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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Immune Response in Microgravity: Genetic Basis and Countermeasure Development Implications

Impairment of the immunity in astronauts and cosmonauts even in shortterm flights is a recognized risk. Longterm orbital space missions and anticipated interplanetary flights increase the concern for more pronounced effects on the immune system with potential clinical consequences. Studies in true and modeled microgravity (MG) have demonstrated that MG directly affects numerous lymphocyte functions. The purpose of this study was to screen for genes involved in lymphocytes response to modeled microgravity (MMG) that could explain the functional and structural changes observed earlier. The microgravity-induced changes in gene expression were analyzed by microarray DNA chip technology. CD3and IL2activated Tcells were cultured in 1g (static) and modeled microgravity (NASA Rotating Wall Vessel bioreactor) conditions for 24 hours. Total RNA was extracted using the RNeasy isolation kit (Qiagen, Valencia, CA). Microarray experiments were performed utilizing Affymetrix Gene Chips (U133A), allowing testing for 18,400 human genes. To decrease the biological variation and aid in detecting microgravity-associated changes, experiments were performed in triplicate using cells obtained from three different donors. Exposure to modeled microgravity resulted in alteration of 89 genes, 10 of which were upregulated and 79 down-regulated. Altered genes were categorized by their function, structural role and by association with metabolic and regulatory pathways. A large proportion was found to be involved in fundamental cellular processes: signal transduction, DNA repair, apoptosis, and multiple metabolic pathways. There was a group of genes directly related to immune and inflammatory responses (IL7R, granulysin, proteasome activator subunit 2, peroxiredoxin 4, HLADRA, lymphocyte antigen 75, IL18R and DOCK2 genes). Among these genes only one (IL7R) was upregulated, the rest were downregulated. The upregulation of the IL7 receptor gene was confirmed by RT PCR. Three genes with altered expression were identified in the apoptosis related group (Granzyme B, APO2 ligand and Beta3endonexin). All of them were downregulated. Gene expression changes in MG might appear pivotal in identifying potential molecular targets for countermeasure development. (Supported by NRA OLMSA02 and NSCORT NAG54072 grants).

Risin, Diana↗
NASA NTRS2012

Modeling the Flow of Rarefied Gases at NASA

At modest temperatures, the thermal energy of atmospheric diatomic gases such as nitrogen is primarily distributed between only translational and rotational energy modes. Furthermore, these energy modes are fully excited such that the specific heat at constant volume is well approximated by the simple expression C(sub v) = 5/2 R. As a result, classical mechanics provides a suitable approximation at such temperatures of the true quantum mechanical behavior of the inter-molecular collisions of such molecules. Using classical mechanics, the transfer of energy between rotational and translation energy modes is studied. The approach of Lordi and Mates is adopted to compute the trajectories and time dependent rotational orientations and energies during the collision of two non-polar diatomic molecules. A Monte-Carlo analysis is performed collecting data from the results of many such simulations in order to estimate the rotational relaxation time. A Graphical Processing Unit (GPU) is employed to improve the performance of the Monte-Carlo analysis. A comparison of the performance of the GPU implementation to an implementation on traditional computer architecture is made. Effects of the assumed inter-molecular potential on the relaxation time are studied. The seminar will also present highlights of computational analyses performed at NASA Johnson Space Center of heat transfer in rarefied gases.

Forrest E. Lumpkin, III↗
NASA NTRS2018

A Mission-Enabling UV Laser for Mass Spectrometry (UVMS) with Continuously Selectable Output for In Situ Planetary Exploration

Ultra-compact, ns-class spaceflight-compatible UV lasers are finding increasing application in laser desorption, excitation, and ionization analytical applications on planetary missions, such as the detection and characterization of potential molecular biosignatures on Mars or icy moon surfaces. A short pulsed, solid state, UV laser is under development with selectable pulse energy capabilities for optimized sample ion production at a planetary surface.

