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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The MolSSI QCArchive project: An open-source platform to compute, organize, and share quantum chemistry data

The Molecular Sciences Software Institute's (MolSSI) Quantum Chemistry Archive (QCArchive) project is an umbrella name that covers both a central server hosted by MolSSI for community data and the Python-based software infrastructure that powers automated computation and storage of quantum chemistry (QC) results. The MolSSI-hosted central server provides the computational molecular sciences community a location to freely access tens of millions of QC computations for machine learning, methodology assessment, force-field fitting, and more through a Python interface. Facile, user-friendly mining of the centrally archived quantum chemical data also can be achieved through web applications found at the website. The software infrastructure can be used as a standalone platform to compute, structure, and distribute hundreds of millions of QC computations for individuals or groups of researchers at any scale. The QCArchiveInfrastructure is open-source (BSD-3C), code repositories can be found at github, and releases can be downloaded via PyPI and Conda. This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods Software > Quantum Chemistry Data Science > Computer Algorithms and Programming

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Strategies for community-sourced biocuration in bioinformatics: a case study on MIBiG 4.0

Biocuration is essential to transform molecular sequence data into standardized, machine-readable resources. Such curated datasets enable comparative analysis, predictive modeling, and data integration across bioinformatics platforms. While professional biocuration is resource-intensive and usually limited to institutional settings, community-driven approaches can mobilize large-scale annotation of specialized datasets and are more resilient to disruptions in scientific funding. Here, we present a model for community-powered curation applied to the Minimum Information about a Biosynthetic Gene Cluster (MIBiG) repository. Through a framework of workflows for metadata capture, annotation validation, and contributor coordination, the MIBiG 4.0 initiative recruited 267 scientists across 178 institutions from 33 countries, volunteering an estimated 4000 h of work. These efforts expanded the MIBiG repository by 22% and enhanced its usability in downstream molecular data analyses in comparative genomic analyses, natural product discovery, and machine learning applications. We provide strategies and actionable lessons for adopting this model, supporting the sustainability of curated bioinformatics resources central to nucleic acid research and related fields.

biocuration↗
NASA NTRS1992

158 micrometers (CII) mapping of the Orion molecular cloud

Data from the inner regions of the Orion nebula in the 157.7409 micrometers (CII) fine structure line is investigated. Large scale strip maps in (CII) across the face of the Orion molecular cloud, and CO spectra at selected positions in the Orion HII region/molecular cloud interface were obtained. The total (CII) luminosity from the Orion molecular cloud is estimated to be approximately 1500 of the solar luminosity or 0.3 of the far infrared luminosity. The overall properties of the Orion molecular cloud deduced are: the photodissociated gas to molecular gas mass fraction, the (CII) line to far infrared continuum intensity ratio and the (CII)/CO(12) (1 to 0) line intensity ratio are the same for the Orion molecular cloud and the nuclei of non-starburst galaxies. The observations provide an important link between (CII) emission from galactic molecular clouds and the nuclei of external galaxies.

Stacey, G. J.↗
NASA NTRS1983

Modeling correlation with flight data

The molecular contamination flow model (space 2 program) predicts the induced environment of the space shuttle orbiter/payload on orbit as well as the induced gas flow between the orbiter and payload surfaces. This computer program relates the input parameters which characterize the time dependent status of the orbiter/payload to the required output parameters. An application of the model to data from space transportation system flights 1, 2, and 3 shows that the model correlates well for direct flow and for return flux (STS-2/H2O). Correlation for return flux from other molecular sources/species appears to be within expectations but more analysis is required. The space 2 model seems to be an adequate predictive tool.

Ehlers, H. K. F.↗
DOE OSTI2024

Multitask methods for predicting molecular properties from heterogeneous data

Data generation remains a bottleneck in training surrogate models to predict molecular properties. We demonstrate that multitask Gaussian process regression overcomes this limitation by leveraging both expensive and cheap data sources. In particular, we consider training sets constructed from coupled-cluster (CC) and density functional theory (DFT) data. We report that multitask surrogates can predict at CC-level accuracy with a reduction in data generation cost by over an order of magnitude. Of note, our approach allows the training set to include DFT data generated by a heterogeneous mix of exchange–correlation functionals without imposing any artificial hierarchy on functional accuracy. More generally, the multitask framework can accommodate a wider range of training set structures—including the full disparity between the different levels of fidelity—than existing kernel approaches based on Δ-learning although we show that the accuracy of the two approaches can be similar. Consequently, multitask regression can be a tool for reducing data generation costs even further by opportunistically exploiting existing data sources.

