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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Tomographic assessment of peening for metallurgical bonding in cold spray

It is widely asserted that peening densifies cold spray coatings and improves particle–particle and particle–substrate bonding, yet systematic studies analyzing the evolution of bonding due to peening particle strikes are scarce. We explore peening at the level of individual particle impacts, by creating two-particle Cu-on-Cu stacks using laser-induced particle impact testing. Exploring impact velocities that range from the onset of bonding at the “critical velocity”, V cr , to its peak near 1.4⋅V cr , we perform full 3D tomography of the particle stacks to characterize the bonding state at the particle-substrate interface. Direct labeling of non-bonded patches and the total particle-substrate interface permits quantification and comparison of bonding in single impacts with bonding after subsequent impacts to reveal the origins of the peening effect. The data reveal a surprising finding: although a second impact directly atop the first particle increases the area of the particle-substrate interface (~40% area increase), there is no improvement in metallurgical bonding. Analysis of these data suggest that not only area expansion (and associated oxide rarefication), but also stress-induced extrusion of metal at that interface needs to occur to achieve metal-on-metal contact to see an enhancement in bonding. Furthermore, our analysis suggests that the subsequent impacting particle needs to have ~70% more kinetic energy to produce additional bonding; this implies that particle and velocity distributions within a spray may be helpful, and that peening may rely on unaligned impacts.

Bonding↗
DOE OSTI2020

Machine learning for collective variable discovery and enhanced sampling in biomolecular simulation

Classical molecular dynamics simulates the time evolution of molecular systems through the phase space spanned by the positions and velocities of the constituent atoms. Molecular-level thermodynamic, kinetic, and structural data extracted from the resulting trajectories provide valuable information for the understanding, engineering, and design of biological and molecular materials. The cost of simulating many-body atomic systems makes simulations of large molecules prohibitively expensive, and the high-dimensionality of the resulting trajectories presents a challenge for analysis. Driven by advances in algorithms, hardware, and data availability, there has been a flare of interest in recent years in the applications of machine learning – especially deep learning – to molecular simulation. Furthermore, these techniques have demonstrated great power and flexibility in both extracting mechanistic understanding of the important nonlinear collective variables governing the dynamics of a molecular system, and in furnishing good low-dimensional system representations with which to perform enhanced sampling or develop long-timescale dynamical models. It is the purpose of this article to introduce the key machine learning approaches, describe how they are married with statistical mechanical theory into domain-specific tools, and detail applications of these approaches in understanding and accelerating biomolecular simulation.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Glancing Angle Deposition in Gas Sensing: Bridging Morphological Innovations and Sensor Performances

Glancing Angle Deposition (GLAD) has emerged as a versatile and powerful nanofabrication technique for developing next-generation gas sensors by enabling precise control over nanostructure geometry, porosity, and material composition. Through dynamic substrate tilting and rotation, GLAD facilitates the fabrication of highly porous, anisotropic nanostructures, such as aligned, tilted, zigzag, helical, and multilayered nanorods, with tunable surface area and diffusion pathways optimized for gas detection. This review provides a comprehensive synthesis of recent advances in GLAD-based gas sensor design, focusing on how structural engineering and material integration converge to enhance sensor performance. Key materials strategies include the construction of heterojunctions and core–shell architectures, controlled doping, and nanoparticle decoration using noble metals or metal oxides to amplify charge transfer, catalytic activity, and redox responsiveness. GLAD-fabricated nanostructures have been effectively deployed across multiple gas sensing modalities, including resistive, capacitive, piezoelectric, and optical platforms, where their high aspect ratios, tailored porosity, and defect-rich surfaces facilitate enhanced gas adsorption kinetics and efficient signal transduction. These devices exhibit high sensitivity and selectivity toward a range of analytes, including NO2, CO, H2S, and volatile organic compounds (VOCs), with detection limits often reaching the parts-per-billion level. Emerging innovations, such as photo-assisted sensing and integration with artificial intelligence for data analysis and pattern recognition, further extend the capabilities of GLAD-based systems for multifunctional, real-time, and adaptive sensing. Finally, current challenges and future research directions are discussed, emphasizing the promise of GLAD as a scalable platform for next-generation gas sensing technologies.

