (GHs) play an essential role in plant biomass degradation and modification for the sustainable production of biochemicals. The filamentous Ascomycete fungus Penicillium subrubescens contains a higher number of GH12 candidates compared to related species. Therefore, we aimed to compare P. subrubescens GH12s for their ability and substrate specificity for plant cell wall polysaccharide degradation and species’ potential as a source of novel enzymes for plant biomass valorization. Our re-evaluated phylogenetic analysis of fungal GH12 members showed that the P. subrubescens GH12s were located in different (new) clades. Biochemical characterization marked PsEglA as an endoglucanase and four other P. subrubescens GH12s (i.e., PsXegA–D) as xyloglucanases. Interestingly, structural features of PsXegD and PsXegE were more comparable to those of Basidiomycete GH12 xyloglucanases with a unique open substrate-binding cleft. PsUegA displayed dual xyloglucanase and endoglucanase activity and also showed distinct structural features. Comparative transcriptome analysis supported the functional diversity of P. subrubescens GH12s in plant biomass degradation. The gene encoding PsUegA was expressed under diverse conditions, suggesting a scouting role for this enzyme.

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

A New Coupled Biogeochemical Modeling Approach Provides Accurate Predictions of Methane and Carbon Dioxide Fluxes Across Diverse Tidal Wetlands

Abstract Tidal wetlands provide valuable ecosystem services, including storing large amounts of carbon. However, the net exchanges of carbon dioxide (CO 2 ) and methane (CH 4 ) in tidal wetlands are highly uncertain. While several biogeochemical models can operate in tidal wetlands, they have yet to be parameterized and validated against high‐frequency, ecosystem‐scale CO 2 and CH 4 flux measurements across diverse sites. We paired the Cohort Marsh Equilibrium Model (CMEM) with a version of the PEPRMT model called PEPRMT‐Tidal, which considers the effects of water table height, sulfate, and nitrate availability on CO 2 and CH 4 emissions. Using a model‐data fusion approach, we parameterized the model with three sites and validated it with two independent sites, with representation from the three marine coasts of North America. Gross primary productivity (GPP) and ecosystem respiration (R eco ) modules explained, on average, 73% of the variation in CO 2 exchange with low model error (normalized root mean square error (nRMSE) <1). The CH 4 module also explained the majority of variance in CH 4 emissions in validation sites ( R 2 = 0.54; nRMSE = 1.15). The PEPRMT‐Tidal‐CMEM model coupling is a key advance toward constraining estimates of greenhouse gas emissions across diverse North American tidal wetlands. Further analyses of model error and case studies during changing salinity conditions guide future modeling efforts regarding four main processes: (a) the influence of salinity and nitrate on GPP, (b) the influence of laterally transported dissolved inorganic C on R eco , (c) heterogeneous sulfate availability and methylotrophic methanogenesis impacts on surface CH 4 emissions, and (d) CH 4 responses to non‐periodic changes in salinity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Contribution of El Niño Southern Oscillation (ENSO) Diversity to Low‐Frequency Changes in ENSO Variance

Abstract El Niño Southern Oscillation (ENSO) diversity is characterized based on the longitudinal location of maximum sea surface temperature anomalies (SSTA) and amplitude in the tropical Pacific, as Central Pacific events are typically weaker than Eastern Pacific events. SSTA pattern and intensity undergo low‐frequency modulations, affecting ENSO prediction skill and remote impacts, and resulting in low‐frequency changes in ENSO variance. Yet, how different ENSO types contribute to these decadal variance changes remains unclear. Here, we decompose the low‐frequency changes of ENSO variance into contributions from ENSO diversity categories. We propose a fuzzy clustering of monthly SSTA to allow for non‐binary event category memberships, where each event can belong to different clusters. Our approach identifies two La Niña and three El Niño categories and shows that the major shift of ENSO variance in the mid‐1970s was associated with an increasing likelihood of strong La Niña and extreme El Niño events.

