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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Synchrotron-based Infrared Microspectroscopy as a Useful Tool to Study Hydration States of Meteorite Constituents

The meteorites Dho 225 and Dho 735 were recently found in Oman. Studies of their mineralogical and chemical composition suggest that these unusual meteorites are thermally metamorphosed CM2 chondrites [1,2,3]. Similar to Antarctic metamorphosed carbonaceous chondrites, the Dho 225 and Dho 735 are enriched in heavy oxygen compared to normal CMs [1,2]. However, IR studies indicating dehydration of matrix phyllosilicates are needed to confirm that the two new meteorites from Oman are thermally metamorphosed [4]. Synchrotron-based IR microspectroscopy is a new promising technique which allows the acquisition of IR spectra from extremely small samples. Here we demonstrate that this non-destructive technique is a useful tool to study hydration states of carbonaceous chondrites in situ. In addition, we acquired reflectance spectra of bulk powders of the Dho 225 and Dho 735 in the range of 0.3-50 microns.

Moroz, L. V.↗
NASA NTRS2005

Modeling of Isotope Fractionation in Stratospheric CO2, N2O, CH4, and O3: Investigations of Stratospheric Chemistry and Transport, Stratosphere-Troposphere Exchange, and Their Influence on Global Isotope Budgets

Until recently, the stable isotopic composition of chemically and datively important stratospheric species, such as ozone (O3), carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4), was largely unexplored, despite indications from the few measurements available and theoretical studies that global-scale isotopic variations will provide a unique tool for quantifying rates of global-scale mass transport into, within, and out of the stratosphere and for understanding the mechanisms of chemical reactions involved in ozone production. The number and geographical extent of observations are beginning to increase rapidly, however, as access to the stratosphere, both directly and by remote-sensing, has increased over the last 10 years and as new analytical techniques have been developed that make global-scale isotope measurements by whole-air sampling more feasible. The objective of this study, begun in April 1999, is to incorporate into the Livermore 2D model the likely photochemical fractionation processes that determine the isotopic compositions of stratospheric CO2, N2O, CH4, and O3, and to use the model results and new observations from NASA field campaigns in 1996 and 1997 to investigate stratospheric chemistry and mass transport. Additionally, since isotopic signatures from the stratosphere are transferred to the troposphere by downward transport at middle and high latitudes, the isotopic compositions may also serve as sensitive tracers of stratosphere-totroposphere transport. Comparisons of model results with stratospheric and upper tropospheric observations from these campaigns, as well as with ground-based observations from new NOAA and NSF-sponsored studies, will help determine whether the magnitudes of the stratospheric fractionation processes are large enough to use as global-scale tracers of transport into the troposphere and, if so, will be used to help constrain the degree of coupling between the troposphere and the stratosphere.

Boering, Kristie A.↗
DOE OSTI2025

Application of Electrochemical Methods to Molten Salt Reactors: Draft TLR Documenting Assessment of Electrochemical Monitoring

Nuclear Regulatory Commission (NRC) is developing the regulatory framework and technical expertise to support regulatory review of advanced non-water reactors, including molten salt reactors (MSRs). In an MSR, it is essential that the salt chemistry be maintained in a desired range in terms of redox potential for reliable operation and mitigation of corrosion to structural materials in the reactor, particularly the reactor vessel and heater exchanger. Measuring the redox potential of the salt in the reactor would also allow for the material lifetimes to be predicted more accurately, and chemical issues to be diagnosed more quickly. In addition to the chemical composition analysis by ICP-MS, electrochemical methods including potentiometry and linear wave scanning (LSC) were also used in molten salt reactor experiment (MSRE) for redox potential monitoring purposes. Electrochemcial methods offers unique advantages such as quick turnaround in results and unique capability of in-line monitoring of redox potential, and are considered popular electroanalytical techniques that can be used to monitor redox potentials and salt chemistry including impurities. The last two decades have seen significant advances in science and engineering of electrochemical methods for potential application to molten salts. The primary goal of this report is to assist NRC in understanding the monitoring of the salt chemistry by electrochemical methods and provide NRC reviewers with necessary information and tools to support regulatory review of MSR designs. This reports consists of two majors parts—Part 1, chemical potential of molten salts and effects by fission process in MSR; Part 2, assessment of electrochemical methods for application to MSRs. The TRLs of the typical relevant electrochemical methods for molten salts were evaluated based on the DOE TRL guidelines and upon a review of the current status of the electrochemical methods for two typical salt systems, fluoride and chloride, for MSRs.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Optical spectroscopy and modeling of uranium gas-phase oxidation: Progress and perspectives