Chemistry↗
NASA NTRS2011

Space Radiation Effects on Human Cells: Modeling DNA Breakage, DNA Damage Foci Distribution, Chromosomal Aberrations and Tissue Effects

Future long-tem space travel will face challenges from radiation concerns as the space environment poses health risk to humans in space from radiations with high biological efficiency and adverse post-flight long-term effects. Solar particles events may dramatically affect the crew performance, while Galactic Cosmic Rays will induce a chronic exposure to high-linear-energy-transfer (LET) particles. These types of radiation, not present on the ground level, can increase the probability of a fatal cancer later in astronaut life. No feasible shielding is possible from radiation in space, especially for the heavy ion component, as suggested solutions will require a dramatic increase in the mass of the mission. Our research group focuses on fundamental research and strategic analysis leading to better shielding design and to better understanding of the biological mechanisms of radiation damage. We present our recent effort to model DNA damage and tissue damage using computational models based on the physics of heavy ion radiation, DNA structure and DNA damage and repair in human cells. Our particular area of expertise include the clustered DNA damage from high-LET radiation, the visualization of DSBs (DNA double strand breaks) via DNA damage foci, image analysis and the statistics of the foci for different experimental situations, chromosomal aberration formation through DSB misrepair, the kinetics of DSB repair leading to a model-derived spectrum of chromosomal aberrations, and, finally, the simulation of human tissue and the pattern of apoptotic cell damage. This compendium of theoretical and experimental data sheds light on the complex nature of radiation interacting with human DNA, cells and tissues, which can lead to mutagenesis and carcinogenesis later in human life after the space mission.

Ponomarev, A. L.↗
DOE OSTI2020

Kinetics Modeling for Design of Continuous Enzymatic Hydrolysis

Enzymatic hydrolysis of cellulose to monomeric sugars continues to be a limiting step in cost-effectively producing sugar and fermentation-based biofuels from biomass. In particular, the high cost of enzymes coupled with the long time-scale of reaction pose challenges to economic viability. Performing enzymatic hydrolysis in a continuous mode with enzyme recycle may provide a path towards substantially reduced costs for sugar production, but design and analysis are complicated by a lack of suitable kinetics models. Computationally attainable models, such as fractal-based models, require knowledge of the reaction-history of the biomass, and are thus only suitable for describing the batch reactions from which they are derived. Fundamental models, while potentially more generalizable, are often too computationally intensive to use in process or reactor modeling. In this work, a phenomenological rate model is proposed based on a two-phase substrate representation. Good agreement is seen between batch and continuous enzymatic hydrolysis (CEH) experiment data, which validates the model and enables us to solve for reactor design parameters, such as CEH reactor size and stream flow rates, based on process variables like yield. This model is integrated with techno-economic analysis software to explore economic sensitivities. Important design optimizations and tradeoffs are identified and quantified, including the relative cost imposed by rate slowdown from sugar inhibition versus the cost to remove and concentrate sugars at a lower concentration. It also identifies, high-leverage avenues for further exploration, such as increasing the maximum feasible solids concentration, and sustaining high membrane flux and reliability.

09 BIOMASS FUELS↗
NASA NTRS2006

BLIMPK/Streamline Surface Catalytic Heating Predictions on the Space Shuttle Orbiter

This paper describes the results of an analysis of localized catalytic heating effects to the U.S. Space Shuttle Orbiter Thermal Protection System (TPS). The analysis applies to the High-temperature Reusable Surface Insulation (HRSI) on the lower fuselage and wing acreage, as well as the critical Reinforced Carbon-Carbon on the nose cap, chin panel and the wing leading edge. The object of the analysis was to use a modified two-layer approach to predict the catalytic heating effects on the Orbiter windward HRSI tile acreage, nose cap, and wing leading edge assuming localized highly catalytic or fully catalytic surfaces. The method incorporated the Boundary Layer Integral Matrix Procedure Kinetic (BLIMPK) code with streamline inputs from viscous Navier-Stokes solutions to produce heating rates for localized fully catalytic and highly catalytic surfaces as well as for nominal partially catalytic surfaces (either Reinforced Carbon-Carbon or Reaction Cured Glass) with temperature-dependent recombination coefficients. The highly catalytic heating results showed very good correlation with Orbiter Experiments STS-2, -3, and -5 centerline and STS-5 wing flight data for the HRSI tiles. Recommended catalytic heating factors were generated for use in future Shuttle missions in the event of quick-time analysis of damaged or repaired TPS areas during atmospheric reentry. The catalytic factors are presented along the streamlines as well as a function of stagnation enthalpy so they can be used for arbitrary trajectories.

