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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Machine learning defect properties in Cd-based chalcogenides

Impurity energy levels in the band gap can have serious consequences for a semiconductor's performance as a photovoltaic absorber. Data-driven approaches can help accelerate the prediction of point defect properties in common semiconductors, and thus lead to the identification of potential deep lying impurity states. In this work, we use density functional theory (DFT) to compute defect formation energies and charge transition levels of hundreds of impurities in CdX chalcogenide compounds, where X = Te, Se or S. We apply machine learning techniques on the DFT data and develop on-demand predictive models for the formation energy and relevant transition levels of any impurity atom in any site. The trained ML models are general and accurate enough to predict the properties of any possible point defects in any Cd-based chalcogenide, as we prove by testing on a few selected defects in mixed chalcogen compounds CdTe 0.5 Se 0.5 and CdSe 0.5 S 0.5 . The ML framework used in this work can be extended to any class of semiconductors.

density functional theory↗
DOE OSTI2020

Kilopower - Powering the Future of Space Exploration [Poster]

The Kilopower Project was initiated by NASA’s Space Technology Mission Directorate to demonstrate subsystem-level technology readiness of small space fission power in a relevant environment (TRL 5) for space science and human exploration power needs. The Kilopower Project centerpiece is the Kilowatt Reactor Using Stirling Technology (KRUSTY) test, which consists of the development and testing of a ground technology demonstrator of a 1 kWe class fission power system. The technologies to be developed and validated by KRUSTY are extensible to space fission power systems from 1 to 10 kWe, which can enable modular surface fission power systems for human exploration, as well as higher power future potential deep space science missions.

42 ENGINEERING↗
NASA NTRS2012

Effect of Rare Earth Elements (Er, Ho) on Semi-Metallic Materials (ScN) in an Applied Electric Field

The development of materials and fabrication technology for field-controlled spectrally active optics is essential for applications such as membrane optics, filters for LIDARs, windows for sensors, telescopes, spectroscopes, cameras and flat-panel displays. The dopants of rare earth elements, in a host of optical systems, create a number of absorption and emission band structures and can easily be incorporated into many high quality crystalline and amorphous hosts. In wide band-gap semiconductors like ScN, the existing deep levels can capture or emit the mobile charges, and can be ionized with the loss or capture of the carriers which are the fundamental basis of concept for smart optic materials. The band gap shrinkage or splitting with dopants supports the possibility of this concept. In the present work, a semi-metallic material (ScN) was doped with rare earth elements (Er, Ho) and tested under an applied electric field to characterize spectral and refractive index shifts by either Stark or Zeeman Effect. These effects can be verified using the UV-Vis spectroscopy, the Hall Effect measurement and the ellipsometric spectroscopy. The optical band gaps of ScN doped with Er and doped with Ho were experimentally estimated as 2.33eV and 2.24eV ( 0.2eV) respectively. This is less than that of undoped ScN (2.5 0.2eV). The red-shifted absorption onset is a direct evidence for the decrease of band gap energy (Eg), and the broadening of valence band states is attributable to the doping cases. A decrease in refractive index with an applied field was observed as a small shift in absorption coefficient using a variable angle spectroscopic ellipsometer. In the presence of an electric field, mobile carriers are redistributed within the space charge region (SCR) to produce this electro-refractive effect. The shift in refractive index is also affected by the density and location of deep potential wells within the SCR. In addition, the microstructure change was observed by a TEM analysis. These results give an insight for future applications for the field-controlled spectrally active material systems.

Kim, Hyunjung↗
NASA NTRS2015

Extended Hard-X-Ray Emission in the Inner Few Parsecs of the Galaxy

The Galactic Centre hosts a puzzling stellar population in its inner few parsecs, with a high abundance of surprisingly young, relatively massive stars bound within the deep potential well of the central supermassive black hole, Sagittarius A* (ref. 1). Previous studies suggest that the population of objects emitting soft X-rays (less than 10 kiloelectronvolts) within the surrounding hundreds of parsecs, as well as the population responsible for unresolved X-ray emission extending along the Galactic plane, is dominated by accreting white dwarf systems2, 3, 4, 5.

