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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Molecular structural dataset of lignin macromolecule elucidating experimental structural compositions

Abstract Lignin is one of the most abundant biopolymers in nature and has great potential to be transformed into high-value chemicals. However, the limited availability of molecular structure data hinders its potential industrial applications. Herein, we present the Lignin Structural (LGS) Dataset that includes the molecular structure of milled wood lignin focusing on two major monomeric units (coniferyl and syringyl), and the six most common interunit linkages (phenylpropane β-aryl ether, resinol, phenylcoumaran, biphenyl, dibenzodioxocin, and diaryl ether). The dataset constitutes a unique resource that covers a part of lignin’s chemical space characterized by polymer chains with lengths in the range of 3 to 25 monomer units. Structural data were generated using a sequence-controlled polymer generation approach that was calibrated to match experimental lignin properties. The LGS dataset includes 60 K newly generated lignin structures that match with high accuracy (~90%) the experimentally determined structural compositions available in the literature. The LGS dataset is a valuable resource to advance lignin chemistry research, including computational simulation approaches and predictive modelling.

Scientific data↗
DOE OSTI2022

The Influence of Environment on Post-Detonation Chemistry and Debris Formation (Abbreviated Final Report: 20-SI-006)

Predicting, responding to, or interpreting the chemical record preserved in debris derived from nuclear events can be challenging due to chemical fractionation. Chemical fractionation is where different species of the evolving radionuclide inventory segregate and/or are lost from the system over the timescales of debris formation. Both historic data and recent research suggest that the interaction and character of the local environment may exert controls on chemical fractionation by influencing the cooling and evolution of the associated fireball as well as the composition of the vapor term and resultant speciation. Prior to this work, an integrated platform permitting dynamic and concurrent consideration of physical and chemical evolution of early time post-detonation event environments did not exist. Our work merged historic data and experimental approaches to support development of a computational framework able to simulate fundamental processes (e.g., entrainment of local environment, oxidation chemistry, and cooling time scales) that may perturb the radionuclide inventory captured in post-detonation debris. Work with historic debris confirmed that entrained environmental material affect debris composition, structure, and radionuclide incorporation. Complementary work utilizing a readily controllable and tunable benchtop setup (a plasma flow reactor) simulated the late cooling of a nuclear fireball (e.g., T < 6000 K) and bounded the sensitivity of actinide speciation and particle size distribution to variations in oxygen concentration and cooling rates. Concurrent laser ablation and laser heating experiments were used to investigate the chemistry and physics of processes occurring in vaporized and/or rapidly heated actinides and other elements in the presence of oxygen. A more computationally efficient microphysical model was developed for predicting and evolving size distributions of particles forming from mixed vapor terms and simulating particle formation processes under a variety of extreme conditions. Continued study of historic nuclear event film confirmed that shockwave data and physics codes agree to within the uncertainty of the data. Good agreement was achieved for thermal emission from an airburst, however the paucity of low-temperature molecular opacity data for mixtures of air, bomb debris, entrained dirt, and water vapor complicate agreement for more elaborate scenarios. A multiphysics code (ALE3D) was modified to bring the necessary physics and chemistry, including these new data and insights, onto a single platform. Code development included improved initialization of large physical systems, modernization of chemistry capabilities, and modifications to enable inclusion of particle transport.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS1982

Thermal Structure of Jupiter and Saturn

Temperatures in the sensible regions of the atmospheres of the outer planets are quite cold. The temperature structures for Jupiter, Saturn, Uranus and Neptune, derived from the equilibrium models are presented in preparation. The vertical temperature profiles for Jupiter and Saturn, the molecular spectroscopic data which form the basis for this type of analysis, and the problems involved with these models for molecular absorption and with the recovery technique in general, are discussed. Results for Jupiter and Saturn from the Pioneer and Voyager infrared experiments are also presented.