Marichalar, Jeremiah J.↗
DOE OSTI2025

Defect Diffusion Graph Neural Networks for Materials Discovery in High-Temperature Energy Applications

Here, the migration of crystallographic defects dictates material properties and performance for a plethora of technological applications. Density functional theory (DFT)-based nudged elastic band (NEB) calculations are a powerful computational technique for predicting defect migration activation energy barriers, yet they become prohibitively expensive for high-throughput screening of defect diffusivities. Without introducing hand-crafted (i.e., chemistry- or structure-specific) descriptors, we propose a generalized deep learning approach to train surrogate models for NEB energies of vacancy migration by hybridizing graph neural networks with transformer encoders and simply using pristine host structures as input. With sufficient training data, computationally efficient and simultaneous inference of vacancy defect thermodynamics and migration activation energies can be obtained to compute temperature-dependent vacancy diffusivities and to down-select candidates for more thorough DFT analysis or experiments. Thus, as we specifically demonstrate for potential water-splitting materials, candidates with desired defect thermodynamics, kinetics, and host stability properties can be more rapidly targeted from open-source databases of experimentally validated or hypothetical materials.

14 SOLAR ENERGY↗
DOE OSTI2022

Tracking carrier and exciton dynamics in mixed-cation lead mixed-halide perovskite thin films

Mixed-cation lead mixed-halide perovskites simultaneously possess structural stability and high power conversion efficiency. A thorough study of both carrier and exciton dynamics is needed to understand the photophysical properties that underpin its superior photovoltaic performance. By utilizing a broadband transient absorption spectroscopy, we observe the carrier and exciton dynamics in a FA 0.85 Cs 0.15 Pb(I 0.97 Br 0.03 ) 3 (FCPIB) perovskite by simultaneously resolving the carrier and exciton contribution to the transient change of the absorption spectra, from which the carrier density and exciton oscillator strength can be determined. Our data reveal a quick and significant conversion of the photogenerated carriers to excitons, on top of the usual carrier recombination process. Moreover, the decay of carrier density shows a change of kinetics from a second-order recombination at high pump fluence to a third-order recombination at low pump fluence. Our analysis utilizes band anharmonicity, presents an independent determination of electronic temperature and quasi-Fermi energy, and reveals an interesting interplay among the processes of carrier cooling, exciton formation/decay and carrier recombination, all as a function of time after photoexcitation. Our work demonstrates the use of pump fluence as a knob to tune the relative populations of carriers and excitons in halide perovskite materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Spatially resolved charge-transfer kinetics at the quantum dot–microbe interface using fluorescence lifetime imaging microscopy

Integrating the optoelectronic properties of quantum dots (QDs) with biological enzymatic systems to form microbe-semiconductor biohybrids offers promising prospects for both solar-to-chemical conversion and light-modulated biochemical processes. Developing these nano–bio hybrid systems necessitates a deep understanding of charge-transfer dynamics at the nano–bio interface. Photoexcited carrier transfer from QDs to microbes is driven by complex interactions, with emerging insights into the relevant thermodynamic and kinetic factors. The heterogeneities of both microbes and QD ensembles pose significant challenges in mechanistic understanding, which is critical for designing advanced nano–bio hybrids. We used fluorescence lifetime imaging microscopy to analyze charge transfer between a CdSe QD film andShewanella oneidensismicrobes. We correlated the spatiotemporal fluorescence data with an analytical model. Our analysis revealed two distinct distributions of QD de-excitation pathways. The characteristics of these distributions: 1) a faster transfer rate ( k ¯ E T 1 = 1.5 10 9 s - 1 ), with a lower acceptor number ( N ¯ a 1 = 0.03 ) and 2) a slower transfer rate ( k ¯ E T 2 = 4.1 10 8 s - 1 ) with a higher acceptor number ( N ¯ a 2 = 0.18 ). We assign these distributions to the indirect and direct electron transfer mechanisms, respectively. Our findings demonstrate how spectroscopic imaging can uncover fundamental electron transfer mechanisms at complex interfaces, offering valuable design principles for future nano–bio hybrids.

