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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Topological Insulators versus Topological Dirac Semimetals in Honeycomb Compounds

Intriguing physical properties of materials stem from their chemical constituents, whereas the connection between them is often not clear. Here, we uncover a general chemical classification for the two quantum phases in the honeycomb ABX structure—topological insulator (TI) and topological Dirac semimetal (TDSM). First, we find among the 816 (existing as well as hypothetical) calculated compounds, 160 TIs (none were noted before), 96 TDSMs, 282 normal insulators (NIs), and 278 metals. Second, based on this classification, we have distilled a simple chemical regularity based on compound formulas for the selectivity between TI and TDSM: the ABX compounds that are TDSM have B atoms (part of the BX honeycomb layers) that come from the periodic table columns XI (Cu, Ag, Au) or XII (Zn, Cd, Hg), or Mg (group II), whereas the ABX compounds whose B at-oms come from columns I (Li, Na, K, Rb, Cs) or II (Ca, Sr, Ba) are TIs. Third, focusing on the ABX bismide compounds that are thermodynamically stable, we find a structural motif that delivers topological insulation and stability at the same time. Furthermore, this study opens the way to simultaneously design new topological materials based on the compositional rules indicated here.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2008

What We Might Know About Gusev Crater if the Mars Exploration Rover Spirit Mission were Coupled with a Mars Sample Return Mission

The science instruments on the Mars Exploration Rover (MER) Spirit have provided an enormous amount of chemical and mineralogical data during more than 1450 sols of exploration at Gusev crater. The Moessbauer (MB) instrument identified 10 Fe-bearing phases at Gusev Crater: olivine, pyroxene, ilmenite, chromite, and magnetite as primary igneous phases and nanophase ferric oxide (npOx), goethite, hematite, a ferric sulfate, and pyrite/marcusite as secondary phases. The Miniature Thermal Emission Spectrometer (Mini-TES) identified some of these Fe-bearing phases (olivine and pyroxene), non- Fe-bearing phases (e.g., feldspar), and an amorphous high-SiO2 phase near Home Plate. Chemical data from the Alpha Particle X-Ray Spectrometer (APXS) provided the framework for rock classification, chemical weathering/alteration, and mineralogical constraints. APXS-based mineralogical constraints include normative calculations (with Fe(3+)/FeT from MB), elemental associations, and stoichiometry (e.g., 90% SiO2 implicates opalline silica). If Spirit had cached a set of representative samples and if those samples were returned to the Earth for laboratory analysis, what value is added by Mars Sample return (MSR) over and above the mineralogical and chemical data provided by MER?

Morris, Richard V.↗
DOE OSTI2024

Accurate, Uncertainty-Aware Classification of Molecular Chemical Motifs from Multimodal X-ray Absorption Spectroscopy

Accurate classification of molecular chemical motifs from experimental measurement is an important problem in molecular physics, chemistry, and biology. In this work, we present neural network ensemble classifiers for predicting the presence (or lack thereof) of 41 different chemical motifs on small molecules from simulated C, N, and O K-edge X-ray absorption near-edge structure (XANES) spectra. Our classifiers not only achieve class-balanced accuracies of more than 0.95 but also accurately quantify uncertainty. Here, we also show that including multiple XANES modalities improves predictions notably on average, demonstrating a “multimodal advantage” over any single modality. In addition to structure refinement, our approach can be generalized to broad applications with molecular design pipelines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1986

Airborne trace contaminants of possible interest in CELSS

One design goal of Closed Ecological Life Support Systems (CELSS) for long duration space missions is to maintain an atmosphere which is healthy for all the desirable biological species and not deleterious to any of the mechanical components in that atmosphere. CELESS design must take into account the interactions of at least six major components; (1) humans and animals, (2) higher plants, (3) microalgae, (4) bacteria and fungi, (5) the waste processing system, and (6) other mechanical systems. Each of these major components can be both a source and a target of airborne trace contaminants in a CELSS. A range of possible airborne trace contaminants is discussed within a chemical classification scheme. These contaminants are analyzed with respect to their probable sources among the six major components and their potential effects on those components. Data on airborne chemical contaminants detected in shuttle missions is presented along with this analysis. The observed concentrations of several classes of compounds, including hydrocarbons, halocarbons, halosilanes, amines and nitrogen oxides, are considered with respect to the problems which they present to CELSS.

