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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A novel framework for increasing research transparency: Exploring the connection between diversity and innovation

A split sample/dual method research protocol is demonstrated to increase transparency while reducing the probability of false discovery. We apply the protocol to examine whether diversity in ownership teams increases or decreases the likelihood of a firm reporting a novel innovation using data from the 2018 United States Census Bureau’s Annual Business Survey. Transparency is increased in three ways: 1) all specification testing and identifying potentially productive models is done in an exploratory subsample that 2) preserves the validity of hypothesis test statistics fromde novoestimation in the holdout confirmatory sample with 3) all findings publicly documented in an earlier registered report and in this journal publication. Bayesian estimation procedures that leverage information from the exploratory stage included in the confirmatory stage estimation replace traditional frequentist null hypothesis significance testing. In addition to increasing statistical power by using information from the full sample, Bayesian methods directly estimate a probability distribution for the magnitude of an effect, allowing much richer inference. Estimated magnitudes of diversity along academic discipline, race, ethnicity, and foreign-born status dimensions are positively associated with innovation. A maximally diverse ownership team on these dimensions would be roughly six times more likely to report new-to-market innovation than a homophilic team.

Science & Technology - Other Topics↗
NASA NTRS1973

Polar volatiles on Mars - Theory versus observation

Synthesis of the results of the Mariner 9 mission, as they pertain to polar volatiles, and comparison of them with a description of the solid-vapor equilibrium relations believed to be presently active on Mars. The discovery by Mariner 9 of extensive volcanic deposits on portions of the Martian surface suggests that the total amount of CO2 liberated to the surface probably exceeds that now present in the atmosphere. Thus excess CO2 in the solid form is to be expected in the polar areas. Although the simplified model of Leighton and Murray (1966), which predicts a permanent CO2 cap, has significant deficiencies both theoretically and observationally, the seasonal caps are composed of CO2, as predicted, excess CO2 is quite likely, and a permanent deposit of solid CO2 evidently is in equilibrium with atmospheric CO2. It is suggested that there must be a large reservoir of solid CO2 in gaseous equilibrium with the atmosphere, but buried immediately below the exposed residual water-ice cap. This reservoir is believed to be located near the north pole. The principal effect of such a reservoir is to average out annual and longer-term fluctuations in the polar heat balance.

Murray, B. C.↗
NASA NTRS1977

Infrared studies of star formation

Infrared observations at wavelengths of a few microns to 1 mm are reviewed which pertain to the problem of star formation. The data considered include observations of large gas and dust clouds within which stars may be forming and detailed studies of individual objects within these clouds. Stages of star formation are outlined, the IR luminosity of forming stars is examined, and criteria for selecting interstellar regions for IR studies are discussed along with the importance of dust in the IR energy distributions of star-formation regions. Detailed results, including IR maps, are evaluated for the Orion Molecular Cloud 1 (OMC-1), W3, OMC-2, Mon R2, RCW 57, M17, CRL 2591, and NGC 7538. Some general properties of star-formation regions are summarized, and observational techniques for IR astronomy are described. It is noted that the discovery of possible pre-main-sequence (PMS) objects in the densest central portions of larger clouds supports the generally accepted premise of gravitational collapse as the driving mechanism for the star-formation process and that the observed properties of possible PMS objects agree qualitatively with the predictions of detailed models based on gravitational collapse.

Werner, M. W.↗
NASA NTRS1981

Nonthermal hard X-ray emission from the nucleus of NGC 1275

Observations confirming the HEAO 1 discovery of a hard X-ray component in the X-ray spectrum of the Perseus cluster are reported. A comparison of the results with 1978 HEAO 1 observations and 1974 balloon limits shows that this component is variable on a time scale of one year. Synchrotron self-Compton models of the compact radio source centered on the nucleus of NGC 1275 predict a substantial secondary X-ray flux based on the observed radio data. While the observed X-ray flux is one-fourth the predicted value, uncertainties in the radio data are sufficient to account for the discrepancy. It is concluded that the hard X-ray flux originates in the active nucleus of the Seyfert galaxy NGC 1275 through the synchrotron self-Compton process.

Rothschild, R. E.↗
NASA NTRS1982

Radio emission from AM Herculis-type binaries

A VLA search for 4.9 GHz radiation from the magnetic cataclysmic variable AM Her, along with the similar EF Eri binary, has led to the discovery of AM Her radio emission having a flux density of 0.67 + or - 0.052 mJy, where 1 mJy is equal to 10 to the -29th W/sq m per Hz. Neither AM Her circular polarization nor EF Eri were detected. The AM Her data are shown to be consistent with a model in which radiation is due to geosynchrotron emission from electrons of energies of a few hundred keV, which are trapped in the magnetosphere of the white dwarf element of the cataclysmic variable.

