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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Biological Information Signal Processor

Biological Information Signal Processor (BISP) is computing system analyzing data on deoxyribonucleic acid (DNA) sequences for molecular genetic analysis. Includes coprocessors, specialized microprocessors complementing present and future computers by performing rapidly most-time-consuming DNA-sequence-analyzing functions, establishing relationships (alignments) between both global sequences and defining patterns in multiple sequences. Also includes state-of-art software and data-base systems on both conventional and parallel computer systems to augment analytical abilities of developmental coprocessors.

Chow, Edward T.↗
NASA NTRS2006

Orion Aerodynamics for Hypersonic Free Molecular to Continuum Conditions

Numerical simulations are performed for the Orion Crew Module, previously known as the Crew Exploration Vehicle (CEV) Command Module, to characterize its aerodynamics during the high altitude portion of its reentry into the Earth's atmosphere, that is, from free molecular to continuum hypersonic conditions. The focus is on flow conditions similar to those that the Orion Crew Module would experience during a return from the International Space Station. The bulk of the calculations are performed with two direct simulation Monte Carlo (DSMC) codes, and these data are anchored with results from both free molecular and Navier-Stokes calculations. Results for aerodynamic forces and moments are presented that demonstrate their sensitivity to rarefaction, that is, for free molecular to continuum conditions (Knudsen numbers of 111 to 0.0003). Also included are aerodynamic data as a function of angle of attack for different levels of rarefaction and results that demonstrate the aerodynamic sensitivity of the Orion CM to a range of reentry velocities (7.6 to 15 km/s).

Moss, James N.↗
DOE OSTI2021

Ab Initio Molecular Dynamics Simulations of Amorphous Calcium Carbonate: Interpretation of Pair Distribution Function and X-Ray Absorption Spectroscopy Data

The structure and transformation of hydrous amorphous calcium carbonate (ACC) are key to understanding biomineralization pathways and their relationship with the properties of the resulting material. Quantitative interpretation of scattering experiments aimed at elucidating the structure of ACC is challenging, due to the amorphous nature of this material, and, therefore, requires models for the structure and the scattering physics. Here, we generate physically realistic ensembles of hydrated ACC structures and their vibrational disorder from ab initio molecular dynamics (AIMD) simulations with an emphasis on enabling the consistent interpretation of the finer details of three complementary structural probes: neutron and x-ray pair distribution experiments and x-ray absorption spectroscopy (XAS). In each case, we simulate the signal directly in reciprocal space and then manipulate it into the real-space pair distribution function (PDF) or spectrum using the same procedures for the experimental and theoretical data. Good agreement with experiment was obtained across the three techniques with the simulations accounting well for all features in the spectra. Remaining small discrepancies pointed to differences between real samples and the idealized simulated systems such as deviations from the nominal CaCO3·nH2O stoichiometry. Additionally, the simulations offered a more accurate description of the local coordination environment of calcium than previous shell-by-shell fits to spectra of synthetic ACC and classical molecular dynamics simulations. This work demonstrates that AIMD is a powerful approach for extracting detailed structural information from neutron PDF, x-ray PDF, and XAS of amorphous carbonate phases.

Prange, Micah P.↗
NASA NTRS2000

Effects of Inert Dust Clouds on the Extinction of Strained, Laminar Flames at Normal and Micro Gravity

A combined experimental and detailed numerical study was conducted on the interaction between chemically inert solid particles and strained, atmospheric methane/air and propane/air laminar flames, both premixed and non-premixed. Experimentally, the opposed jet configuration was used with the addition of a particle seeder capable of operating in conditions of varying gravity. The particle seeding system was calibrated under both normal and micro gravity and a noticeable gravitational effect was observed. Flame extinction experiments were conducted at normal gravity by seeding inert particles at various number densities and sizes into the reacting gas phase. Experimental data were taken for 20 and 37 (mu) nickel alloy and 25 and 60 (mu) aluminum oxide particles. The experiments were simulated by solving along the stagnation streamline the conservation equations of mass, momentum, energy, and species conservation for both phases, with detailed descriptions of chemical kinetics, molecular transport, and thermal radiation. The experimental data were compared with numerical simulations, and insight was provided into the effects on extinction of the fuel type, equivalence ratio, flame configuration, strain rate. particle type. particle size. particle mass, delivery rate. the orientation of particle injection with respect to the flame and gravity. It was found that for the same injected solid mass, larger particles can result in more effective flame cooling compared to smaller particles, despite the fact that equivalent masses of the larger particles have smaller total surface area to volume ratio. This counter-intuitive finding resulted from the fact that the heat exchange between the two phases is controlled by the synergistic effect of the total contact area and the temperature difference between the two phases. Results also demonstrate that meaningful scaling of interactions between the two phases may not be possible due to the complexity of the couplings between the dynamic and thermal parameters of the problem.