Chemistry↗
NASA NTRS1977

Interstellar clouds and molecular hydrogen

Data obtained from the Copernicus Orbiting Astronomical Observatory, launched in 1972 and still obtaining information, are used in a discussion of the interstellar medium. The Copernicus instruments have facilitated direct estimates for the density and temperature of individual interstellar clouds, and improved the ability to determine where along the line of sight a cloud lies with respect to background stars. The physical characteristics of hydrogen molecules are considered, with attention to the formation and destruction of interstellar hydrogen. The differences between 'thin' clouds, in which molecular hydrogen is optically thin, and 'thick' clouds are examined. Several features of the interstellar medium are described.

Jura, M.↗
DOE OSTI2020

Integrating solvation shell structure in experimentally driven molecular dynamics using x-ray solution scattering data

In the past few decades, prediction of macromolecular structures beyond the native conformation has been aided by the development of molecular dynamics (MD) protocols aimed at exploration of the energetic landscape of proteins. Yet, the computed structures do not always agree with experimental observables, calling for further development of the MD strategies to bring the computations and experiments closer together. Here, we report a scalable, efficient MD simulation approach that incorporates an x-ray solution scattering signal as a driving force for the conformational search of stable structural configurations outside of the native basin. We further demonstrate the importance of inclusion of the hydration layer effect for a precise description of the processes involving large changes in the solvent exposed area, such as unfolding. Utilization of the graphics processing unit allows for an efficient all-atom calculation of scattering patterns on-the-fly, even for large biomolecules, resulting in a speed-up of the calculation of the associated driving force. The utility of the methodology is demonstrated on two model protein systems, the structural transition of lysine-, arginine-, ornithine-binding protein and the folding of deca-alanine. We discuss how the present approach will aid in the interpretation of dynamical scattering experiments on protein folding and association.

Hsu, Darren J.↗
NASA NTRS2011

Technical Tension Between Achieving Particulate and Molecular Organic Environmental Cleanliness: Data from Astromaterial Curation Laboratories

NASA Johnson Space Center operates clean curation facilities for Apollo lunar, Antarctic meteorite, stratospheric cosmic dust, Stardust comet and Genesis solar wind samples. Each of these collections is curated separately due unique requirements. The purpose of this abstract is to highlight the technical tensions between providing particulate cleanliness and molecular cleanliness, illustrated using data from curation laboratories. Strict control of three components are required for curating samples cleanly: a clean environment; clean containers and tools that touch samples; and use of non-shedding materials of cleanable chemistry and smooth surface finish. This abstract focuses on environmental cleanliness and the technical tension between achieving particulate and molecular cleanliness. An environment in which a sample is manipulated or stored can be a room, an enclosed glovebox (or robotic isolation chamber) or an individual sample container.

Allton, J. H.↗
DOE OSTI2020

Beaver Creek Soil Incubation Experiment July 2018

The data accompanies the manuscript Antecedent conditions determine the biogeochemical response of coastal soils to seawater exposure" that evaluates impact of periodic seawater inundations of soils from in a first-order coastal watershed in the Olympic Peninsula of Washington state, USA. Samples were collected in July 2018 and subjected to laboratory incubations. The files contain a read me file, data files including soil chemical characteristics, FTICR-MS molecular and data file, FTICR-MS derived processed data from FREDA, reference file for transformation analysis, LC-MS derived molecular feature abundance data, gas flux data for multiple regression and R codes. The files are related to the publication and have been used in the results and analyses section.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Machine Learning-Based Classification of Lignocellulosic Biomass from Pyrolysis-Molecular Beam Mass Spectrometry Data