Chanmugam, G.↗
NASA NTRS1999

Discovery of a New Soft Gamma Repeater, SGR 1627-41

We report the discovery of a new soft gamma repeater (SGR), SGR 1627-41, and present BATSE observations of the burst emission and BeppoSAX Narrow-Field Instrument observations of the probable persistent X-ray counterpart to this SGR. All but one burst spectrum are well fit by an optically thin thermal bremsstrahlung model with kT values between 25 and 35 keV. The spectrum of the X-ray counterpart, SAX J1635.8-4736, is similar to that of other persistent SGR X-ray counterparts. We find weak evidence for a periodic signal at 6.41 s in the light curve for this source. Like other SGRs, this source appears to be associated with a young supernova remnant, G337.0-0.1. Based upon the peak luminosities of bursts observed from this SGR, we find a lower limit on the dipole magnetic field of the neutron star of B(sub dipole) approximately > 5 x 10(exp 14) G.

Woods, Peter M.↗
NASA NTRS2021

NuSTAR reveals the hidden nature of SS433

SS433 is the only Galactic binary system known to persistently accrete at highly super-critical (or hyper-critical) rates, similar to those in tidal disruption events, and likely needed to explain the rapid growth of those very high redshift quasars containing massive SMBHs. Probing the inner regions of SS433 in the X-rays is crucial to understanding this system, and super-critical accretion in general, but is highly challenging due to obscuration by the surrounding wind, driven from the accretion flow. NuSTAR observed SS433 in the hard X-ray band across multiple phases of its 162 day super-orbital precession period. Spectral-timing tools allow us to infer that the hard X-ray emission from the inner regions is likely being scattered towards us by the walls of the wind-cone. By comparing to numerical models, we determine an intrinsic X-ray luminosity of >= 2 x 10^37 erg/s and that, if viewed face on, we would infer an apparent luminosity of > 1 x 10^39 erg/s, confirming SS433’s long-suspected nature as an ultraluminous X-ray source (ULX). We present the discovery of a narrow, ~ 100 s lag due to atomic processes occurring in outflowing material travelling at least 0.14-0.29c, which matches absorption lines seen in ULXs and – in the future – will allow us to map a super-critical outflow for the first time.

M J Middleton↗
NASA NTRSDate not supplied

Expanding Repository Data Available For Sharing And Knowledge Discovery

Some of the hardest space biology and space health challenges require data-intensive, bioinformatic, meta-analytical, and computer-assisted research approaches. These challenges include examining interdisciplinary space life science research across experiments and across interacting spaceflight hazards (radiation, altered gravity, confinement, hostile-closed environments, distance-duration from Earth). The approaches to confront these challenges involve mining multiple datasets simultaneously from various hierarchical organizations of biological complexity, all while concurrently evaluating how experimental design factors affect endpoints of standard assays. To enable this field, it is essential that principal investigators (PIs) submit data in a structure so it can be maximally re-used. The purpose of the NASA Ames Life Sciences Data Archive (ALSDA) is to collect, curate, and make publicly available all non-human space-relevant biological data. ALSDA must also ensure data are open-access, and maximally findable, accessible, interoperable, and reusable (FAIR). The scope of ALSDA data collected and submitted by PIs include subject and study design metadata, assay metadata parameters, raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). ALSDA recently integrated into a collaborative group of Open Science projects to facilitate a suite of new tools and workflows that will improve data submission, accessibility, and reusability by implementing digital data submission agreements, and adopting the data management system originally developed by NASA GeneLab. ALSDA intends to bring current biological repository data and all future collected data into this new scientific data reuse reality. This new suite of tools will enable ALSDA to deploy a science curation system using scientific assay configurations for the data submission portal. It will capture essential assay parameters according to established standards in each sub-field within biology. The submission portal expedites data collection by enhancing ease of PI data submission, providing a user interface and specificity for which data is to be submitted. Data submissions can be brought into cutting-edge informatic analysis portals to enable mining of physiological, behavioral, biochemical, and imaging datasets in conjunction with ‘omics-level datasets. As ALSDA datasets are submitted, curated, and published (e.g., micro-computed tomography, histology, pulse oximetry, serum metabolites, magnetic resonance imaging, intraocular pressure, novel object recognition, etc.), the merging together of spaceflight data along this multi-hierarchical complexity of biology will enable informatics and data-intensive approaches resulting in knowledge discoveries across missions, space hazards, and biological disciplines.