Andac, M. Gurhan↗
DOE OSTI2026

An interactive machine learning platform for analyzing multi-particle coincidence data from cold target recoil ion momentum spectroscopy

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements uniform manifold approximation and projection for non-linear dimensionality reduction to reveal correlations in high-dimensional data. We also discuss potential extensions to deep autoencoders for feature learning and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric’s robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT’s capabilities, we analyze photo-double-ionization data measured using the COLTRIMS method for three-body dissociation of the D 2 O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software’s modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Artificial neural networks↗
NASA NTRS1989

A CO and far-infrared study of the S254-S258 region

The molecular cloud associated with compact radio and bright optical H II regions is studied from observations of (C-12)O, (C-13)O, HCN J = 1-0 emission. The far-infrared and millimeter molecular line emission from the S254-S258 molecular cloud is analyzed, using co-added survey data from IRAS, to investigate the coupling between the dust and gas components and the internal energetics associated with molecular clouds. The dust component is analyzed by fitting model intensities, derived from a dust mass column density temperature relation, to the observed far-infrared emission. Such modeling is shown to provide a more complete description of the cold dust component which comprises most of the dust mass than can be determined from the standard single temperature analysis. Local heating of the dust component by newborn massive stars associated with the H II regions of the cloud is inferred from the spatial distribution of temperatures of grains which make the largest contributions to the observed 60 and 100 micron emission.

Heyer, Mark H.↗
NASA NTRS1987

Spectroscopic comparison of effects of electron radiation on mechanical properties of two polyimides

The differences in the radiation durabilities of two polyimide materials, Du Pont Kapton and General Electric Ultem, are compared. An explanation of the basic mechanisms which occur during exposure to electron radiation from analyses of infrared (IR) and electron paramagnetic resonance (EPR) spectroscopic data for each material is provided. The molecular model for Kapton was, in part, established from earlier modeling for Ultem (pp. 1293-1298 of IEEE Transactions on Nuclear Science, December 1984). Techniques for understanding the durability of one complex polymer based on the understanding of a different and equally complex polymer are demonstrated. The spectroscopic data showed that the primary radiation-generated change in the tensile properties of Ultem (a large reduction in tensile elongation) was due to crosslinking, which followed the capture by phenyl radicals of hydrogen atoms removed from gem-dimethyl groups. In contrast, the tensile properties of Kapton remained unchanged because radical-radical recombination, a self-mending process, took place.

Long, Edward R., Jr.↗
DOE OSTI2025

The Future of a Myriad of Accelerated Biodiscoveries Lies in AI‐Powered Mass Spectrometry and Multiomics Integration

The intersection of modern artificial intelligence (AI) and mass spectrometry (MS) is set to transform the MS‐based “omics” research fields, particularly proteomics, metabolomics, lipidomics, and glycomics, enabling advancements across a wide range of domains, from health to environment and industrial biotechnology. Beginning with an overview of key challenges inherent in MS software pipelines, this personal perspective explores how AI‐driven solutions can address them to enhance data processing, integration and interpretation. It proposes a paradigm shift in molecular identification and quantitation algorithms, leveraging AI to enable holistic interpretation of MS‐based multiomics data. While centered on MS‐based omics, this holistic AI‐driven paradigm is also critical for connecting dynamic biochemical changes to genomics and transcriptomics contexts, reinforcing the integrative value of MS in multiomics research. Ultimately, this AI‐driven approach could enhance efficiency, accuracy, and molecular breadth of coverage, deepening our systems‐level understanding of biological processes and accelerating a myriad of biodiscoveries.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Visualizing and analyzing 3D biomolecular structures using Mol* at RCSB.org: Influenza A H5N1 virus proteome case study

The easiest and often most useful way to work with experimentally determined or computationally predicted structures of biomolecules is by viewing their three-dimensional (3D) shapes using a molecular visualization tool. Mol* was collaboratively developed by RCSB Protein Data Bank (RCSB PDB, RCSB.org) and Protein Data Bank in Europe (PDBe, PDBe.org) as an open-source, web-based, 3D visualization software suite for examination and analyses of biostructures. It is capable of displaying atomic coordinates and related experimental data of biomolecular structures together with a variety of annotations, facilitating basic and applied research, training, education, and information dissemination. Across RCSB.org, the RCSB PDB research-focused web portal, Mol* has been implemented to support single-mouse-click atomic-level visualization of biomolecules (e.g., proteins, nucleic acids, carbohydrates) with bound cofactors, small-molecule ligands, ions, water molecules, or other macromolecules. RCSB.org Mol* can seamlessly display 3D structures from various sources, allowing structure interrogation, superimposition, and comparison. Using influenza A H5N1 virus as a topical case study of an important pathogen, we exemplify how Mol* has been embedded within various RCSB.org tools—allowing users to view polymer sequence and structure-based annotations integrated from trusted bioinformatics data resources, assess patterns and trends in groups of structures, and view structures of any size and compositional complexity. In addition to being linked to every experimentally determined biostructure and Computed Structure Model made available at RCSB.org, Standalone Mol* is freely available for visualizing any atomic-level or multi-scale biostructure at rcsb.org/3d-view.