Science & Technology - Other Topics↗
NASA NTRS1978

Kinetics of hydrogen-oxygen and methane-oxygen ignition sensitized by NO or NO2

In a study of methane ignition sensitized by NO2, the induction period chemical kinetics were examined by monitoring reactants and intermediates (CH4, NO2, OH, NO, CO, CO2, and H2O) prior to ignition. Data were obtained at pressure of 2-4 atm, temperatures of 1300-1900 K, equivalence ratios of 0.5-1.0, and NO2 up to 3.4 mole %. A tentative NO2 sensitization mechanism was deduced from the analysis of photometric observations and the comparison of computer modeling with observations.

Slack, M. W.↗
NASA NTRS1988

Turbulence modeling in hypersonic inlets

A study is conducted to analyze the performance of different turbulence models when applied to flow through a Mach 7.4 hypersonic inlet. The analysis, which is two-dimensional, is done by comparing computational results from a Parabolized Navier-Stokes code and a full Navier-Stokes code, with experimental data. The McDonald-Camarata (MC) and Baldwin-Lomax (BL) models were the two zero-equation models used in the study. The Turbulent Kinetic Energy (TKE) model was chosen as a representative higher order model. The MC model, when run with transition of flow, provides a solution which compares excellently with the data. Transition has a first order effect on the overall solution provided by the code. The BL model predicts separation of flow in the inlet, which contradicts experimental findings. The TKE model does not perform any better than the MC and BL models, despite the fact that it is a higher order turbulence model. The BL and TKE models predict transition in the inlet at a location which is much earlier than observed in the experiment. This may be attributed to the empirical constants used to determine the point of transition.

Ng, W. F.↗
DOE OSTI2022

Inferring small-sample-reactivity worth from oscillation experiment with auto-corrected local flux

To estimate reactivity changes as a function of time from the signal of detectors count rates, one usually uses point kinetic equations. However, when detectors are located inside the core, it is often necessary to compute a correction factor to account for the flux-shape deformation (i.e. the change of detector efficiency that may have been induced by neutron absorbers movements). Various simulation methods have been developed depending on transients observed. They range from the resolution of static equations up to full-time-dependent neutron transport in 3D. However, those methods require high computational-cost calculations of local reaction rates that rely on nuclear data evaluations. Therefore, a 'measured' reactivity is never determined through pure measurements. Taking advantage of the known oscillation movement of a small sample at the center of the MINERVE reactor, the innovative algorithm presented in this paper derives the correction factor needed to get no time drift on reactivity steps. Derived correction factors are in good agreement with those obtained independently with TRIPOLI-4 through sensitivity analysis. Low sensitivity to the sample composition and moderate sensitivity to the detectors position reinforce the reliability of those results. This application paves the way to almost pure nuclear data reactivity measurements. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1994