x-ray emission↗
NASA NTRS2016

Nuclear Systems Kilopower Overview

The Nuclear Systems Kilopower Project was initiated by NASAs Space Technology Mission Directorate Game Changing Development Program in fiscal year 2015 to demonstrate subsystem-level technology readiness of small space fission power in a relevant environment (Technology Readiness Level 5) for space science and human exploration power needs. The Nuclear Systems Kilopower Project consists of two elements. The primary element is the Kilopower Prototype Test, also called the Kilopower Reactor Using Stirling Technology(KRUSTY) Test. This element consists of the development and testing of a fission ground technology demonstrator of a 1 kWe fission power system. A 1 kWe system matches requirements for some robotic precursor exploration systems and future potential deep space science missions, and also allows a nuclear ground technology demonstration in existing nuclear test facilities at low cost. The second element, the Mars Kilopower Scalability Study, consists of the analysis and design of a scaled-up version of the 1 kWe reference concept to 10 kWe for Mars surface power projected requirements, and validation of the applicability of the KRUSTY experiment to key technology challenges for a 10 kWe system. If successful, these two elements will lead to initiation of planning for a technology demonstration of a 10 kWe fission power capability for Mars surface outpost power.

Space Nuclear Power↗
NASA NTRS2017

Kilopower: Small and Affordable Fission Power Systems for Space

The Nuclear Systems Kilopower Project was initiated by NASA's Space Technology Mission Directorate Game Changing Development Program in fiscal year 2015 to demonstrate subsystem-level technology readiness of small space fission power in a relevant environment (Technology Readiness Level 5) for space science and human exploration power needs. The Nuclear Systems Kilopower Project centerpiece is the Kilopower Reactor Using Stirling Technology (KRUSTY) test, which consists of the development and testing of a fission ground technology demonstrator of a 1 kWe-class fission power system. The technologies to be developed and validated by KRUSTY are extensible to space fission power systems from 1 to 10 kWe, which can enable higher power future potential deep space science missions, as well as modular surface fission power systems for exploration. The Kilopower Project is cofounded by NASA and the Department of Energy National Nuclear Security Administration (NNSA).KRUSTY include the reactor core, heat pipes to transfer the heat from the core to the power conversion system, and the power conversion system. Los Alamos National Laboratory leads the design of the reactor, and the Y-12 National Security Complex is fabricating it. NASA Glenn Research Center (GRC) has designed, built, and demonstrated the balance of plant heat transfer and power conversion portions of the KRUSTY experiment. NASA MSFC developed an electrical reactor simulator for non-nuclear testing, and the design of the reflector and shielding for nuclear testing. In 2016, an electrically heated non-fissionable Depleted Uranium (DU) core was tested at GRC in a configuration identical to the planned nuclear test. Once the reactor core has been fabricated and shipped to the Device Assembly Facility at the NNSAs Nevada National Security Site, the KRUSTY nuclear experiment will be assembled and tested. Completion of the KRUSTY experiment will validate the readiness of 1 to 10 kWe space fission technology for NASAs future requirements for sunlight-independent space power. An early opportunity for demonstration of In-Situ Resource Utilization (ISRU) capability on the surface of Mars is currently being considered for 2026 launch. Since a space fission system is the leading option for power generation for the first Mars human outpost, a smaller version of a planetary surface fission power system could be built to power the ISRU demonstration and ensure its end-to-end validity. Planning is underway to start the hardware development of this subscale flight demonstrator in 2018.

Space nuclear power↗
NASA NTRS2020

Kilopower Project: The KRUSTY Fission Power Experiment and Potential Missions

The Kilopower Project was initiated by NASA’s Space Technology Mission Directorate/Game Changing Development Program in fiscal year 2015 to demonstrate subsystem-level technology readiness of small space fission power in a relevant environment (Technology Readiness Level 5) for space science and human exploration power needs. The Kilopower Project centerpiece is the Kilowatt Reactor Using Stirling TechnologY (KRUSTY) test, which consists of the development and testing of a ground technology demonstrator of a 1-kW(electric)–class fission power system (FPS). The technologies to be developed and validated by KRUSTY are extensible to space FPSs from 1 to 10 kW(electric), which can enable modular surface FPSs for human exploration as well as higher-power future potential deep space science missions. The KRUSTY demonstration is cofunded by NASA and the U.S. Department of Energy National Nuclear Security Administration. The KRUSTY demonstration in the National Critical Experiment Research Center’s Device Assembly Facility was completed in the first quarter of 2018.