3D biostructure↗
DOE OSTI2023

Chemical evolution in nitrogen shocked beyond the molecular stability limit

Evolution of nitrogen under shock compression up to 100 GPa is revisited via molecular dynamics simulations using a machine-learned interatomic potential. The model is shown to be capable of recovering the structure, dynamics, speciation, and kinetics in hot compressed liquid nitrogen predicted by first-principles molecular dynamics, as well as the measured principal shock Hugoniot and double shock experimental data, albeit without shock cooling. Our results indicate that a purely molecular dissociation description of nitrogen chemistry under shock compression provides an incomplete picture and that short oligomers form in non-negligible quantities. Finally, this suggests that classical models representing the shock dissociation of nitrogen as a transition to an atomic fluid need to be revised to include reversible polymerization effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1991

Electron densities and the excitation of CN in molecular clouds

In molecular clouds of modest density and relatively high fractional ionization, the rotational excitation of CN is controlled by a competition among electron impact, neutral impact and the interaction with the cosmic background radiation. The degree of excitation can be measured through optical absorption lines and millimeter-wave emission lines. The available, accurate data on CN in diffuse and translucent molecular clouds are assembled and used to determine electron densities. The derived values, n(e) = roughly 0.02 - 0.5/cu cm, imply modest neutral densities, which generally agree well with determinations by other techniques. The absorption- and emission-line measurements of CN both exclude densities higher than n(H2) = roughly 10 exp 3.5/cu cm on scales varying from 0.001 to 60 arcsec in these clouds.

Black, John H.↗
DOE OSTI2021

A physics-informed and hierarchically regularized data-driven model for predicting fluid flow through porous media

This paper presents a new deep learning data-driven model for predicting structure dependent pore-fluid velocity fields in rock. The model is based on a Convolutional Auto-Encoder (CAE) artificial neural network capable of learning from image data generated by direct numerical simulations of fluid flow through pore-structures, such as by Lattice Boltzmann or molecular dynamics methods. The main novelty of the model in comparison to previous CAE-based data-driven approaches consists of three parts. The first is a methodology for decomposing the full-domain of the porous media into sub-regions, or “sub-domains”, in order to reduce the overall size of the CAE, batch process the sub-domains in parallel, and enable the CAE to learn local and generalizable nonlinear mappings of pore-fluid velocities. The second consists of embedding the finite difference solutions of the incompressible Navier-Stokes and continuity equations into convolutional layers prior to the CAE in order to provide the CAE with knowledge of fluid dynamics physics (PhyFlow). The third main novelty is that the training of the CAE is regularized with a hierarchical loss function that encourages the learning of fluid flow patterns (in a way similar to ranked modes in principal component analysis), ranking from most to least important. This is shown to increase the stability in learning, reduce over-fitting, and promote interpretability of the CAE neural network layers (HierCAE). The comprehensive new data-driven model, which we call the PhyFlow-HierCAE model, is shown to exhibit improved accuracy and generalizability of flow field predictions over conventional CAE models, attributable to the embedded physical knowledge and the hierarchical regularization, as well as realize orders of magnitude speed-ups in computation times as a surrogate for the direct numerical simulations. Examples of training and forward predictions on unseen pore-structures are provided and evaluated for data from Lattice Boltzmann and molecular dynamics simulations of pore-fluid flow. The model is shown to be a fast and accurate emulator (or “surrogate”) for predicting effective permeability of unseen pore-structures based on learning from relatively small direct numerical simulation datasets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Data-Driven Approach for Controlled Icosahedral Boron- Rich Compound Growth

This final technical report summarizes the research accomplishments and research highlights at the end of the funding period. This project aimed to leverage existing and new computational data produced from first-principles and molecular dynamics simulations to understand the thermodynamic, mechanical, and electronic properties of icosahedral boron compounds. The goal is to achieve targeted material properties by controlling the synthesis routes of these boron-rich compounds.