Orton, G.↗
NASA NTRS2004

A molecular timescale of eukaryote evolution and the rise of complex multicellular life

BACKGROUND: The pattern and timing of the rise in complex multicellular life during Earth's history has not been established. Great disparity persists between the pattern suggested by the fossil record and that estimated by molecular clocks, especially for plants, animals, fungi, and the deepest branches of the eukaryote tree. Here, we used all available protein sequence data and molecular clock methods to place constraints on the increase in complexity through time. RESULTS: Our phylogenetic analyses revealed that (i) animals are more closely related to fungi than to plants, (ii) red algae are closer to plants than to animals or fungi, (iii) choanoflagellates are closer to animals than to fungi or plants, (iv) diplomonads, euglenozoans, and alveolates each are basal to plants+animals+fungi, and (v) diplomonads are basal to other eukaryotes (including alveolates and euglenozoans). Divergence times were estimated from global and local clock methods using 20-188 proteins per node, with data treated separately (multigene) and concatenated (supergene). Different time estimation methods yielded similar results (within 5%): vertebrate-arthropod (964 million years ago, Ma), Cnidaria-Bilateria (1,298 Ma), Porifera-Eumetozoa (1,351 Ma), Pyrenomycetes-Plectomycetes (551 Ma), Candida-Saccharomyces (723 Ma), Hemiascomycetes-filamentous Ascomycota (982 Ma), Basidiomycota-Ascomycota (968 Ma), Mucorales-Basidiomycota (947 Ma), Fungi-Animalia (1,513 Ma), mosses-vascular plants (707 Ma), Chlorophyta-Tracheophyta (968 Ma), Rhodophyta-Chlorophyta+Embryophyta (1,428 Ma), Plantae-Animalia (1,609 Ma), Alveolata-plants+animals+fungi (1,973 Ma), Euglenozoa-plants+animals+fungi (1,961 Ma), and Giardia-plants+animals+fungi (2,309 Ma). By extrapolation, mitochondria arose approximately 2300-1800 Ma and plastids arose 1600-1500 Ma. Estimates of the maximum number of cell types of common ancestors, combined with divergence times, showed an increase from two cell types at 2500 Ma to approximately 10 types at 1500 Ma and 50 cell types at approximately 1000 Ma. CONCLUSIONS: The results suggest that oxygen levels in the environment, and the ability of eukaryotes to extract energy from oxygen, as well as produce oxygen, were key factors in the rise of complex multicellular life. Mitochondria and organisms with more than 2-3 cell types appeared soon after the initial increase in oxygen levels at 2300 Ma. The addition of plastids at 1500 Ma, allowing eukaryotes to produce oxygen, preceded the major rise in complexity.

Evolution, Molecular↗
NASA NTRS2001

CAP: A Computer Code for Generating Tabular Thermodynamic Functions from NASA Lewis Coefficients

For several decades the NASA Glenn Research Center has been providing a file of thermodynamic data for use in several computer programs. These data are in the form of least-squares coefficients that have been calculated from tabular thermodynamic data by means of the NASA Properties and Coefficients (PAC) program. The source thermodynamic data are obtained from the literature or from standard compilations. Most gas-phase thermodynamic functions are calculated by the authors from molecular constant data using ideal gas partition functions. The Coefficients and Properties (CAP) program described in this report permits the generation of tabulated thermodynamic functions from the NASA least-squares coefficients. CAP provides considerable flexibility in the output format, the number of temperatures to be tabulated, and the energy units of the calculated properties. This report provides a detailed description of input preparation, examples of input and output for several species, and a listing of all species in the current NASA Glenn thermodynamic data file.