Garavelli, J. S.↗
DOE OSTI2022

Comparative chemical genomic profiling across plant-based hydrolysate toxins reveals widespread antagonism in fitness contributions

Abstract The budding yeast Saccharomyces cerevisiae has been used extensively in fermentative industrial processes, including biofuel production from sustainable plant-based hydrolysates. Myriad toxins and stressors found in hydrolysates inhibit microbial metabolism and product formation. Overcoming these stresses requires mitigation strategies that include strain engineering. To identify shared and divergent mechanisms of toxicity and to implicate gene targets for genetic engineering, we used a chemical genomic approach to study fitness effects across a library of S. cerevisiae deletion mutants cultured anaerobically in dozens of individual compounds found in different types of hydrolysates. Relationships in chemical genomic profiles identified classes of toxins that provoked similar cellular responses, spanning inhibitor relationships that were not expected from chemical classification. Our results also revealed widespread antagonistic effects across inhibitors, such that the same gene deletions were beneficial for surviving some toxins but detrimental for others. This work presents a rich dataset relating gene function to chemical compounds, which both expands our understanding of plant-based hydrolysates and provides a useful resource to identify engineering targets.

09 BIOMASS FUELS↗
NASA NTRS2010

A Cabonaceous Chondrite Dominated Lithology from the HED Parent; PRA 04401

The paired howardite breccias Mt. Pratt (PRA) 04401 and PRA 04402 are notable for their high proportion of carbonaceous chondrite clasts [1]. They consist predominantly of coarse (0.1-7 mm) diogenite (orthopyroxene), eucrite (plagioclase + pyroxene), and carbonaceous chondrite clasts set in a finer grained matrix of these same materials. Coarse C-chondrite clasts up to 7 mm are composed mainly of fine-grained phyllosilicates with lesser sulfides and high-mg# anhydrous magnesian silicates. Most of these clasts appear to be texturally consistent with CM2 classification [1] and some contain relict chondrules. The clasts are angular and reaction or alteration textures are not apparent in the surrounding matrix. PRA 04401 contains about 70 modal% C-chondrite clasts while PRA 04402 contains about 7%. Although many howardites are known to contain abundant C-chondrite clasts [2,3,4], PRA 04401 is, to our knowledge, the most chondrite-rich howardite lithology identified to date. Low EPMA totals from CM2-type clasts in other howardites suggest that they frequently contain 10 wt% or more water [2], a figure consistent with their mineralogy. PRA 04401, therefore, demonstrates the potential for hydrous lithologies with greater than 5 wt% water to occur locally within the nominally anhydrous HED parent body. Since the origin of this water is xenogenic, it might therefore be concentrated in portions of the asteroid surface where it would be more readily observable by remote sensing techniques. We plan to further examine C-chondrite clasts in PRA 04401/2 with the intent of establishing firm chemical classification, estimating water content, and evaluating their relationship with the host breccia. To help place them in context of the HED parent, we will also compare these breccias with other howardites to evaluate which lithologies are likely to be more prevalent on the asteroid surface.

Herrin, Jason S.↗
DOE OSTI2025

ChemEcho v1.0

ChemEcho is a tool that converts tandem mass spectra into embeddings used to build machine learning (ML) models with fully explainable predictions. It provides an API for transforming raw tandem mass spectral data into embeddings, along with functions for training and validating ML models. Additionally, it includes utilities for retrieving and cleaning training data. ChemEcho is broadly applicable in ML pipelines that use tandem mass spectra for a variety of tasks, such as chemical classification or bioactivity mining. While there are existing methods to generate embeddings from fragmentation data, ChemEcho's approach ensures that predictions remain interpretable, enabling experts to evaluate results and generate hypotheses about the underlying data.

Harwood, Thomas [Lawrence Berkeley National Labora↗
NASA NTRS1991

Studies of volatiles and organic materials in early terrestrial and present-day outer solar system environments

A review and partial summary of projects within several areas of research generally involving the origin, distribution, chemistry, and spectral/dielectric properties of volatiles and organic materials in the outer solar system and early terrestrial environments are presented. The major topics covered include: (1) impact delivery of volatiles and organic compounds to the early terrestrial planets; (2) optical constants measurements; (3) spectral classification, chemical processes, and distribution of materials; and (4) radar properties of ice, hydrocarbons, and organic heteropolymers.

Sagan, Carl↗
NASA NTRS1997

Stardust to Planetesimals: A Chondrule Connection?