Coyle, D. Barry↗
NASA NTRS1985

Identification and properties of molecular systems of potential use in solar-pumped lasers

The concepts and computational tools of theortical chemistry are used to investigate molecular properties needed in direct solar-pumped lasers. Compounds of the type RR'CXY, with R and R' organic groups, and X and Y halide atoms were identified as likely candidates because of their highly enhanced absorption coefficients over compounds with a single halide atom. The use of a combination of vibrational excitation followed by electronic excitation to enhance quantum yields at certain wavelengths is indicated. A self-consistent eikonal approximation to state-to-state transitions was tested for CH3I and is useful for other problems involving electronic energy and charge transfer. An approach to calculate potential energy surfaces and transition dipoles was developed which is based on the generation of eigenstates of the nonrelativisitc Hamiltonian followed by incorporation of the spin-orbit coupling by configuration interaction.

Micha, D. A.↗
DOE OSTI2025

A review of displacement cascade simulations using molecular dynamics emphasizing interatomic potentials for TPBAR components

This review explores molecular dynamics simulations for studying radiation damage in Tritium Producing Burnable Absorber Rod (TPBAR) materials, emphasizing the role of interatomic potentials in displacement cascades. Recent machine learning potentials (MLPs), trained on quantum data, enhance prediction accuracy over traditional models like EAM. We highlight temperature, PKA energy, and composition effects on damage evolution in TPBAR components, recommending suitable potentials and discussing advancements for materials in extreme radiation environments.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Hybrid Quantum Mechanical, Molecular Mechanical, and Machine Learning Potential for Computing Aqueous-Phase Adsorption Free Energies on Metal Surfaces

Performing reliable computer simulations of elementary processes occurring at metal–water interfaces is pivotal for novel catalyst design in sustainable energy applications. Computational catalyst design hinges on the ability to reliably and efficiently compute the potential energy surface (PES) of the system. Here, due to the large system sizes needed for studying processes at liquid water–metal interfaces, these systems can currently not be described using density functional theory (DFT). In this work, we used a hybrid quantum mechanical, molecular mechanical, and machine learning potential for studying the adsorption behavior of phenol, atomic hydrogen, 2-butanol, and 2-butanone on the (0001) facet of Ru under reducing conditions when Ru is not oxidized. Specifically, we describe the adsorbate and the surrounding metal atoms at the DFT level of theory. Here, we also considered the electrostatic field effect of the water molecules on adsorbate–metal interactions. Next, for the water–water and water–adsorbate interactions, we used established classical force fields. Finally, for the water–Ru surface interaction, for which no reliable force fields have been published, we used Behler–Parrinello high-dimensional neural network potentials (HDNNPs). Employing this setup, we used our explicit solvation for metal surface (eSMS) approach to compute the aqueous-phase effect on the low-coverage adsorption of selected molecules and atoms on the (0001) facet of Ru. In agreement with previous experimental and computational studies of oxygenated molecules over transition metal facets, we found that liquid water destabilizes the tested adsorbates on Ru(0001). Interestingly, our findings indicate that adsorbates on Ru are less affected by the presence of an aqueous phase than on other transition metals (e.g., Pt), highlighting the necessity of experimental investigations of Ru-based catalytic systems in liquid water.

Adsorption↗
NASA NTRS1971

N2/plus/ potential-energy curves

Molecular nitrogen ion potential energy curves based on valence bond method, calculating sextet and quartet states at intermediate internuclear separation distances

Stallcop, J. R.↗
DOE OSTI2024

Understanding Strain and Failure of a Knot in Polyethylene Using Molecular Dynamics with Machine-Learned Potentials

A neural network potential (NNP) has been developed by fitting to ab initio electronic structure data on hydrocarbons and is used to study failure of linear and knotted polyethylene (PE) chains. A linear PE chain must be highly strained before breaking as the stress is equally distributed across the chain. In contrast, the stress in a PE chain with a 31 or overhand knot, accumulates at the knot’s entrance/exit. We find the strain energy is greatest when the bond length and angle are strained simultaneously, and that the knot weakens the chain by increasing the variance of the C–C–C angle, thereby allowing rupture at lower bond strains. Here, we extend our analysis to both 51 and 52 knots and find that both break at the entrance/exit of a loop. Notably, molecular scale PE knots exhibit many of the same characteristics as knots in a macroscopic rope, with stick–slip phenomena upon tightening and similar points of failure.