Zehe, Michael J.↗
NASA NTRS2002

CAP: A Computer Code for Generating Tabular Thermodynamic Functions from NASA Lewis Coefficients

For several decades the NASA Glenn Research Center has been providing a file of thermodynamic data for use in several computer programs. These data are in the form of least-squares coefficients that have been calculated from tabular thermodynamic data by means of the NASA Properties and Coefficients (PAC) program. The source thermodynamic data are obtained from the literature or from standard compilations. Most gas-phase thermodynamic functions are calculated by the authors from molecular constant data using ideal gas partition functions. The Coefficients and Properties (CAP) program described in this report permits the generation of tabulated thermodynamic functions from the NASA least-squares coefficients. CAP provides considerable flexibility in the output format, the number of temperatures to be tabulated, and the energy units of the calculated properties. This report provides a detailed description of input preparation, examples of input and output for several species, and a listing of all species in the current NASA Glenn thermodynamic data file.

Zehe, Michael J.↗
DOE OSTI2025

Scaling High-Resolution Soil Organic Matter Composition to Improve Predictions of Potential Soil Respiration Across the Continental United States

Despite the importance of microbial soil organic matter (SOM) respiration in regulating the flux of carbon between soils and the atmosphere, soil carbon cycling models remain primarily based on climate and soil properties, leading to large uncertainty in predictions. To address this knowledge gap, we analyzed high-resolution water-extractable SOM profiles from soil cores collected across the United States by the 1,000 Soils Pilot of the Molecular Observation Network. Our innovation lies in using machine learning to distill thousands of SOM formula into tractable units; and it enables integrating data from molecular measurements into soil respiration models. In surface soils, SOM chemistry provided better estimates of potential soil respiration than soil physicochemistry, and using them combined yielded the best prediction. Overall, we identify specific subsets of organic molecules that may improve predictions of global soil respiration and create a strong basis for developing new representations in process-based models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

An IRAS survey of the Taurus-Auriga molecular cloud

IRAS data are used to search for young premain-sequence stars not previously associated with molecular cloud cores in the Taurus-Auriga region. NIR photometry and optical spectroscopy suggest that many of the objects are young stars. The sample includes six new embedded sources with luminosities comparable to that of the average T Tauri star, suggesting that surveys for premain-sequence stars in the cloud are essentially complete for luminosities greater than 0.5 solar luminosities. A disagreement is found between accretion rates derived from the duration of the embedded phase and those derived from the bolometric luminosity. It is found that this disagreement may be reconciled if a star accretes most of its mass in a time that is short compared to the duration of the embedded phase or if the ages of T Tauri stars have been underestimated.

Kenyon, Scott J.↗
NASA NTRSDate not supplied

Fracture Prediction of Epoxy Resin using Morse Bond Potential Embedded in GAFF using Molecular Dynamics Simulations

A generic method is developed to investigate the fracture behavior of an epoxy resin using atomistic molecular (MD) dynamics simulations. The epoxy system consisted of the stoichiometric mixture of tetra-/tri-functional epoxies and di-functional hardener molecules and was cured with a step-growth crosslinking algorithm. A hybrid force field (hFF) in which Morse bond function were added in second generation-general Amber Force Field (GAFF2) was used to capture bond breaking of the crosslinked epoxy system under uniaxial deformation. The Morse bond parameters for covalent bonds in the crosslinked backbone were fit to dissociation curves computed by CASPT2/6-311+G**. After the systems in various crosslink densities were obtained and equilibrated, the full length of stress-strain (𝜎-𝜀) curve was produced including initial elastic regime, yielding, plastic flow, strain hardening, and progressive failure. We found that the hFF was effective in studying the dissociation of crosslinked polymers and understanding the failure mechanism. In the results, the hFF delivered the same elastic property obtained from the unmodified force field GAFF. The stress-strain curve, however, began to be distinct in the plastic regime due to broken covalent bonds capable of altering the tensile behavior. Once the stress reached maximum, it progressively decreased until the ultimate failure (𝜎=0). Since hFF employed the existing GAFF functions with including a minimal change of its bond potential, this approach is easier to perform and computationally more efficient for unveiling the fracture behavior of polymer materials at the molecular level than other approaches with reactive force fields. We expect this approach will be utilized to accelerate the material-by-design process for thermosets by incorporate data from molecular models.