We report that studies related to U gas-phase oxidation through plasma- and thermo-chemistry are important for many fields, including environmental monitoring, forensic analysis, debris analysis in a weapon detonation event, and nucleation physics. Recently, significant efforts have been made to understand the chemical pathways involved in the progression from U atoms to diatoms (UO) and polyatomic molecules (UxOy), employing optical spectroscopy tools and computational modeling. In many studies, laser ablation of U or a U-containing flow reactor are used as a highly resource-efficient, repeatable, tunable, and lab-scale testbed for studying gas-phase oxidation in U plasmas. The spectroscopic analysis of high-temperature gas-phase oxidation of U is challenging due to the congested U spectra, resolution limitations of instrumentation, and the numerous chemical reaction pathways possible. This article focuses on the current understanding and challenges related to studying U plasma chemistry, specifically U gas-phase oxidation and molecular formation, via optical spectroscopy of plasmas and associated computational and spectral modeling. The physical and chemical processes involved in the evolution from U atoms to U oxide molecules to nanoparticles and agglomerates (i.e., debris) are discussed in the context of optical spectroscopic studies. The article concludes by highlighting opportunities for future research efforts based on existing knowledge published in the literature.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Approaches to genetic tool development for rapid domestication of non-model microorganisms

Abstract Non-model microorganisms often possess complex phenotypes that could be important for the future of biofuel and chemical production. They have received significant interest the last several years, but advancement is still slow due to the lack of a robust genetic toolbox in most organisms. Typically, “domestication” of a new non-model microorganism has been done on an ad hoc basis, and historically, it can take years to develop transformation and basic genetic tools. Here, we review the barriers and solutions to rapid development of genetic transformation tools in new hosts, with a major focus on Restriction-Modification systems, which are a well-known and significant barrier to efficient transformation. We further explore the tools and approaches used for efficient gene deletion, DNA insertion, and heterologous gene expression. Finally, more advanced and high-throughput tools are now being developed in diverse non-model microbes, paving the way for rapid and multiplexed genome engineering for biotechnology.

09 BIOMASS FUELS↗
DOE OSTI2022

Ch3MS-RF: a random forest model for chemical characterization and improved quantification of unidentified atmospheric organics detected by chromatography–mass spectrometry techniques