Space nuclear reactor↗
NASA NTRS2022

The Co2 Profile and Analytical Model for the Pioneer Venus Large Probe Neutral Mass Spectrometer

We present a significantly updated CO2 altitude profile for Venus (64.2–0.9 km) and provide support for a potential deep lower atmospheric haze of particles (≤17 km). We extracted this information by developing a new analytical model for mass spectra obtained by the Pioneer Venus Large Probe (PVLP) Neutral Mass Spectrometer (LNMS). Our model accounts for changes in LNMS configuration and output during descent and enables the disentanglement of isobaric species via a data fitting routine that adjusts for mass-dependent changes in peak shape. The model yields CO2 in units of density (kg m−3), isotope ratios for 13C/12C and 18O/16O, and 14 measures of CO2 density across 55.4–0.9 km, which represents the most complete altitude profile for CO2 at ≤60 km to date. The CO2 density profile is also consistent with the pressure, temperature, and volumetric gas measurements from the PVLP and VeNeRa spacecraft. Nominal and low-noise operations for the LNMS mass analyzer are supported by the behaviors (e.g., ionization yields, fragmentation yields, and peak shapes) of several internal standards (e.g., CH3+, CH4+, 40Ar+, 136Xe2+, and 136Xe+), which were tracked across the descent. Lastly, our review of the CO2 profile and LNMS spectra reveals hitherto unreported partial and rapidly clearing clogs of the inlet in the lower atmosphere, along with several ensuing data spikes at multiple masses. Together, these observations suggest that atmospheric intake was impacted by particles at ≤17 km and that rapid particle degradation at the inlet yielded a temporary influx of mass signals into the LNMS.

Venus↗
DOE OSTI2023

Overview of the Pathways to CO2 Utilization and Storage for the Intermountain West Region

The topic of the webinar focused on findings from the first phase of I-WEST initiative, specifically related to CO2 utilization and storage as one of the many potential deep decarbonization pathway available to the region. Specifically, the seminar presented topics like: an overview of CCUS technology and benefits; a highlight of a variety of CO2 storage and utilization approaches available to the region, relevant governing regulations, and technical and non-technical grand challenges associated with each option; findings from an assessment of opportunities for CCUS deployment at significant scale within the Intermountain West; and context to help listeners better understand the technical aspects of CCUS and how they interface with economic, social, and policy aspects of decarbonization applicable to the I-WEST geographic region.

Vikara, Derek↗
DOE OSTI2021

Modeling Liquid Water by Climbing up Jacob’s Ladder in Density Functional Theory Facilitated by Using Deep Neural Network Potentials

Within the framework of Kohn–Sham density functional theory (DFT), the ability to provide good predictions of water properties by employing a strongly constrained and appropriately normed (SCAN) functional has been extensively demonstrated in recent years. Here, we further advance the modeling of water by building a more accurate model on the fourth rung of Jacob’s ladder with the hybrid functional, SCAN0. In particular, we carry out both classical and Feynman path-integral molecular dynamics calculations of water with the SCAN0 functional and the isobaric–isothermal ensemble. To generate the equilibrated structure of water, a deep neural network potential is trained from the atomic potential energy surface based on ab initio data obtained from SCAN0 DFT calculations. For the electronic properties of water, a separate deep neural network potential is trained by using the Deep Wannier method based on the maximally localized Wannier functions of the equilibrated trajectory at the SCAN0 level. The structural, dynamic, and electric properties of water were analyzed. The hydrogen-bond structures, density, infrared spectra, diffusion coefficients, and dielectric constants of water, in the electronic ground state, are computed by using a large simulation box and long simulation time. For the properties involving electronic excitations, we apply the GW approximation within many-body perturbation theory to calculate the quasiparticle density of states and bandgap of water. Compared to the SCAN functional, mixing exact exchange mitigates the self-interaction error in the meta-generalized-gradient approximation and further softens liquid water toward the experimental direction. For most of the water properties, the SCAN0 functional shows a systematic improvement over the SCAN functional. However, some important discrepancies remain. The H-bond network predicted by the SCAN0 functional is still slightly overstructured compared to the experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Modeling the Solvation and Acidity of Carboxylic Acids Using an Ab Initio Deep Neural Network Potential