High-throughput analysis of biomass is necessary to ensure consistent and uniform feedstocks for agricultural and bioenergy applications and is needed to inform genomics and systems biology models. Pyrolysis followed by mass spectrometry such as molecular beam mass spectrometry (py-MBMS) analyses are becoming increasingly popular for the rapid analysis of biomass cell wall composition and typically require the use of different data analysis tools depending on the need and application. Here, the authors report the py-MBMS analysis of several types of lignocellulosic biomass to gain an understanding of spectral patterns and variation with associated biomass composition and use machine learning approaches to classify, differentiate, and predict biomass types on the basis of py-MBMS spectra. Py-MBMS spectra were also corrected for instrumental variance using generalized linear modeling (GLM) based on the use of select ions relative abundances as spike-in controls. Machine learning classification algorithms e.g., random forest, k-nearest neighbor, decision tree, Gaussian Naïve Bayes, gradient boosting, and multilayer perceptron classifiers were used. The k-nearest neighbors (k-NN) classifier generally performed the best for classifications using raw spectral data, and the decision tree classifier performed the worst. After normalization of spectra to account for instrumental variance, all the classifiers had comparable and generally acceptable performance for predicting the biomass types, although the k-NN and decision tree classifiers were not as accurate for prediction of specific sample types. Gaussian Naïve Bayes (GNB) and extreme gradient boosting (XGB) classifiers performed better than the k-NN and the decision tree classifiers for the prediction of biomass mixtures. The data analysis workflow reported here could be applied and extended for comparison of biomass samples of varying types, species, phenotypes, and/or genotypes or subjected to different treatments, environments, etc. to further elucidate the sources of spectral variance, patterns, and to infer compositional information based on spectral analysis, particularly for analysis of data without a priori knowledge of the feedstock composition or identity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Equilibrium carbon isotope fractionation factors of hydrocarbons: Semi-empirical force-field method

Here, we have calculated the reduced partition function ratios for carbon isotopes (β-factor) of 67 hydrocarbons (alkanes, alkenes, alkynes, cycloalkanes, and aromatics), including their 267 single-substituted isotopomers. The calculations were performed using the harmonic oscillator – rigid rotator model and the Urey / Bigeleisen-Mayer approach. Normal frequencies of molecular vibrations of the isotopologues were calculated from the molecular structures data and valence field force constants stored in the Light-handled Elucidation of Vibrations (LEV) database elaborated by Dr. Gribov and his colleagues in Russia. The LEV database is constructed from experimental spectroscopic and structural data by solving inverse problems of molecular vibrations. The LEV is internally consistent and the most comprehensive database available to date. The β-factor were calculated in the temperature range of 200–800 K with a 10 K step. Our calculations predict that the β-factors increase with an increasing number of C atoms within the same groups of hydrocarbons (e.g., alkanes). Our calculations also show a general descending order of 13 C enrichments among the different groups of hydrocarbons: cycloalkanes, aromatics, alkenes (double bonds) and isoalkanes, alkanes, alkynes (triple bonds). Position-specific, intramolecular isotope effects within hydrocarbons are determined by the β-factors of C in the different functional groups in the order: quaternary (C), tertiary (methine, CH), secondary (methylene, CH 2 ), primary (methyl, CH 3 ) and double bond (C=C), saturated bond (C - C), triple bond (HC≡). Our calculations on bulk and position-specific carbon isotope β-factors of the hydrocarbons, which are generally consistent with very limited ab initio calculations in the literature, are internally consistent and the most comprehensive to date for future applications to position-specific isotope geochemistry of hydrocarbons.

58 GEOSCIENCES↗
NASA NTRS1985

Submillimeter observations of OH and CH in M42

The (sup 2) pi sub 1/2 (J = 3/2 to 1/2) transitions of OH at 163.12 and 163.40 micro m have been detected and upper limits have been obtained for the (sup 2) pi sub 3/2 (J = 3/2 to 1/2) transitions of CH at 149.09 and 149.39 micro m, in observations of the Kleinmann-Low Nebula of Orion. All four flux levels lie between 1 and 1.2 x 10 to the 17th power/sq.cm. The OH lines are bright when compared to the lower, (sup 2) pi sub 3/2 (J = 5/2 to 3/2) fluxes reported and imply that the 119 micro m emission observed is partially self-absorbed. The combined results provide strong constraints. Taken together with existing data on molecular hydrogen and CO and recent data on other OH transition, they suggest OH emission from post-shock regions at temperatures T approx 1000 k, densities approx. 7 x 10 to the 6th powr/cu cm N sub OH approx 80/cu cm optically thick for the (sup 2) pi sub 3/2 (J = 5/2 to 3/2), 119 micro m but only partially self-absorbing in the (J = 7/2 to 3/2), 84 micro m transitions over a Doppler velocity bandwidth of 30 km/sec. The OH column density is N sub OH approx 4 x 10 to the 16th powr/sq cm. in the emitting regions which occupy a fraction of approx 0.1 of a 1' x 1' field of view centered on the Becklin-Neugebauer source. The CO (J = 31 to 30), 84 micro m transition appears to lie sufficiently close to one of the 84 micro m OH line components to be partially absorbed as well, through a Bowen-type mechanism.