Abstract. The chemical composition of ambient organic aerosols plays a critical role in driving their climate and health-relevant properties and holds important clues to the sources and formation mechanisms of secondary aerosol material. In most ambient atmospheric environments, this composition remains incompletely characterized, with the number of identifiable species consistently outnumbered by those that have no mass spectral matches in the literature or the National Institute of Standards and Technology/National Institutes of Health/Environmental Protection Agency (NIST/NIH/EPA) mass spectral databases, making them nearly impossible to definitively identify. This creates significant challenges in utilizing the full analytical capabilities of techniques which separate and generate spectra for complex environmental samples. In this work, we develop the use of machine learning techniques to quantify and characterize novel, or unidentifiable, organic material. This work introduces Ch3MS-RF (Chemical Characterization by Chromatography–Mass Spectrometry Random Forest Modeling), an open-source, R-based software tool, for efficient machine-learning-enabled characterization of compounds separated in chromatography–mass spectrometry applications but not identifiable by comparison to mass spectral databases. A random forest model is trained and tested on a known 130 component representative external standard to predict the response factors of novel environmental organics based on position in volatility–polarity space and mass spectrum, enabling the reproducible, efficient, and optimized quantification of novel environmental species. Quantification accuracy on a reserved 20 % test set randomly split from the external standard compound list indicates that random forest modeling significantly outperforms the commonly used methods in both precision and accuracy, with a median response factor percent error of −2 %, for modeled response factors, compared to > 15 %, for typically used proxy assignment-based methods. Chemical properties modeling, evaluated on the same reserved 20 % test set and an extrapolation set of species identified in ambient organic aerosol samples collected in the Amazon rainforest, also demonstrate robust performance. Extrapolation set property prediction mean absolute errors for carbon number, oxygen to carbon ratio (O : C), average carbon oxidation state (OSc‾), and vapor pressure are 1.8, 0.15, 0.25, and 1.0 (log(atm)), respectively. Extrapolation set out-of-sample R2 for all properties modeled are above 0.75, with the exception of vapor pressure. While predictive performance for vapor pressure is less robust compared to the other chemical properties modeled, random-forest-based modeling was significantly more accurate than other commonly used methods of vapor pressure prediction, decreasing the mean vapor pressure prediction error to 0.24 (log(atm)) from 0.55 (log(atm)) (chromatography-based vapor pressure prediction) and 1.2 (log(atm)) (chemical formula-based vapor pressure prediction). The random forest model significantly advances an untargeted analysis of the full scope of chemical speciation yielded by two-dimensional gas chromatography (GCxGC-MS) techniques and can be applied to gas chromatography coupled with electron ionization mass spectrometry (GC-MS) as well. It enables the accurate estimation of key chemical properties commonly utilized in the atmospheric chemistry community, which may be used to more efficiently identify important tracers for further individual analysis and to characterize compound populations uniquely formed under specific ambient conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Latent Mechanisms of Polarization Switching from In Situ Electron Microscopy Observations

In situ scanning transmission electron microscopy enables observation of the domain dynamics in ferroelectric materials as a function of externally applied bias and temperature. The resultant data sets contain a wealth of information on polarization switching and phase transition mechanisms. However, identification of these mechanisms from observational data sets has remained a problem due to a large variety of possible configurations, many of which are degenerate. Here, an approach based on a combination of deep learning-based semantic segmentation, rotationally invariant variational autoencoder (VAE), and non-negative matrix factorization to enable learning of a latent space representation of the data with multiple real-space rotationally equivalent variants mapped to the same latent space descriptors is introduced. By varying the size of training sub-images in the VAE, the degree of complexity in the structural descriptors is tuned from simple domain wall detection to the identification of switching pathways. Importantly, this yields a powerful tool for the exploration of the dynamic data in mesoscopic electron, scanning probe, optical, and chemical imaging. Moreover, this work adds to the growing body of knowledge of incorporating physical constraints into the machine and deep-learning methods to improve learned descriptors of physical phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Noncentrosymmetric Triangular Magnet CaMnTeO 6 : Strong Quantum Fluctuations and Role of s 0 versus s 2 Electronic States in Competing Exchange Interactions

Abstract Noncentrosymmetric triangular magnets offer a unique platform for realizing strong quantum fluctuations. However, designing these quantum materials remains an open challenge attributable to a knowledge gap in the tunability of competing exchange interactions at the atomic level. Here, a new noncentrosymmetric triangular S = 3/2 magnet CaMnTeO 6 is created based on careful chemical and physical considerations. The model material displays competing magnetic interactions and features nonlinear optical responses with the capability of generating coherent photons. The incommensurate magnetic ground state of CaMnTeO 6 with an unusually large spin rotation angle of 127°(1) indicates that the anisotropic interlayer exchange is strong and competing with the isotropic interlayer Heisenberg interaction. The moment of 1.39(1) µB , extracted from low‐temperature heat capacity and neutron diffraction measurements, is only 46% of the expected value of the static moment 3 µB . This reduction indicates the presence of strong quantum fluctuations in the half‐integer spin S = 3/2 CaMnTeO 6 magnet, which is rare. By comparing the spin‐polarized band structure, chemical bonding, and physical properties of AMnTeO 6 ( A = Ca, Sr, Pb), how quantum‐chemical interpretation can illuminate insights into the fundamentals of magnetic exchange interactions, providing a powerful tool for modulating spin dynamics with atomically precise control is demonstrated.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The Transient Covalent Bond in Abiotic Nonequilibrium Systems