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

The design space of E(3)-equivariant atom-centred interatomic potentials

Abstract Molecular dynamics simulation is an important tool in computational materials science and chemistry, and in the past decade it has been revolutionized by machine learning. This rapid progress in machine learning interatomic potentials has produced a number of new architectures in just the past few years. Particularly notable among these are the atomic cluster expansion, which unified many of the earlier ideas around atom-density-based descriptors, and Neural Equivariant Interatomic Potentials (NequIP), a message-passing neural network with equivariant features that exhibited state-of-the-art accuracy at the time. Here we construct a mathematical framework that unifies these models: atomic cluster expansion is extended and recast as one layer of a multi-layer architecture, while the linearized version of NequIP is understood as a particular sparsification of a much larger polynomial model. Our framework also provides a practical tool for systematically probing different choices in this unified design space. An ablation study of NequIP, via a set of experiments looking at in- and out-of-domain accuracy and smooth extrapolation very far from the training data, sheds some light on which design choices are critical to achieving high accuracy. A much-simplified version of NequIP, which we call BOTnet (for body-ordered tensor network), has an interpretable architecture and maintains its accuracy on benchmark datasets.

Computer Science↗
DOE OSTI2025

Computational investigation of water glasses using machine-learning potentials

The molecular origins of water’s anomalous properties have long been a subject of scientific inquiry. The liquid–liquid phase transition hypothesis, which posits the existence of distinct low-density and high-density liquid states separated by a first-order phase transition terminating at a critical point, has gained increasing experimental and computational support and offers a thermodynamically consistent framework for many of water’s anomalies. However, experimental challenges in avoiding crystallization near the postulated liquid–liquid critical point have focused attention to water’s canonical glassy states: low-density and high-density amorphous ice. Here, we use two Deep Potential machine-learning models, trained on the Strongly Constrained and Appropriately Normed density functional and the highly accurate Many-Body Polarizable potential, to conduct an investigation of water’s glassy phenomenology based on quantum mechanical calculations. Despite not being explicitly trained on amorphous ices, both models accurately capture the structure and transformation of the water glasses, including their interconversion along different thermodynamic paths. Isobaric quenching of liquid water at various pressures generates a continuum of intermediate amorphous ices and density fluctuations increase near the liquid–liquid critical pressure. The glass transition temperatures of the amorphous ices produced at different pressures exhibit two distinct branches, corresponding to low-density and high-density amorphous ice behaviors, consistent with experiment and the liquid–liquid transition hypothesis. Extrapolating transformation pressures from isothermal compressions to experimental compression rates brings our simulations into excellent agreement with data. Our findings demonstrate that machine-learning potentials trained on equilibrium phases can effectively model nonequilibrium glassy behavior and pave the way for studying long-timescale, out-of-equilibrium processes with quantum mechanical accuracy.

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

Saturn Magnetospheric Impact on Surface Molecular Chemistry and Astrobiological Potential of Enceladus

The active south polar surface of Enceladus is exposed to strong chemical processing by direct interaction with charged plasma and energetic particles in the local magnetospheric environment of this icy moon. Chemical oxidation activity is suggested by detection of H202 at the surface in this region and less directly by substantial presence of C02, CO, and N2 in the plume gases. Molecular composition of the uppermost surface, including ejecta from plume activity, is radiolytically transformed mostly by penetrating energetic electrons with lesser effects from more depleted populations of energetic protons. The main sources of molecular plasma ions and E-ring dust grains in the magnetospheric environment are the cryovolcanic plume emissions from Enceladus. These molecular ions and the dust grains are chemically processed by magnetospheric interactions that further impact surface chemistry on return to Enceladus. For example, H20 neutrals dominating the emitted plume gas return to the surface mostly as H30+ ions after magnetospheric processing. Surface oxidant loading is further increased by return of radiolytically processed ice grains from the E-ring. Plume frost deposition and micrometeoroid gardening protect some fraction of newly produced molecular species from destruction by further irradiation. The evident horizontal and vertical mobility of surface ices in the south polar region drive mixing of these processed materials into the moon interior with potential impacts on deep ice molecular chemistry and plume gas production. Similarly as suggested previously for Europa, the externally driven source of radiolytic oxidants could affect evolution of life in any subsurface liquid water environments of Enceladus.