Geology↗
DOE OSTI2024

Quantifying the Diversity of an Atmospheric Aerosol Population in an Arctic Oil Field on a Single‐Particle Level

As the Arctic rapidly warms, sea ice extent is decreasing and oil and gas extraction activities are expanding. Local combustion emissions affect the Arctic atmospheric aerosol chemical mixing state (the distribution of chemical species across the aerosol population), which impacts climate-relevant properties. Bulk and single-particle measurements of submicron aerosols were conducted at Oliktok Point, Alaska within the North Slope of Alaska oil fields. In this work, we quantify aerosol diversity using online single-particle mass spectrometry data (32,880 individual particles), offline single-particle microscopy data (20,912 individual particles), and online bulk aerosol mass spectrometry and aethalometer data. This method was used to derive individual particle mass fractions for both refractory and non-refractory material within distinct particle types. Single-particle, average single-particle, and bulk population diversities (D i , D α , D γ , respectively) and mixing state indices (χ) were calculated for the data set. Calculated D i values were generally low (2.2 ± 0.6), as individual particle masses were dominated by a few chemical species of interest. Aged aerosol particles (those internally mixed with nitrate and/or sulfate) exhibited higher D i values (>3) compared to recently emitted (fresh) aerosol particles. During oil field plume periods, D α values approached three due to the abundance of diesel combustion particles, which were rich in sulfate, black carbon, and organic aerosol. Overall, the submicron aerosol population within the Arctic oil fields was found to be relatively externally mixed (χ < 50%), due to the constant local emissions within oil fields combining with background aerosol and locally emitted sea spray aerosol at the coastal site.

Wu, J.↗
DOE OSTI2026

Spatio-temporal dynamics of Hendra virus in Australia reveal stable maintenance of diverse viral clades among Pteropus bats

Hendra virus (HeV) was discovered in 1994 in Australia. Limited genomic data have hindered comprehensive understanding of HeV’s evolutionary dynamics. Here, in this work, we recovered 48 HeV genomes from bats and 9 from horses from Australia between 2016 and 2020, revealing four distinct clades. Each clade was distributed over a large spatial area with multiple clades co-circulating within a single bat roost on the same day and over consecutive years. The diversity and temporal stability of co-circulating clades suggest that viral dynamics are driven by episodic shedding of existing lineages maintained at the population level, rather than immune-driven strain-replacement dynamics. HeV isolates of different clades displayed variation in phenotypic properties but minimal antigenic differences. We provide an overview of evolutionary dynamics, phenotypic properties and assessment of countermeasures for HeV, and provide insights into the processes that maintain virus diversity in bats and influence the potential for viral emergence.

genetic variation↗
DOE OSTI2026

Mobile genetic elements shape microbial diversity and functions in thawing permafrost soils

Ecosystems are shaped by communities of microorganisms whose niches and impacts depend on functional profiles influenced by gene gains and losses. Culture-based experiments demonstrate that mobile genetic elements (MGEs) can mediate gene flux, but quantitative understanding of these dynamics in natural systems remains limited. Here we develop and apply a systematic, meta-omic framework to investigate MGEs in a complex natural system using an 8-year soil time series collected at Stordalen Mire, in Sweden’s thawing permafrost margin. In this climate-critical peatland, we identify ~2.1 million MGE recombinases across 89 microbial phyla and assess ecological distributions, affected functions, past mobility and current activity. This revealed an active mobilome that shapes natural genetic diversity via differential impacts on major phyla and affects a wide range of functions, including metabolic genes involved in carbon flux and nutrient cycling. These findings and this analytic framework suggest avenues towards a better understanding of MGE diversity, activity, mobility and impacts across ecosystems.

Biological and medical sciences↗
DOE OSTI2025

Molecular diversity of dissolved organic matter reflects macroecological patterns in river networks

Deciphering dissolved organic matter (DOM) molecular complexity is crucial for understanding ecosystem function. Using the continental-scale Worldwide Hydrobiogeochemistry Observation Network for Dynamic Rivers Systems (WHONDRS) Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) dataset, we reveal fundamental scaling patterns of DOM chemodiversity with watershed characteristics. Analysis of 54 river sites shows local and regional watershed features significantly influence DOM chemodiversity (2500–8718 unique formulae), exhibiting consistent scaling patterns across compound classes and a novel latitudinal gradient (decreasing diversity with increasing latitude). Scaling relationships for DOM composition vary by compound class. Crucially, the scaling parameters (B, baseline chemodiversity; Z, sensitivity) are linearly interrelated. This B–Z relationship is most robust for potentially bio-labile carbohydrates (coefficient of determination R 2 ≈ 0.85), diminishing for recalcitrant, plant-derived molecules (such as lignin), and indicates (potential) biolability-dependent coupling between baseline diversity and environmental responsiveness. These quantitative scaling relationships, with scaling exponents ranging from − 2.1 to 2.2 across compound classes, enable prediction of DOM composition across watersheds, offering a framework to understand ecosystem responses to environmental change. This research bridges biogeochemistry and ecology, providing tools to anticipate molecular transformations across scales.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Achieving precise multiparameter measurements with distributed optical fiber sensor using wavelength diversity and deep neural networks