Abstract Biochemical systems accomplish many critical functions with by operating out‐of‐equilibrium using the energy of chemical fuels. The formation of a transient covalent bond is a simple but very effective tool in designing analogous reaction networks. This Minireview focuses on the fuel chemistries that have been used to generate transient bonds in recent demonstrations of abiotic nonequilibrium systems (i.e., systems that do not make use of biological components). Fuel reactions are divided into two fundamental classifications depending on whether the fuel contributes structural elements to the activated state, a distinction that dictates how they can be used. Reported systems are further categorized by overall fuel reaction (e.g., hydrolysis of alkylating agents, carbodiimide hydration) and illustrate how similar chemistry can be used to effect a wide range of nonequilibrium behavior, ranging from self‐assembly to the operation of molecular machines.

Kariyawasam, Lasith S.↗
DOE OSTI2026

Three pairs of fungal Trametes strains isolated from distinct geographic origins show conserved genomic features and adaptive response to plant biomass

The genomes of white-rot fungi hold extended repertoires of enzymes active on virtually all the chemical bonds that intertwine lignocellulose polymers, and several Trametes species have been identified as powerful tools for biorefinery or bioremediation. However, only few studies have addressed the intra-species polymorphism one would expect from fungal strains collected in contrasted environments. We compared the genome sequence of pairs of strains collected in different geographic areas, for each of three fungal species. Using an updated list of the predicted functions for fungal ligno- and cellulolytic enzymes (CAZymes), we observed a high conservation of the gene repertoires among the six strains. We compared the adaptative response of the fungi grown on crystalline cellulose, wheat straw, aspen or pine sawdust by transcriptomics and secretomics. The gene regulation profiles were determined by the species and the substrates, rather than the strain. The secretomes did not show marked differences in the sets of secreted CAZymes after 3 day-growth on the substrates. We identified five transcription factor genes and two sesquiterpenoid synthesis genes induced during growth on lignocellulose. Wider studies using larger sets of strains will be necessary to evaluate the genericity of our findings, and to assess the phenotype diversity one could expect from geographic diversity as compared to taxonomic diversity in Trametes fungi.

Drula, E. [French National Research Institute for ↗
DOE OSTI2026

Dynamic Nuclear Polarization Enhanced 113 Cd Solid-State Nuclear Magnetic Resonance Spectroscopy Reveals CdSe Nanocrystals with Triangular Two-Dimensional Projections are Terminated by {100} Facets

Surface structure plays an important role in particle growth and determining the chemical and photophysical properties of semiconductor nanocrystals (NCs). Therefore, there is a need for structural tools that can characterize and detect different surface facets. Here, we sought to investigate the structure of {111} CdSe facets by applying dynamic nuclear polarization (DNP) enhanced 113 Cd and 77 Se solid-state nuclear magnetic resonance (SSNMR) spectroscopy to zinc-blende CdSe NCs that exhibit triangular two-dimensional (2D) projections within transmission electron microscope (TEM) images. It was originally hypothesized in the literature that these CdSe NCs were tetrahedral in shape and terminated by facets from the {111} family of lattice planes of the zinc-blende structure. Surprisingly, we observe 113 Cd NMR spectra indicating that the primary facets are from the {100} family of lattice planes. We also obtained DNP-enhanced 113 Cd and 77 Se SSNMR spectra of recently reported right trigonal bipyramidal (rTriBP) CdSe NCs grown by seeded growth. The 113 Cd NMR spectra rTriBP CdSe NCs are consistent with {100} surface facets. TEM images show that rTriBP NCs may also exhibit triangular 2D projections that are similar to the so-called tetrahedral NCs. Based upon these results, we conclude that the so-called tetrahedral NCs are predominantly terminated by {100} surface facets and most likely have the same shape as rTriBP NCs. These results highlight the need for multiple complementary techniques when assigning the shape and surface termination of NCs.