Cooper, Paul D.↗
DOE OSTI2024

Breaking the Million-Electron and 1 EFLOP/s Barriers: Biomolecular-Scale Ab Initio Molecular Dynamics Using MP2 Potentials

The accurate simulation of complex biochemical phenomena has historically been hampered by the computational requirements of high-fidelity molecular-modeling techniques. Quantum mechanical methods, such as ab initio wave-function (WF) theory, deliver the desired accuracy, but have impractical scaling for modeling biosystems with thousands of atoms. Combining molecular fragmentation with MP2 perturbation theory, this study presents an innovative approach that enables biomolecular-scale ab initio molecular dynamics (AIMD) simulations at WF theory level. Leveraging the resolution-of-the-identity approximation for Hartree-Fock and MP2 gradients, our approach eliminates computationally intensive four-center integrals and their gradients, while achieving near-peak performance on modern GPU architectures. The introduction of asynchronous time steps minimizes time step latency, overlapping computational phases and effectively mitigating load imbalances. Utilizing up to 9,400 nodes of Frontier and achieving 59% (1006.7 PFLOP/s) of its double-precision floating-point peak, our method enables us to break the million-electron and 1EFLOP/s barriers for AIMD simulations with quantum accuracy.

Kurzak, Jakub↗
NASA NTRS1975

Molecular fluorescence as a monitor of minor stratospheric constituents

The potential of molecular fluorescence was assessed as a stratospheric monitor of the concentrations of various minor species. Seventeen molecules were considered and all spectral regions from the vacuum ultraviolet through to the infrared are included. The exercise has produced few surprises; however, further confirmation has emerged as to the feasibility of this sensitive technique for monitoring stratospheric OH, NO2, and SO2, sufficient to warrant its development as analytical flight hardware for these species. All the other molecules have been eliminated with the exception of C10 which appears to have promise but requires additional information before its detection limit can be calculated; its fluorescence spectrum is as yet uninvestigated. A handbook for molecular fluorescence is presented, and a compilation of all reported studies for simple molecules using line source excitation is included.

Schofield, K.↗
DOE OSTI2024

Shallow Rate-Redox Potential Scaling in Aqueous Molecular Oxygen Reduction Electrocatalysis Across a Family of Iron Macrocycles

Rate-overpotential scaling relationships have been employed widely to understand trends in oxygen reduction reaction (ORR) electrocatalysis by dissolved metal macrocycles in organic electrolytes. Similar scaling relationships remain unknown for surface-adsorbed ORR electrocatalysts in the acidic aqueous environments germane to proton-exchange membrane (PEM) fuel cells. Herein, we examine ORR catalysis in aqueous perchloric acid media for a structurally diverse array of iron macrocycle complexes adsorbed on Vulcan carbon black. The macrocycles encompass Fe– N 4 , Fe–N 2 N' 2 and Fe–N x C 4-x motifs bearing pyrrolic, pyridinic, and N-heterocyclic carbene (NHC) moieties in the primary ligation sphere, giving rise to a 670 mV range in Fe(III/II) redox potentials, E Fe(III/II) . Experimental Tafel data in the micropolarization regime were extrapolated to the E Fe(III/II) to furnish estimated per-site-normalized current density (j per-site ) values that span ~4.6 orders of magnitude across the family of compounds. Despite the structural diversity of this family of compounds, extrapolated j per-site values correlate with the Fe(III/II) redox potentials in a roughly log-linear fashion with a shallow scaling factor of approximately 145 mV/decade. Further, these findings highlight that negative shifts in E Fe(III/II) lead to diminishing returns in catalytic rate promotion and suggest that changes to the primary ligating environment in a macrocycle are insufficient to break fundamental rate-potential scaling relationships in aqueous ORR catalysis. Together these studies motivate the further development of higher-potential iron complexes that employ motifs beyond the equatorial ligation plane to enhance ORR catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