Formic and acetic acid constitute the simplest of carboxylic acids, yet they exhibit fascinating chemistry in the condensed phase such as proton transfer and dimerization. The go-to method of choice for modeling these rare events have been accurate but expensive ab-initio molecular dynamics simulations. Here, we present a deep neural network potential trained using accurate ab-initio data that can be used in tandem with enhanced-sampling methods to perform an efficient exploration of the free-energy surface of aqueous solutions of weak carboxylic acids. In particular, we show that our model captures proton dissociation and provides a good estimate of the pK a , as well as the dimerization of formic and acetic acid. This provides a suitable starting point for applications in different research areas where computational efficiency coupled with the accuracy of ab-initio methods is required.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2024

Theoretical Prediction of Thermal Expansion Anisotropy for Y 2 Si 2 O 7 Environmental Barrier Coatings Using a Deep Neural Network Potential and Comparison to Experiment

Environmental barrier coatings (EBCs) are an enabling technology for silicon carbide (SiC)-based ceramic matrix composites (CMCs) in extreme environments such as gas turbine engines. However, development of new coating systems is hindered by the large design space and difficulty in predicting properties for these materials. Density Functional Theory (DFT) has successfully been used to model and predict some thermodynamic and thermo-mechanical properties of high-temperature ceramics for EBCs, although these calculations are challenging due to their high computational costs. In this work, we use machine learning to train a deep neural network potential (DNP) for Y 2 Si 2 O 7 , which is then applied to calculate thermodynamic and thermo-mechanical properties at near-DFT accuracy much faster and using less computational resources than DFT. We use this DNP to predict phonon-based thermodynamic properties of Y 2 Si 2 O 7 with good agreement to DFT and experiments. We also utilize the DNP to calculate the anisotropic, lattice direction-dependent coefficients of thermal expansion (CTEs) for Y 2 Si 2 O 7 . Molecular dynamics trajectories using the DNP correctly demonstrate accurate prediction of the anisotropy of the CTE in good agreement with diffraction experiments. In the future, this DNP could be applied to accelerate additional property calculations for Y 2 Si 2 O 7 compared to DFT or experiments.

rare earth silicates↗
DOE OSTI2024

Theoretical Prediction of Thermal Expansion Anisotropy for Y 2 Si 2 O 7 Environmental Barrier Coatings Using a Deep Neural Network Potential and Comparison to Experiment

Environmental barrier coatings (EBCs) are an enabling technology for silicon carbide (SiC)-based ceramic matrix composites (CMCs) in extreme environments such as gas turbine engines. However, the development of new coating systems is hindered by the large design space and difficulty in predicting the properties for these materials. Density Functional Theory (DFT) has successfully been used to model and predict some thermodynamic and thermo-mechanical properties of high-temperature ceramics for EBCs, although these calculations are challenging due to their high computational costs. In this work, we use machine learning to train a deep neural network potential (DNP) for Y 2 Si 2 O 7 , which is then applied to calculate the thermodynamic and thermo-mechanical properties at near-DFT accuracy much faster and using less computational resources than DFT. We use this DNP to predict the phonon-based thermodynamic properties of Y 2 Si 2 O 7 with good agreement to DFT and experiments. We also utilize the DNP to calculate the anisotropic, lattice direction-dependent coefficients of thermal expansion (CTEs) for Y 2 Si 2 O 7 . Molecular dynamics trajectories using the DNP correctly demonstrate the accurate prediction of the anisotropy of the CTE in good agreement with the diffraction experiments. In the future, this DNP could be applied to accelerate additional property calculations for Y 2 Si 2 O 7 compared to DFT or experiments.