Convective flow effects on protein crystal growth

A high-resolution microscopic interferometric setup for the monitoring of protein morphologies has been developed. Growth or dissolution of a crystal can be resolved with a long-term depth resolution of 200 A and a lateral resolution of 2 microns. This capability of simultaneously monitoring the interfacial displacement with high local depth resolution has yielded several novel results. We have found with lysozyme that (1) the normal growth rate is oscillatory, and (2) depending on the impurity content of the solution, the growth step density is either greater or lower at the periphery of a facet than in its center. The repartitioning of Na plus and Cl minus ions between lysozyme solutions and crystals was studied for a wide range of crystallization conditions. A nucleation-growth-repartitioning model was developed, to interpret the large body of data in unified way. The results strongly suggest that (1) the ion to lysozyne ratio in the crystal depends mostly on kinetic rather than crystallographic parameters, and (2) lysozyme crystals possess a salt-rich core with a diameter electron microscopy results appear to confirm this finding, which could have far-reaching consequences for x-ray diffraction studies. A computational model for diffusive-convective transport in protein crystallization has been applied to a realistic growth cell geometry, taking into account the findings of the above repartitioning studies and our kinetics data for the growth of lysozyme. The results show that even in the small cell employed, protein concentration nonuniformities and gravity-driven solutal convection can be significant. The calculated convection velocities are of the same order to magnitude as those found in earlier experiments. As expected, convective transport, i.e., at Og, lysozyme crystal growth remains kinetically limited. The salt distribution in the crystal is predicted to be non-uniform at both 1g and 0g, as a consequence of protein depletion in the solution. Static and dynamic light scattering studies in undersaturated and supersaturated solutions have been performed. Diffusivities in undersaturated solutions, were found to vary with lysozyme concentrations. Depending on the salt concentration, the diffusivities either increase or decrease. Interestingly, the corresponding static scattering intensities behave oppositely, Our current analysis indicates that these changes are inconsistent with aggregation in undersaturated solutions. However, the data are compatible with concentration-dependent changes of the interactions between protein and salt.

Rosenberger, Franz↗
DOE OSTI2026

An experimental and kinetic modeling study of the ignition of 2-methyl decane

Ignition delay times (IDTs) of 2-methyl decane (C 11 H 24 -2) are measured in a high-pressure shock tube and in a rapid compression machine at equivalence ratios in the range 0.5–2.0 at 90 % dilution, at temperatures in the range 600–1430 K and at pressures of 15 and 30 bar. To clarify the effect of the branched methyl group on fuel oxidation, IDTs of n-undecane (nC 11 H 24 ) are also measured at similar conditions to those measured for C 11 H 24 -2. A new chemical kinetic mechanism, using C3MechV4.0.1 as the core chemistry, is developed and validated against the new experimental data. The thermodynamic properties of the fuel (RH), alkyl (Ṙ), alkyl peroxy (RȮ 2 ), hydroperoxy-alkyl (Q̇OOH), and peroxy hydroperoxy alkyl (Ȯ 2 QOOH) radicals are updated in both the C 11 H 24 -2 and nC 11 H24 models using THERM25. A reaction path flux analysis for C 11 H 24 -2 at different temperatures was conducted. Compared to nC 11 H 24 , C 11 H 24 -2 shows slower reactivity. At low and intermediate temperatures, the chain propagation pathway Q̇OOH ↔ C 11 cyclic ether + ȮH is favored for C 11 H 24 -2, while the chain branching pathway Q̇OOH ↔ Ȯ 2 QOOH ↔ C 11 carbonyl hydroperoxide (KHP) + ȮH is suppressed, leading to lower reactivity compared to nC 11 H 24 . At high temperatures, the presence of the branched methyl group inhibits the direct decomposition of the fuel, resulting in reduced C 2 H 4 formation, which in turn suppresses the reactivity of the fuel.

2-methyl decane↗
NASA NTRS1961

Kinetics of Hydrogen Oxidation Downstream of Lean Propane and Hydrogen Flames

The decay of hydrogen was measured downstream of lean, flat, premixed hydrogen and propane-air flames seated on cooled porous burners. Experimental variables included temperature, pressure, initial equivalence ratio and diluent. Sampling of burned gas was done through uncooled quartz orifice probes, and the analysis was based on gas chromatography. An approximate treatment of the data in which diffusion was neglected led to the following rate expression for the zone downstream of hydrogen flames d[H (sub 2)] divided by (d times t) equals 1.7 times 10 (sup 10) [H (sub 2)] (sup 3) divided by (sub 2) [O (sub 2)]e (sup (-8100 divided by RT)) moles per liters per second. On the basis of a rate expression of this form, the specific rate constant for the reaction downstream of hydrogen flames was about three times as great as that determined downstream of propane flames. This result was explained on the basis of the existence of a steady state between hydrogen and carbon monoxide in the burned gas downstream of propane flames.