The development of advanced distributed optical fiber sensing systems that are capable of performing accurate and spatially resolved multiparameter measurements is of great interest to a wide range of scientific and industrial applications. Here, in this paper, we propose and experimentally demonstrate a wavelength diversity based advanced distributed optical fiber sensor system to accomplish multiparameter sensing while greatly enhancing measurement accuracy. A suite of deep neural network (DNN) algorithms are developed and verified for data denoising, rapid Brillouin frequency shift estimation, and vibration data event classification. As a proof-of-concept, we demonstrate the effectiveness of the proposed advanced wavelength diversity distributed fiber sensor system assisted by DNN for simultaneous, independent measurements of static strain, temperature, and acoustic vibrations over a 25 km long sensing fiber at 3 m spatial resolution. These results suggest the potential for an intelligent multiparameter monitoring system with enhanced performance in advanced structural health monitoring applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Reproducibility of fixed-node diffusion Monte Carlo across diverse community codes: The case of water–methane dimer

Fixed-node diffusion quantum Monte Carlo (FN-DMC) is a widely trusted many-body method for solving the Schrödinger equation, known for its reliable predictions of material and molecular properties. Furthermore, its excellent scalability with system complexity and near-perfect utilization of computational power make FN-DMC ideally positioned to leverage new advances in computing to address increasingly complex scientific problems. Even though the method is widely used as a computational gold standard, reproducibility across the numerous FN-DMC code implementations has yet to be demonstrated. This difficulty stems from the diverse array of DMC algorithms and trial wave functions, compounded by the method’s inherent stochastic nature. Here, this study represents a community-wide effort to assess the reproducibility of the method, affirming that yes, FN-DMC is reproducible (when handled with care). Using the water–methane dimer as the canonical test case, we compare results from eleven different FN-DMC codes and show that the approximations to treat the non-locality of pseudopotentials are the primary source of the discrepancies between them. In particular, we demonstrate that, for the same choice of determinantal component in the trial wave function, reliable and reproducible predictions can be achieved by employing the T-move, the determinant locality approximation, or the determinant T-move schemes, while the older locality approximation leads to considerable variability in results. These findings demonstrate that, with appropriate choices of algorithmic details, fixed-node DMC is reproducible across diverse community codes—highlighting the maturity and robustness of the method as a tool for open and reliable computational science.

Della Pia, Flaviano [Univ. of Cambridge (United Ki↗
DOE OSTI2025

Structural insights into VRC01-class bnAb precursors with diverse light chains elicited in the IAVI G001 human vaccine trial

The development of germline-targeting vaccines represents a potentially transformative strategy to elicit broadly neutralizing antibodies (bnAbs) against HIV and other antigenically diverse pathogens. Here, we report on structural characterization of vaccine-elicited VRC01-class bnAb precursors in the IAVI G001 Phase 1 clinical trial with the eOD-GT8 60mer nanoparticle as immunogen. High-resolution X-ray structures of eOD-GT8 monomer complexed with Fabs of five VRC01-class bnAb precursors with >90% germline identity revealed a conserved mode of binding to the HIV CD4-binding site via IGHV1-2-encoded heavy chains, mirroring mature bnAb interactions. The light-chain V-gene diversity emulated VRC01 bnAbs and stabilized antigen engagement, while their conserved five-residue LCDR3 motifs prevented steric clashes. Notably, the VRC01-class bnAb precursors accommodated the N276 glycan, a key barrier in HIV Env recognition, through structural rearrangements in HCDR3 or LCDR1, despite its absence in the immunogen. Surface plasmon resonance analysis showed that 87% of elicited antibodies retained glycan binding capacity, albeit with reduced affinity. These findings validate the ability of eOD-GT8 60mer nanoparticles to prime VRC01-class bnAb precursors with native-like paratopes but with intrinsic glycan adaptability. Structural mimicry of mature bnAbs was observed even with limited somatic hypermutation, indicating that critical features are encoded in the germline repertoire. The structures highlight how germline-encoded features drive bnAb-like recognition at early stages. This work provides molecular evidence supporting germline targeting in humans and provides guidance for designing booster immunogens to shepherd affinity maturation toward broad neutralization.

Science & Technology - Other Topics↗