life science↗
DOE OSTI2022

DOE new players Carbon cycle (2016-2021)

The overarching scientific goals of our multidisciplinary grant was to further expand understanding about the key microorganisms (players), metabolic strategies (processes), and interspecies relationships (interactions) involved in the formation and oxidation of methane in the environment. This research applied novel environmental metagenomics, transcriptomics, and proteomic techniques, state-of-the-art analytical imaging, stable isotope geochemistry, and reaction-transport modeling to address these goals and develop an ‘ecosystems level’ understanding of the factors which regulate microbial methane cycling in anoxic sedimentary ecosystems. For decades, it was believed that the obligate step in methanogenesis catalyzed by methyl coenzyme M reductase (Mcr) was limited to a specific branch of the archaeal Domain, formerly known as the Euryarchaeota. Less than a decade ago co-I Tyson’s team published a surprising metagenomic-based discovery of divergent Mcr genes in a novel uncultured phylum (Bathyarchaeota), catalyzing a major shift in thinking about the diversity of microorganisms that encode the potential for methane (or higher alkane) metabolism in anoxic environments (Evans et al., 2015). In our work here, we further expand on the groups of archaea harboring the genomic potential for methane or hydrocarbon metabolism using environmental metagenomics and new gene targeted bioinformatics techniques. We additionally advanced understanding about the terminal electron acceptors and metabolic potential supporting the anaerobic oxidation of methane (AOM) in terrestrial ecosystems, specifically focused on new lineages of ANME archaea capable of respiring manganese oxides with methane presumably using large extracellular multi-heme cytochrome complexes. New details about specific syntrophic mechanisms underlying the exchange of electrons during sulfate-coupled methane oxidation between ANME-2 archaea and their sulfate-reducing bacterial partners were also elucidated as part of this funded project. Through a series of experimental ‘omics and single cell stable isotope probing studies with incubated environmental sediment samples and a cultured model electrogenic microorganism combined with model-based predictions. Combined, this work provides strong support for the hypothesis of direct interspecies electron transfer (DIET) is the dominant syntrophic mechanism controlling the anaerobic oxidation of methane with sulfate over other proposed mechanisms and additionally illustrates important spatial constraints and the underlying physico-chemical factors influencing AOM syntrophic consortia structure for DIET and extracellular metal respiration. This collaborative multi-institutional project successfully advanced several of our milestone goals including the identification of new microbial players containing methyl coenzyme M reductases hypothesized to be central to methane or hydrocarbon cycling in anoxic environments and enhancing fundamental knowledge about the role extracellular electron transfer plays in the ecophysiology of methanotrophic archaea respiring metal oxides and in the physical and metabolic structuring of syntrophic interactions in methane-rich sedimentary ecosystems.

03 NATURAL GAS↗
NASA NTRS2010

RXTE Observations of the 1A 1118-61 in an Outburst, and the Discovery of a Cyclotron Line

We present the analysis of RXTE monitoring data obtained during the January 2009 outburst of the hard X-ray transient IA 1118-61. Using these observations the broadband (3.5-120 keV) spectrum of the source was measured for the first time ever. We have found that the broadband continuum spectrum of the source is similar to other accreting pulsars and is well described by several conventionally used phenomenological models. We have discovered that regardless of the applied continuum model, a prominent broad absorption feature at approx. 55 keV is observed. We interpret this feature as a Cyclotron Resonance Scattering Feature (CRSF). The observed CRSF energy is one of the highest known and corresponds to a magnetic field of B approx. 4.8 x 10(exp 12) G in the scattering region. Furthermore, our data suggests an iron emission line presence, which was not reported previously for lA 1118-61 as well. Timing properties of the source, including a strong spin-up, were found to be similar to those observed by CGRO/BATSE during the previous outburst, however the broadband capabilities of RXTE reveal a more complicated energy dependency of the pulse-profile.