Changwoon Jang↗
DOE OSTI2020

Development of a grain growth model for U 3 Si 2 using experimental data, phase field simulation and molecular dynamics

The purpose of this work is to develop a model for normal grain growth in U 3 Si 2 . The average grain boundary energy was determined from previously published molecular dynamics simulations. The grain growth kinetics were quantified at various temperatures by annealing nanocrystalline samples. Here, the mobility was determined by comparing phase field grain growth simulations to the experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A physics-informed operator regression framework for extracting data-driven continuum models

The application of deep learning toward discovery of data-driven models requires careful application of inductive biases to obtain a description of physics which is both accurate and robust. We present here a framework for discovering continuum models from high fidelity molecular simulation data. Our approach applies a neural network parameterization of governing physics in modal space, allowing a characterization of differential operators while providing structure which may be used to impose biases related to symmetry, isotropy, and conservation form. Here, we demonstrate the effectiveness of our framework for a variety of physics, including local and nonlocal diffusion processes and single and multiphase flows. For the flow physics we demonstrate this approach leads to a learned operator that generalizes to system characteristics not included in the training sets, such as variable particle sizes, densities, and concentration.

42 ENGINEERING↗
DOE OSTI2024

Data and scripts associated with: “Burn severity and vegetation type control phosphorus concentration, molecular composition, and mobilization”

This data package is associated with the publication “Burn severity and vegetation type control phosphorus concentration, molecular composition, and mobilization” published in European Geophysical Union - Biogeosciences (Barnes et al. 2025). This study investigates how phosphorus (P) biogeochemistry is altered by burn severity in contrasting types of vegetation chars. This data package documents the workflow used to process and generate the main figures and statistics in the manuscript. The R scripts reference minimally processed P nuclear magnetic resonance (P-NMR) and X-ray absorption near edge structure (P-XANES) data, as well as fully processed data including total elemental composition of the solid chars, total elemental composition of the char leachates (particulate and aqueous phases), and leachate aqueous phase molybdate reactive P concentration. These source data and associated metadata can be found on ESS-DIVE at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1894135 (Grieger et al. 2022; v3). Files and scripts included in this data package finish the processing workflow for P-NMR and P-XANES data. These data can be used to gain a better understanding of bulk chemical changes in chars and their leachates, as well as detailed molecular changes to P. This data package is associated with the GitHub repository found at https://github.com/river-corridors-sfa/rcsfa-RC3-BSLE_P. This data package is comprised of a “data” folder and a series of data processing and analysis scripts. Details on how to recreate the workflow can be found in the Critical Details section of the readme and the “workflow_readme.md” file. The file-level metadata file (file ending in “flmd.csv”) lists all files contained in this data package and descriptions for each. The data dictionary (file ending in “dd.csv”) describes all tabular data columns and their respective definitions and units.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Method for simultaneous characterization and expansion of reference libraries for small molecule identification

A variational autoencoder (VAE) has been developed to learn a continuous numerical, or latent, representation of molecular structure to expand reference libraries for small molecule identification. The VAE has been extended to include a chemical property decoder, trained as a multitask network, to shape the latent representation such that it assembles according to desired chemical properties. The approach is unique in its application to metabolomics and small molecule identification, focused on properties that are obtained from experimental measurements (m/z, CCS) paired with its training paradigm, which involves a cascade of transfer learning iterations. First, molecular representation is learned from a large dataset of structures with m/z labels. Next, in silico property values are used to continue training. Finally, the network is further refined by being trained with the experimental data. The trained network is used to predict chemical properties directly from structure and generate candidate structures with desired chemical properties. The network is extensible to other training data and molecular representations, and for use with other analytical platforms, for both chemical property and feature prediction as well as molecular structure generation.