Santhiran, Anuluxan [Ames Laboratory (AMES), Ames,↗
DOE OSTI2024

An artificial intelligence accelerated virtual screening platform for drug discovery

Abstract Structure-based virtual screening is a key tool in early drug discovery, with growing interest in the screening of multi-billion chemical compound libraries. However, the success of virtual screening crucially depends on the accuracy of the binding pose and binding affinity predicted by computational docking. Here we develop a highly accurate structure-based virtual screen method, RosettaVS, for predicting docking poses and binding affinities. Our approach outperforms other state-of-the-art methods on a wide range of benchmarks, partially due to our ability to model receptor flexibility. We incorporate this into a new open-source artificial intelligence accelerated virtual screening platform for drug discovery. Using this platform, we screen multi-billion compound libraries against two unrelated targets, a ubiquitin ligase target KLHDC2 and the human voltage-gated sodium channel Na V 1.7. For both targets, we discover hit compounds, including seven hits (14% hit rate) to KLHDC2 and four hits (44% hit rate) to Na V 1.7, all with single digit micromolar binding affinities. Screening in both cases is completed in less than seven days. Finally, a high resolution X-ray crystallographic structure validates the predicted docking pose for the KLHDC2 ligand complex, demonstrating the effectiveness of our method in lead discovery.

Science & Technology - Other Topics↗
DOE OSTI2021

Monolignol acyltransferase for lignin p-hydroxybenzoylation in Populus

Plant lignification exhibits significant plasticity. Lignin in many species including Populus spp. has long been known decorated with p-hydroxybenzoates. However, the molecular basis for such structural modification remains undetermined. Here we report the identification and characterization of a Populus BAHD family acyltransferase that catalyzes monolignol p-hydroxybenzoylation, thus controlling the formation of p-hydroxybenzoylated lignin structures. We reveal that Populus acyltransferase PHBMT1 kinetically preferentially utilizes p-hydroxybenzoyl-CoA to acylate syringyl lignin monomer sinapyl alcohol in vitro. Consistently, disrupting PHBMT1 in Populus via CRISPR/Cas9 gene editing nearly completely depletes p-hydroxybenzoates of stem lignin; conversely, overexpression of PHBMT1 enhances stem lignin p-hydroxybenzoylation, suggesting PHBMT1 functions as a prime monolignol p-hydroxybenzoyltransferase in planta. Altering lignin p-hydroxybenzoylation significantly changes lignin solvent dissolution rate, indictive of its structural significance on lignin physiochemical properties. Identification of monolignol p-hydroxybenzoyltransferase offers a valuable tool for tailoring lignin structure and physiochemical properties and for engineering the industrially important platform chemical in woody biomass.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

VIPIR: A High-Throughput Drop-Weight Impact Instrument for Imaging the Initiation and Propagation of Reactions in Energetic Materials

Characterizing the handling safety and sensitivity of explosives has been a challenging area of study for over 60 years. Historically one of the most accessible and widely utilized experiments has been the drop-weight impact test, which involves dropping a weight on a small sample sandwiched between two anvils. Because this experiment generally only utilizes sound thresholds to determine whether or not a sample reacted, the physical and chemical properties governing sensitivity remain convolved. Better understanding of chemical and material characteristics is needed to give the chemistry and engineering communities a predictive tool to determine the handling sensitivity of explosives prior to pursuing expensive and potentially hazardous synthesis and formulation operations. Here, we are developing a high throughput drop tower instrument capable of imaging the deformation and flow of energetic materials during impact and the resulting thermal ignition and propagation events. This instrument is based on previous designs but has been modified for higher throughput and tailorable modifications in the future. Herein, we present key design features that enable high-speed visible and thermal imaging of explosive initiation by sub-shock impacts, as well as preliminary results in which ignition sites were observed in an erythritol tetranitrate sample.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