36 MATERIALS SCIENCE↗
NASA NTRS1972

Apollo 15 rake sample microbreccias and non-mare rocks: Bulk rock, mineral and glass electron microprobe analyses

Quantitative electron microprobe data of Apollo 15 nonmare rake samples are presented. Bulk analyses of lithic fragments in the nomare rocks (expressed in oxide weight-percent) and the corresponding CIPW molecular norms are given. The mineralogy of the rocks and lithic fragments are also given; structural formulae for complete analyses and molecular end-members for all mineral analyses are included. The mineral analyses include pyroxene, olivine, plagioclase, barian K-feldspar, spinel and ilmenite, cobaltian metallic nickel-iron as well as SiO2-K2O-rich residual glass. Electron micropobe analyses (oxide weight percent) of glasses in loose fines and microbreccia samples and their CIPW molecular norms are presented along with electron microprobe data on bulk, mineral, and matrix glass from chondrules.

Hlava, P. F.↗
NASA NTRS1972

Terrestrial atmospheric composition from stellar occultations

Stellar ultraviolet light transmitted through the upper mesosphere and lower thermosphere of the earth's atmosphere is primarily affected by the photoabsorption processes of ozone and molecular oxygen. The stellar ultraviolet photometers aboard the OAO-2 satellite have measured the intensity changes of several stars during occultation of the star by the earth. The measurements of the relative intensity change in certain atmospheric absorption bands are used to recover the vertical number density profiles of the absorbing species. Using the OAO-2 occultation data, the vertical number density profiles of molecular oxygen in the 100-200 km altitude region and ozone in the 60-100 km altitude region are determined.

Hays, P. B.↗
NASA NTRSDate not supplied

Analysis of Nonequilibrium Molecular Nitrogen Ultraviolet Radiation in Pure N2 Shockwaves

This paper presents an analysis of data previously reported from a test series in the Electric Arc Shock Tube Facility for incident shocks composed of pure Nitrogen. The present work focuses on the lowest velocity measured in the test (approximately 7 km/s) where molecular radiation is significant. Analysis of the spectral data with the NEQAIR radiative transport code obtains post-shock trends in temperature and number densities of the states of N2. The results suggest that chemical, and possibly thermal, equilibrium has not been obtained within the distance/time measured (about 5 cm/120 s). In the nonequilibrium region of the shock, differences between rotational temperatures of different species are observed, as well as differences between rotational and vibrational temperatures. Population of rotational states above the dissociation limit is observed to occur over a distance of several cm. Finally, these data suggest that predissociation strongly affects the C^3 Π_u state of N2, leading to a lower measured radiation than predicted. An effective average pre-dissociation rate is shown to produce reasonable agreement under quasi-steady state approximation.

Augustin Tibere Inglesse↗
DOE OSTI2022

Correlations for the specific heat capacity of ( U x Pu 1 - x ) 1 - y Gd y O 2 - z derived from molecular dynamics

We report UO 2 is the primary conventional fuel used in most nuclear reactors with Gd 2 O 3 commonly added as a burnable absorber to produce a more level power distribution in the reactor core at the beginning of operation. It can also be mixed with other actinide oxides to produce mixed oxide (MOx) fuel. In this study, molecular dynamics simulations were used to predict the specific heat capacity of Gd-doped PuO 2 , UO 2 and (U, Pu)O 2 MOx accommodating Gd 3+ substituted at cation sites via two charge compensation mechanisms - oxygen vacancy formation and the oxidation of U 4+ to U 5+ . The specific heat capacity values for PuO 2 and UO 2 are in good agreement with other studies showing a distinct peak at high temperatures - above 1800 K. As Gd 3+ is added, the peak height reduces for each composition considered. An analytical fit was applied to the data where Gd 3+ was fully charge compensated by either oxygen vacancies or U 5+ . The expression was then validated by predicting the specific heat capacity for three compositions of (Ux Pu 1-x ) 1-y Gd y O 2-z containing both oxygen vacancies and U 5+ , and compared to molecular dynamics data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1978

Compatibility of seasonal variations in mid-latitude thermospheric models at solar maximum and low geomagnetic activity

Satellite drag data, in situ mass spectrometer data, Fabry Perot interferometer data, and incoherent scatter data were used to produce models of the concentration of atomic oxygen and molecular nitrogen in the thermosphere and of the exospheric temperature. Incoherent scatter data from two stations near 45 deg N were used. The three techniques provide similar patterns for the annual variations of the atomic oxygen concentration at 400 km, and the mean annual temperatures are within 20 K of each other for five of the six models involved. Four of the models are in good agreement concerning the annual temperature variation. There is fair agreement between incoherent scatter models and mass spectrometer models for the N2 concentrations at 400 km but disagreement between these models and the satellite drag model. It is shown that most disagreements can be resolved by changing both the vertical temperature profile and the lower-thermosphere oxygen concentration in the direction indicated by previous incoherent scatter measurements.

Alcayde, D.↗