Doroshenko, V.↗
DOE OSTI2025

Combining MicroED and native mass spectrometry for structural discovery of enzyme–small molecule complexes

With the goal of accelerating the discovery of small molecule–protein complexes, we leverage fast, low-dose, event-based electron counting microcrystal electron diffraction (MicroED) data collection and native mass spectrometry. This approach, which we term electron diffraction with native mass spectrometry (ED-MS), allows assignment of protein target structures bound to ligands with data obtained from crystal slurries soaked with mixtures of known inhibitors and crude biosynthetic reactions. This extends to libraries of printed ligands dispensed directly onto TEM grids for later soaking with microcrystal slurries, and complexes with noncovalent ligands. ED-MS resolves structures of the natural product, epoxide-based cysteine protease inhibitor E-64, and its biosynthetic analogs bound to the model cysteine protease, papain. It further identifies papain binding to its preferred natural products, by showing that two analogs of E-64 outcompete others in binding to papain crystals, and by detecting papain bound to E-64 and an analog from crude biosynthetic reactions, without purification. ED-MS also resolves binding of the CTX-M-14 β-lactamase, a target of active drug development, to the non-β-lactam inhibitor, avibactam, alone or in a cocktail of unrelated compounds. These results illustrate the utility of ED-MS for natural product ligand discovery and for structure-based screening of small molecule binders to macromolecular targets, promising utility for drug discovery.

MicroED↗
DOE OSTI2023

Two-Dimensional Energy Histograms as Features for Machine Learning to Predict Adsorption in Diverse Nanoporous Materials

A major obstacle for machine learning (ML) in chemical science is the lack of physically informed feature representations that provide both accurate prediction and easy interpretability of the ML model. In this work, we describe adsorption systems using novel two-dimensional energy histogram (2D-EH) features, which are obtained from the probe-adsorbent energies and energy gradients at grid points located throughout the adsorbent. The 2D-EH features encode both energetic and structural information of the material and lead to highly accurate ML models (coefficient of determination R2 ~ 0.94–0.99) for predicting single-component adsorption capacity in metal–organic frameworks (MOFs). Here, we consider the adsorption of spherical molecules (Kr and Xe), linear alkanes with a wide range of aspect ratios (ethane, propane, n-butane, and n-hexane), and a branched alkane (2,2-dimethylbutane) over a wide range of temperatures and pressures. The interpretable 2D-EH features enable the ML model to learn the basic physics of adsorption in pores from the training data. We show that these MOF-data-trained ML models are transferrable to different families of amorphous nanoporous materials. We also identify several adsorption systems where capillary condensation occurs, and ML predictions are more challenging. Nevertheless, our 2D-EH features still outperform structural features including those derived from persistent homology. The novel 2D-EH features may help accelerate the discovery and design of advanced nanoporous materials using ML for gas storage and separation in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

An autonomous laboratory for the accelerated synthesis of novel materials

To close the gap between the rates of computational screening and experimental realization of novel materials, we introduce the A-Lab, an autonomous laboratory for the solid-state synthesis of inorganic powders. This platform uses computations, historical data from the literature, machine learning (ML) and active learning to plan and interpret the outcomes of experiments performed using robotics. Over 17 days of continuous operation, the A-Lab realized 41 novel compounds from a set of 58 targets including a variety of oxides and phosphates that were identified using large-scale ab initio phase-stability data from the Materials Project and Google DeepMind. Synthesis recipes were proposed by natural-language models trained on the literature and optimized using an active-learning approach grounded in thermodynamics. Analysis of the failed syntheses provides direct and actionable suggestions to improve current techniques for materials screening and synthesis design. The high success rate demonstrates the effectiveness of artificial-intelligence-driven platforms for autonomous materials discovery and motivates further integration of computations, historical knowledge and robotics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Toward implementing autonomous adaptive data acquisition for scanning hyperspectral imaging of biological systems

Autonomous experimentation is an emerging area of research, primarily related to autonomous vehicles, scientific combinatorial discovery approaches in materials science and drug discovery, and iterative research loops of planning, experimentation, and analysis. However, autonomous approaches developed in these contexts are difficult to apply to high-dimensional mapping technologies, such as scanning hyperspectral imaging of biological systems, due to sample complexity and heterogeneity. We briefly cover the history of adaptive sampling algorithms and surrogate modeling in order to define autonomous adaptive data acquisition as an objective-based, flexible building block for future biological imaging experimentation driven by intelligent infrastructure. We subsequently summarize the recent implementations of autonomous adaptive data acquisition (AADA) for scanning hyperspectral imaging, assess how these address the difficulties of autonomous approaches in hyperspectral imaging, and highlight the AADA design variation from a goal-oriented perspective. Finally, we present a modular AADA architecture that embeds AADA-driven flexible building blocks to address the challenge of time resolution for high-dimensional scanning hyperspectral imaging of nonequilibrium dynamical systems. In our example research-driven experimental design case, we propose an AADA infrastructure for time-resolved, noninvasive, and label-free scanning hyperspectral imaging of living biological systems. This AADA infrastructure can accurately target the correct state of the system for experimental workflows that utilize subsequent expensive, high-information-content analytical techniques.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Evolutionary engineering reveals amino acid substitutions in Ato2 and Ato3 that allow improved growth of Saccharomyces cerevisiae on lactic acid