36 MATERIALS SCIENCE↗
NASA NTRS2011

Potential Uses of Deep Space Cooling for Exploration Missions

Nearly all exploration missions envisioned by NASA provide the capability to view deep space and thus to reject heat to a very low temperature environment. Environmental sink temperatures approach as low as 4 Kelvin providing a natural capability to support separation and heat rejection processes that would otherwise be power and hardware intensive in terrestrial applications. For example, radiative heat transfer can be harnessed to cryogenically remove atmospheric contaminants such as carbon dioxide (CO2). Long duration differential temperatures on sunlit versus shadowed sides of the vehicle could be used to drive thermoelectric power generation. Rejection of heat from cryogenic propellant could avoid temperature increase thus avoiding the need to vent propellants. These potential uses of deep space cooling will be addressed in this paper with the benefits and practical considerations of such approaches.

Chambliss, Joseph↗
NASA NTRS2012

Potential Uses of Deep Space Cooling for Exploration Missions

Nearly all exploration missions envisioned by NASA provide the capability to view deep space and thus to reject heat to a very low temperature environment. Environmental sink temperatures approach as low as 4 Kelvin providing a natural capability to support separation and heat rejection processes that would otherwise be power and hardware intensive in terrestrial applications. For example, radiative heat transfer can be harnessed to cryogenically remove atmospheric contaminants such as carbon dioxide (CO2). Long duration differential temperatures on sunlit versus shadowed sides of the vehicle could be used to drive thermoelectric power generation. Rejection of heat from cryogenic propellant could counter temperature increases thus avoiding the need to vent propellants. These potential uses of deep space cooling will be addressed in this paper with the benefits and practical considerations of such approaches.

Chambliss, Joe↗
NASA NTRSDate not supplied

A MULTI TARGETED DIETARY SUPPLEMENT AS A POTENTIAL COUNTERMEASURE FOR DEEP SPACE EXPLORATION

Future deep space exploration to the Moon and Mars and beyond are currently major goals of NASA. Space flight presents unique challenges to the human physiology from the combined effects of microgravity, social isolation, altered circadian rhythm and radiation. Oxidative stress has been implicated as a crucial factor in space environment induced injury. Elucidating these detrimental effects on the central nervous system and brain is a primary objective, as they may result in adverse changes in astronaut behavior, mood and performance of critical tasks. We were recently funded by HRP Human Factors Behavioral Performance (HFBP) Element to test the hypothesis that Galactic Cosmic Ray Simulation (GCRsim) Ionizing Radiation (IR), microgravity and social isolation combine synergistically to trigger an oxidative stress response that alters immune homeostasis, brain structure and function, and neurobehavioral and cognitive performance. This project will identify potential biomarkers for, and mechanisms underlying, structural and functional changes in the immune and nervous systems leading to behavioral/cognitive performance deficits, and its potential application to develop effective countermeasures to mitigate negative health effects of long duration space habitation. Countermeasures to offset neurological damaged and cognitive deficits are paramount for protecting astronauts during deep space transits, but many countermeasures have been found to be unsuitable in ground-based model studies. We have developed a multi targeted dietary supplement (MTDS) designed to simultaneously ameliorate oxidative stress, inflammatory processes, energetic shortfalls, and membrane and mitochondrial deterioration. Administration of this MTDS has improved cognition and longevity in age accelerated and normal aging mice. Specifically, the MTDS was found to prevent a decline in mitochondrial complex III activity and cell loss, as well as prevent an increase in protein carbonyls and mitochondrial 3-nitrotyrosine in the brain of these mice. Further, administration of the MTDS was also found to reduce bone marrow chromosomal aberrations, DNA damage, lymphocyte apoptosis after whole body exposure of 2 Gy γ radiation. Mice exposed to a high dose cranially (10 Gy) had decreased cognitive responses (seen as increased latency time to uncover buried food and decreased novel object recognition), increased plasma 8-OHdG levels, increased markers of cell stress in the brain, decreased hippocampal brain-derived neurotrophic factor (BDNF) protein and decreased plasma levels of cytokines, all of which were ameliorated with treatment of the MTDS. As we have shown the supplement is protective in models of cognitive damage similar space environment stressors, particularly increased oxidative stress, we propose it may be a suitable countermeasure for upcoming deep space exploration.

Stephanie Puukila↗