Colby, Sean M.↗
NASA NTRS1995

Exchange, interpretation, and database-search of ion mobility spectra supported by data format JCAMP-DX

To assist peak assignment in ion mobility spectrometry it is important to have quality reference data. The reference collection should be stored in a database system which is capable of being searched using spectral or substance information. We propose to build such a database customized for ion mobility spectra. To start off with it is important to quickly reach a critical mass of data in the collection. We wish to obtain as many spectra combined with their IMS parameters as possible. Spectra suppliers will be rewarded for their participation with access to the database. To make the data exchange between users and system administration possible, it is important to define a file format specially made for the requirements of ion mobility spectra. The format should be computer readable and flexible enough for extensive comments to be included. In this document we propose a data exchange format, and we would like you to give comments on it. For the international data exchange it is important, to have a standard data exchange format. We propose to base the definition of this format on the JCAMP-DX protocol, which was developed for the exchange of infrared spectra. This standard made by the Joint Committee on Atomic and Molecular Physical Data is of a flexible design. The aim of this paper is to adopt JCAMP-DX to the special requirements of ion mobility spectra.

Baumback, J. I.↗
DOE OSTI2025

Comparative Performance Evaluation of Large Language Models for Extracting Molecular Interactions and Pathway Knowledge

Understanding the interactions and regulatory relationships among biomolecules is essential for deciphering complex biological systems and elucidating the mechanisms behind diverse biological functions. Traditionally, the collection of such molecular interaction data has relied on expert curation, a process that is both time-consuming and labor-intensive. To address these limitations, this study explores the use of large language models (LLMs) to automate the genome-scale extraction of molecular interaction knowledge. Here, we evaluate the performance of various LLMs on key biological tasks, including the identification of protein-protein interactions, detection of genes associated with pathways influenced by low-dose radiation, and inference of gene regulatory relationships. Our findings demonstrate that larger LLMs tend to perform better, particularly in extracting intricate gene and protein interactions. Despite their strengths, these models face challenges in recognizing functionally diverse gene groups and highly correlated regulatory relationships. Through a comprehensive analysis using established molecular interaction and pathway databases, we show that LLMs possess the potential to identify relevant biomolecules and predict their interactions, offering valuable insights and marking a significant step toward AI-driven biological knowledge discovery.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

Experimental test of a predicted dynamics–structure–thermodynamics connection in molecularly complex glass-forming liquids

Significance The physical origin of cooperative activated relaxation in glass-forming liquids, which underlies the huge growth of viscosity and suppression of diffusion with cooling, remains elusive. Understanding this problem is of fundamental scientific interest and can assist in the design of new materials. We combine experimental relaxation time and equation-of-state data of molecular liquids to provide strong evidence for the recent theoretical prediction that activated relaxation, though causally driven by dynamically coupled cage-scale hopping and nonlocal collective elasticity quantified by local structural correlations, is well captured based on a thermodynamic description with dimensionless compressibility as the key variable. A mechanistic deduction is the crossover from fragile to strong (e.g., inorganic networks) relaxation behavior arises from the irrelevance of long-range elasticity effects.

36 MATERIALS SCIENCE↗
NASA NTRS2024

Multiscale Modeling of Thermoplastics Using Atomistic-informed Micromechanics

A multiscale repeating unit cell model of a single spherulite containing four disparate length scales was developed to predict the thermoelastic behavior of semicrystalline thermoplastic materials for composite aerospace applications. The continuum level scales were fully coupled and modeled using the generalized method of cells and the high fidelity generalized method of cells micromechanics theories. Data from molecular dynamics simulations were used as inputs for the amorphous and crystalline constituents in the multiscale continuum models. Effective Young’s modulus, shear modulus, Poisson’s ratio, coefficient of thermal expansion, and thermal conductivity were predicted for polyether ether ketone and polyether ketone ketone, showing good agreement with the available experimental data from the open literature. Moreover, it is shown that predicted properties are fairly insensitive to the fidelity of the micromechanics model used at the highest continuum scale or the assumed shape of the spherulite.

thermoplastics↗