ABSTRACT In Saccharomyces cerevisiae, the complete set of proteins involved in transport of lactic acid across the cell membrane has not been determined. In this study, we aimed to identify transport proteins not previously described to be involved in lactic acid transport via a combination of directed evolution, whole-genome resequencing and reverse engineering. Evolution of a strain lacking all known lactic acid transporters on lactate led to the discovery of mutated Ato2 and Ato3 as two novel lactic acid transport proteins. When compared to previously identified S. cerevisiae genes involved in lactic acid transport, expression of ATO3T284C was able to facilitate the highest growth rate (0.15 ± 0.01 h-1) on this carbon source. A comparison between (evolved) sequences and 3D models of the transport proteins showed that most of the identified mutations resulted in a widening of the narrowest hydrophobic constriction of the anion channel. We hypothesize that this observation, sometimes in combination with an increased binding affinity of lactic acid to the sites adjacent to this constriction, are responsible for the improved lactic acid transport in the evolved proteins.

Baldi, Nicolò↗
DOE OSTI2024

Field-controlled dynamics of skyrmions and monopoles

Magnetic monopoles, despite their ongoing experimental search as elementary particles, have inspired the discovery of analogous excitations in condensed matter systems. In chiral condensed matter systems, emergent monopoles are responsible for the onset of transitions between topologically distinct states and phases, such as in the case of transitions from helical and conical phase to A-phase comprising periodic arrays of skyrmions. By combining numerical modeling and optical characterizations, we describe how different geometrical configurations of skyrmions terminating at monopoles can be realized in liquid crystals and liquid crystal ferromagnets. We demonstrate how these complex structures can be effectively manipulated by external magnetic and electric fields. Furthermore, we discuss how our findings may hint at similar dynamics in other physical systems and their potential applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Unified feature association networks through integration of transcriptomic and proteomic data

High-throughput multi-omics studies and corresponding network analyses of multi-omic data have rapidly expanded their impact over the last 10 years. As biological features of different types (e.g. transcripts, proteins, metabolites) interact within cellular systems, the greatest amount of knowledge can be gained from networks that incorporate multiple types of -omic data. However, biological and technical sources of variation diminish the ability to detect cross-type associations, yielding networks dominated by communities comprised of nodes of the same type. We describe here network building methods that can maximize edges between nodes of different data types leading to integrated networks. We systematically rank several network inference methods and demonstrate that, in many cases, using a random forest method, GENIE3, produces the most integrated networks. This increase in integration does not come at the cost of accuracy as GENIE3 produces networks of approximately the same quality as the other network inference methods tested here. Using GENIE3, we also infer networks representing antibody-mediated Dengue virus cell invasion and receptor-mediated Dengue virus invasion. A number of functional pathways showed centrality differences between the two networks including genes responding to both GM-CSF and IL-4, which had a higher centrality value in an antibody-mediated vs. receptor-mediated Dengue network. Because a biological system involves the interplay of many different types of molecules, incorporating multiple data types into networks will improve their use as models of biological systems. The methods explored here are some of the first to specifically highlight and address the challenges associated with how such multi-omic networks can be assembled and how the greatest number of interactions can be inferred from different data types. The resulting networks can lead to the discovery of new host response patterns and interactions during viral infection, generate new hypotheses of pathogenic mechanisms and confirm disease associated mechanisms of disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Energy I-Corps Electron Beam (EB) Potential for International Trade of Logs

The purpose of this document is to capture the potential from Fermilab’s “Team EB Treement” at the DOE Energy I-Corps program. Energy I-Corps, a key initiative of the Office of Technology Transitions, pairs teams of researchers with industry mentors for an intensive two-month training where the researchers define technology value propositions, conduct customer discovery interviews, and develop viable market pathways for their technologies. The team was composed prior to the Energy I-Corp program; however, the program was a catalyst for education and information exchange between the team members and stakeholders, customers, and regulators. These exchanges were captured in the evolution of a Business Model Canvas (BMC) and a Value Proposition (VP). The BMC and VP underwent numerous transformations based on feedback from the conversations between members of the team and forest or agriculture industry stakeholders and the program instructors.

43 PARTICLE ACCELERATORS↗