The unique nature of chondrules has been known for nearly two centuries. Modern techniques of analysis have shown that these millimeter sized silicate objects are among the oldest objects in our solar system. Researchers have devised textural and chemical classification systems for chondrules in an effort to determine their origins. It is agreed that most chondrules were molten at some point in their history, and experimental analogs suggest that the majority of chondrules formed from temperatures below 1600 C at cooling rates in the range of hundreds of degrees per hour. Although interstellar grains are present in chondrite matrices, their contribution as precursors to chondrule formation is unknown. Models for chondrule formation focus on the pre-planetary solar nebula conditions, although planetary impact models have had proponents.

Paque, Julie↗
DOE OSTI2019

Classification of local chemical environments from x-ray absorption spectra using supervised machine learning

We report that x-ray absorption spectroscopy is a premier element-specific technique for materials characterization. Specifically, the x-ray absorption near-edge structure (XANES) encodes important information about the local chemical environment of an absorbing atom, including coordination number, symmetry, and oxidation state. Interpreting XANES spectra is a key step towards understanding the structural and electronic properties of materials, and as such, extracting structural and electronic descriptors from XANES spectra is akin to solving a challenging inverse problem. Existing methods rely on empirical fingerprints, which are often qualitative or semiquantitative and not transferable. In this paper, we present a machine learning-based approach, which is capable of classifying the local coordination environments of the absorbing atom from simulated K-edge XANES spectra. The machine learning classifiers can learn important spectral features in a broad energy range without human bias and once trained, can make predictions on the fly. The robustness and fidelity of the machine learning method are demonstrated by an average 86% accuracy across the wide chemical space of oxides in eight 3d transition-metal families. Lastly, we found that spectral features beyond the preedge region play an important role in the local structure classification problem especially for the late 3d transition-metal elements.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Hazardous Chemical Inventory Guidelines, Purpose, and Process

The Environment, Safety, and Health Planning department at Sandia National Laboratories is interested in the purchase and storage of chemicals and their potential impact following an uncontrolled release. The large number of projects conducted at SNL make tracking every chemical purchase impractical; therefore, attention is focused on hazardous substances purchased in large quantities. Chemicals and quantities of concern are determined through regulatory guidelines; e.g., the OSHA Process Safety Management list, the EPA Risk Management Plan list, and the Department of Energy Subcommittee on Consequence Assessment and Protective Actions Emergency Response Planning Guidelines. Based on these regulations, a list of chemicals with quantities of concern was created using the Aerial Locations of Hazardous Atmospheres (ALOHA) and SCREEN View chemical dispersion modelling software. The nature of this report does not draw conclusions, rather it documents the logic for a chemicals of concern list to ensure compliance with various regulations and form the basis for monitoring chemicals that may affect hazard classification. Hazardous Chemical Inventory Guidelines, Purpose, and Process 4 This page left blank.

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

SERS-based ssDNA composition analysis with inhomogeneous peak broadening and reservoir computing

Surface-enhanced Raman spectroscopy employed in conjunction with post-processing machine learning methods is a promising technique for effective data analysis, allowing one to enhance the molecular and chemical composition analysis of information rich DNA molecules. In this work, we report on a room temperature inhomogeneous broadening as a function of the increased adenine concentration and employ this feature to develop one-dimensional and two dimensional chemical composition classification models of 200 long single stranded DNA sequences. Afterwards, we develop a reservoir computing chemical composition classification scheme of the same molecules and demonstrate enhanced performance that does not rely on manual feature identification.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Active sampling of volatile chemicals for non-invasive classification of chicken eggs by sex early in incubation

According to industry estimates, approximately 7 billion day-old male chicks are disposed of annually worldwide because they are not of use to the layer industry. A practical process to identify the sex of the egg early in incubation without penetrating the egg would improve animal welfare, reduce food waste and mitigate environmental impact. We implemented a moderate vacuum pressure system through commercial egg-handling suction cups to collect volatile organic compounds (VOCs). Three separate experiments were set up to determine optimal conditions to collect eggs VOCs to discriminate male from female embryos. Optimal extraction time (2 min), storage conditions (short period of incubation during egg storage (SPIDES) at days 8–10 of incubation), and sampling temperature (37.5°C) were determined. Our VOC-based method could correctly differentiate male from female embryos with more than 80% accuracy. These specifications are compatible with the design of specialized automation equipment capable of high-throughput, in-ovo sexing based on chemical sensor microchips.

Borras, Eva↗
DOE OSTI2013

Physical Properties of Chemicals in PAC Revision 27 Listing

1 Purpose The purpose of this chemical physical property listing is to provide data required to apply the DOE SCAPA Protective Action Criteria (PAC) values to calculation of the LLNL Quantity (Q) Value thresholds for facility chemical hazard classification.

99 GENERAL AND MISCELLANEOUS↗