Fine, Burton↗
DOE OSTI2022

Experimental measurements of fluid flow in an 84-pin hexagonal rod bundle with spacer grid for a gas-cooled fast modular reactor

A 50 MW e helium-cooled fast modular reactor (FMR) is under development, and as part of the Department of Energy Integrated Research Project (IRP), Texas A&M University is conducting the thermal-hydraulic characterization of its baseline core configuration. Here, we experimentally investigated the axial and cross flow fields characteristics in the hexagonal fuel rod bundle composed of 84 rods, a central rod, and spacer grids at a Reynolds number of 12,000. A fully transparent experimental facility resembling of one unit of the fuel assembly was constructed. Time-resolved particle image velocimetry (TR-PIV) measurements were performed to characterize hydraulic behavior downstream the spacer grid. Velocity measurements were conducted in the axial and radial direction of the rod bundle. From the PIV velocity vector fields, the full-field flow statistics were computed for the mean velocity, vorticity, and Reynolds stresses. An analysis of the energy decay downstream of the spacer grid was conducted with calculations of secondary-flow intensities, turbulent kinetic energy, power spectrum, and spatial-temporal velocity cross correlations. The vorticity field was obtained and pairs of counter-rotating vortexes were identified using a 3D reconstruction of several measurement planes. The data from this experimental campaign will be used to validate numerical models based on Computational Fluid Dynamics and other codes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Benchmark Modeling and Simulation of the FFTF LOFWOS Test #13 Using SAM

The Fast Flux Test Facility (FFTF) was a 400 MW thermal powered, oxide-fueled, liquid sodium cooled test reactor, built to assist development and testing of advanced fuels and materials for fast breeder reactors. In July 1986, a series of unprotected Loss of Flow Without Scram (LOFWOS) transients were performed in FFTF as part of the Passive Safety Testing (PST) program. The LOFWOS Test #13, which was initiated at 50% power and 100% flow with the pump pony motors left off, has been chosen as a benchmark case by IAEA to support collaborative efforts within international partnerships on the validation of simulation tools and models in the area of sodium fast reactor passive safety in an IAEA Coordinated Research Project (CRP), launched in October 2018. The System Analysis Module (SAM) is an advanced and modern system analysis tool under development at Argonne National Laboratory for advanced non-LWR safety analysis. It utilizes the object-oriented application framework MOOSE to leverage the modern software environment and advanced numerical methods. The capabilities of SAM are being extended to enable the transient modeling, analysis, and design of various advanced nuclear reactor systems. To participate the IAEA CRP and enhance the SAM validation base for advanced reactor transient safety analysis, benchmark simulations of the FFTF LOFWOS Test #13 are performed using the SAM code. In this first phase of the validation effort, the thermal-hydraulic behavior of the reactor system is the focus and the reactor kinetics is not considered in the SAM FFTF model. Instead, the results of Argonne’s neutronics calculations are directly used, including the power shape of the active core region and the power history during the transient. The simulation results of FFTF at steady state agreed well with the measured data from the test. During the transient, reasonably good agreement were also obtained. Future work to improve the model will focus on introducing the reactivity predictions into the model, as well as better understanding or resolving the current discrepancies with the measured data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2001

Thermal/Pyrolysis Gas Flow Analysis of Carbon Phenolic Material

Provided in this study are predicted in-depth temperature and pyrolysis gas pressure distributions for carbon phenolic materials that are externally heated with a laser source. Governing equations, numerical techniques and comparisons to measured temperature data are also presented. Surface thermochemical conditions were determined using the Aerotherm Chemical Equilibrium (ACE) program. Surface heating simulation used facility calibrated radiative and convective flux levels. Temperatures and pyrolysis gas pressures are predicted using an upgraded form of the SINDA/CMA program that was developed by NASA during the Solid Propulsion Integrity Program (SPIP). Multispecie mass balance, tracking of condensable vapors, high heat rate kinetics, real gas compressibility and reduced mixture viscosity's have been added to the algorithm. In general, surface and in-depth temperature comparisons are very good. Specie partial pressures calculations show that a saturated water-vapor mixture is the main contributor to peak in-depth total pressure. Further, for most of the cases studied, the water-vapor mixture is driven near the critical point and is believed to significantly increase the local heat capacity of the composite material. This phenomenon if not accounted for in analysis models may lead to an over prediction in temperature response in charring regions of the material.

Clayton, J. Louie↗