Viscuso, P. J.↗
DOE OSTI2022

Data-driven design of molecular nanomagnets

Three decades of research in molecular nanomagnets have raised their magnetic memories from liquid helium to liquid nitrogen temperature thanks to a wise choice of the magnetic ion and coordination environment. Still, serendipity and chemical intuition played a main role. In order to establish a powerful framework for statistically driven chemical design, here we collected chemical and physical data for lanthanide-based nanomagnets, catalogued over 1400 published experiments, developed an interactive dashboard (SIMDAVIS) to visualise the dataset, and applied inferential statistical analysis. Our analysis shows that the Arrhenius energy barrier correlates unexpectedly well with the magnetic memory. Furthermore, as both Orbach and Raman processes can be affected by vibronic coupling, chemical design of the coordination scheme may be used to reduce the relaxation rates. Indeed, only bis-phthalocyaninato sandwiches and metallocenes, with rigid ligands, consistently present magnetic memory up to high temperature. Analysing magnetostructural correlations, we offer promising strategies for improvement, in particular for the preparation of pentagonal bipyramids, where even softer complexes are protected against molecular vibrations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Modeling Adsorption in Silica Pores via Minkowski Functionals and Molecular Electrostatic Moments

Capillary condensation phenomena are important in various technological and environmental processes. Using molecular simulations, we study the confined phase behavior of fluids relevant to carbon sequestration and shale gas production. As a first step toward translating information from the molecular to the pore scale, we express the thermodynamic potential and excess adsorption of methane, nitrogen, carbon dioxide, and water in terms of the pore’s geometric properties via Minkowski functionals. This mathematical reconstruction agrees very well with molecular simulations data. Our results show that the fluid molecular electrostatic moments are positively correlated with the number of adsorption layers in the pore. Moreover, stronger electrostatic moments lead to adsorption at lower pressures. These findings can be applied to improve pore-scale thermodynamic and transport models.

42 ENGINEERING↗
DOE OSTI2021

Replication Data for: Evolution of Metastable Structures at Bimetallic Surfaces from Microscopy and Machine-Learning Molecular Dynamics

The data underlying this published work have been made publicly available in this repository as part of the IMASC Data Management Plan. This work was supported as part of the Integrated Mesoscale Architectures for Sustainable Catalysis (IMASC), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award # DE-SC0012573.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Inelastic, exchange, and reactive processes in rovibrationally excited collisions of HD with H

ABSTRACT The HD molecule is an important coolant in early universe chemistry models and a tracer of H2 in star-forming regions. Rate coefficients for collisional excitation and de-excitation of HD rotational and vibrational levels form important ingredients in astrophysical models. While collisions with He, H2, and H are the most important, available data for H + HD collisions are largely limited to temperatures less than 1000 K for the vibrational ground state, low-lying rotational levels of the v = 1 HD vibrational level, or computed without reactive contributions. Here, through explicit quantum scattering calculations, we report extensive data for rovibrational transitions in HD induced by H atoms for a range of rotational levels in v = 1 and some v = 0 levels for temperatures up to 1000 K. The significance of the computed results for astrophysical modeling is discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Are permafrost microorganisms as old as permafrost?

ABSTRACT Permafrost describes the condition of earth material (sand, ground, organic matter, etc.) cemented by ice when its temperature remains at or below 0°C continuously for longer than 2 years. Evidently, permafrost is as old as the time passed from freezing of the earth material. Permafrost is a unique phenomenon and may preserve life forms it encloses. Therefore, in order to talk confidently about the preservation of paleo-objects in permafrost, knowledge about the geological age of sediments, i.e. when the sediments were formed, and permafrost age, when those sediments became permanently frozen, is essential. There are two types of permafrost—syngenetic and epigenetic. The age of syngenetic permafrost corresponds to the geological age of its sediments, whereas the age of epigenetic permafrost is less than the geological age of its sediments. Both of these formations preserve microorganisms and their metabolic products; however, the interpretations of the microbiological and molecular-biological data are inconsistent. This paper reviews the current knowledge of time–temperature history and age of permafrost in relation to available microbiological and metagenomic data.

59 BASIC BIOLOGICAL SCIENCES↗