A parameter sensitivity study for simulating DNA damage after proton irradiation using TOPAS-nBio

Monte Carlo (MC) track structure simulation tools are commonly used for predicting radiation induced DNA damage by modeling the physical and chemical reactions at the nanometer scale. However, the outcome of these MC simulations is particularly sensitive to the adopted parameters which vary significantly across studies. In this study, a previously developed full model of nuclear DNA was used to describe the DNA geometry. The TOPAS-nBio MC toolkit was used to investigate the impact of physics and chemistry models as well as three key parameters (the energy threshold for direct damage, the chemical stage time length, and the probability of damage between hydroxyl radical reactions with DNA) on the induction of DNA damage. Our results show that the difference in physics and chemistry models alone can cause differences up to 34% and 16% in the DNA double strand break (DSB) yield, respectively. Additionally, changing the direct damage threshold, chemical stage length, and hydroxyl damage probability can cause differences of up to 28%, 51%, and 71% in predicted DSB yields, respectively, for the configurations in this study.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2005

Modeling and Visualizing Flow of Chemical Agents Across Complex Terrain

Release of chemical agents across complex terrain presents a real threat to homeland security. Modeling and visualization tools are being developed that capture flow fluid terrain interaction as well as point dispersal downstream flow paths. These analytic tools when coupled with UAV atmospheric observations provide predictive capabilities to allow for rapid emergency response as well as developing a comprehensive preemptive counter-threat evacuation plan. The visualization tools involve high-end computing and massive parallel processing combined with texture mapping. We demonstrate our approach across a mountainous portion of North California under two contrasting meteorological conditions. Animations depicting flow over this geographical location provide immediate assistance in decision support and crisis management.

Kao, David↗
NASA NTRS2017

An Overview of Atmospheric Chemistry and Air Quality Modeling

This presentation will include my personal research experience and an overview of atmospheric chemistry and air quality modeling to the participants of the NASA Student Airborne Research Program (SARP 2017). The presentation will also provide examples on ways to apply airborne observations for chemical transport (CTM) and air quality (AQ) model evaluation. CTM and AQ models are important tools in understanding tropospheric-stratospheric composition, atmospheric chemistry processes, meteorology, and air quality. This presentation will focus on how NASA scientist currently apply CTM and AQ models to better understand these topics. Finally, the importance of airborne observation in evaluating these topics and how in situ and remote sensing observations can be used to evaluate and improve CTM and AQ model predictions will be highlighted.

Atmospheric↗
NASA NTRS2022

Using an Explainable Machine Learning Approach to Characterize Earth System Model Errors: Application of SHAP Analysis to Modeling Lightning Flash Occurrence

Computational models of the Earth System are critical tools for modern scientific inquiry. Effortstoward evaluating and improving errors in representations of physical and chemical processes inthese large computational systems are commonly stymied by highly nonlinear and complexerror behavior. Recent work has shown that these errors can be effectively predicted usingmodern Artificial Intelligence (A.I.) techniques. In this work, we go beyond these previousstudies to apply an interpretable A.I. technique to not only predict model errors but also movetoward understanding the underlying reasons for successful error prediction. We use XGBoostclassification trees and SHapley Additive exPlanations (SHAP) analysis to explore the errors inthe prediction of lightning occurrence in the NASA GEOS model, a widely used Earth SystemModel. This explainable error prediction system can effectively predict the model error andindicates that the errors are strongly related to convective processes and the characteristics ofthe land surface.

Artificial intelligence↗