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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

High performance space computing with system-on-chip instrument avionics for space-based Next Generation Imaging Spectrometers (NGIS)

The emergent technology of system-on-chip (SoC) devices promises lighter, smaller, cheaper, and more capable and reliable space electronic systems that could help to unveil some of the most treasured secrets in our universe. This technology is an improvement over the technology that is currently used in space applications, which lags behind state-of-the-art commercial-off-the-shelf (COTS) equipment by several generations. SoC technology integrates all computational power required by next-generation space exploration science instruments onto a single chip. This presentation will describe a Xilinx Zynq-based data acquisition, cloud-screening and compression computing system that has been developed at the Jet Propulsion Laboratory (JPL) for JPL’s Next Generation Imaging Spectrometers (NGIS). The Xilinx Zynq-based Alpha Data hardware assembly fits into a 120mm by 190m by 40mm assembly and uses 9 watts at peak performance. The computing element is a Xilinx Zynq Z7045Q which includes a Kintex-7 FPGA (equivalent to 3 RAD Virtex5 FPGAs in terms of logic cell resources) and dual-core ARM Cortex-A9 Processors (equivalent to 10 RAD750 Power PCs in term of processing capability).

Dolinar, Sam↗
DOE OSTI2025

xGFabric: Coupling Sensor Networks and HPC Facilities with Private 5G Wireless Networks for Real-Time Digital Agriculture

Advanced scientific applications require coupling distributed sensor networks with centralized high-performance computing facilities. Citrus Under Protective Screening (CUPS) exemplifies this need in digital agriculture, where citrus research facilities are instrumented with numerous sensors monitoring environmental conditions and detecting protective screening damage. CUPS demands access to computational fluid dynamics codes for modeling environmental conditions and guiding real-time interventions like water application or robotic repairs. These computing domains have contrasting properties: sensor networks provide low-performance, limited-capacity, unreliable data access, while high-performance facilities offer enormous computing power through high-latency batch processing. Private 5G networks present novel capabilities addressing this challenge by providing low latency, high throughput, and reliability necessary for near-real-time coupling of edge sensor networks with HPC simulations. This work presents xGFabric, an end-to-end system coupling sensor networks with HPC facilities through Private 5G networks. The prototype connects remote sensors via 5G network slicing to HPC systems, enabling real-time digital agriculture simulation.

Digital Agriculture↗
DOE OSTI2021

Projector-Based Quantum Embedding for Molecular Systems: An Investigation of Three Partitioning Approaches

Projector-based embedding is a relatively recent addition to the collection of methods that seek to utilize chemical locality to provide improved computational efficiency. This work considers the interactions between the different proposed procedures for this method and their effects on the accuracy of the results. The interplay between the embedded background, projector type, partitioning scheme, and level of atomic orbital (AO) truncation are investigated on a selection of reactions from the literature. The Huzinaga projection approach proves to be more reliable than the level-shift projection when paired with other procedural options. Active subsystem partitioning from the subsystem projected AO decomposition (SPADE) procedure proves slightly better than the combination of Pipek-Mezey localization and Mulliken population screening (PMM). Along with these two options, a new partitioning criteria is proposed based on subsystem von Neumann entropy and the related subsystem orbital occupancy. This new method overlaps with the previous PMM method, but the screening process is computationally simpler. Finally, AO truncation proves to be a robust option for the tested systems when paired with the Huzinaga projection, with satisfactory results being acquired at even the most severe truncation level.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Root hairs vs. trichomes: Not everyone is straight!

Trichomes show 47 morphological phenotypes, while literature reports only two root hair phenotypes in all plants. However, could hair-like structures exist below-ground in a similar wide range of morphologies like trichomes? Genetic mutants and root hair stress phenotypes point to the possibility of uncharacterized morphological variation existing belowground. For example, such root hairs in Arabidopsis (Arabidopsis thaliana) can be wavy, curled, or branched. We found hints in the literature about hair-like structures that emerge before root hairs belowground. As such, these early emerging hair structures can be potential exceptions to the contrasting morphological variation between trichomes and root hairs. Here, in this work, we show a previously unreported ‘hooked’ hair structure growing below-ground in common bean. The unique ‘hooking’ shape distinguishes the ‘hooked hair’ morphologically from root hairs. Currently, we cannot fully characterize the phenotype of our observation due to the lack of automated methods for phenotyping root hairs. This phenotyping bottleneck also handicaps the discovery of more morphology types that might exist below-ground as manual screening across species is slower than computer-assisted high-throughput screening.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Computational investigation of the impact of metal–organic framework topology on hydrogen storage capacity

Metal–organic frameworks (MOFs) are promising, tunable materials for hydrogen storage. For application under cryogenic operating conditions, past work has run into a ceiling on performance due to a trade-off in the volumetric deliverable capacity (VDC) versus the gravimetric deliverable capacity (GDC). In this study, we computationally constructed and screened 105 230 MOF structures based on 529 nets to explore the effect of underlying topology on the hydrogen storage performance of the resulting materials. A machine learning model was developed based on simulated hydrogen uptake to facilitate screening of the entire dataset, and it successfully identified the top 10% of materials with a root-mean-square error of approximately 1 g L −1 as validated by subsequent grand canonical Monte Carlo simulations. We identified a promising structure based on the tsx topology that exhibits both VDC and GDC higher than the current benchmark material, MOF-5. Our data-driven analysis indicates that nets with higher net density yield MOFs with enhanced volumetric and gravimetric surface areas, thereby improving maximum VDC while shifting the capacity trade-off toward higher GDC.

36 MATERIALS SCIENCE↗
DOE OSTI2022

First-principles Search for Compact Optical Materials [Slides]

Optoelectronics can increase speed and efficiency of information technology. There is a need to miniaturize components below the difrraction limit. Computational pre-screening increases the speed of materials discovery. Factors that must be accounting for beyond raw performance are material stability, cost, and environmental impact.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Tank Waste LDR Organics Data Summary for Sample-and-Send (Rev.1A)

The presence of organic chemicals regulated under the Resource Conservation and Recovery Act (RCRA) Land Disposal Restrictions (LDR) adds complexity to treating and disposing of the low activity fraction of Hanford tank waste if a low temperature treatment method such as grouting is used (SRNL-STI-2020-00228). The complexity arises from the fact that the baseline vitrification method is considered by the Washington State Department of Ecology (Ecology) as providing adequate thermal treatment for organics; a status not automatically extended to a lowtemperature process, such as solidifying the waste in a cementitious waste form. In addition, the Environmental Protection Agency (EPA) LDR program is intended to ensure that wastes are properly treated prior to disposal. Proper treatment makes hazardous waste less harmful to groundwater by reducing the mobility and/or toxicity of the hazardous constituents in the waste. EPA guidance indicates that stabilization/solidification of waste for organics could be considered impermissible dilution under the LDR dilution prohibition. In addition, waste storage activities at Hanford have required transferring and blending waste within the tank system and these activities have potentially altered the concentrations of the hazardous constituents. The LDR dilution prohibition found in 40 Code of Federal Regulations (CFR) 268.3 states that “… no generator, transporter, handler, or owner or operator of a treatment, storage, or disposal facility shall in any way dilute a restricted waste or the residual from treatment of a restricted waste as a substitute for adequate treatment …”. Hence, if LAW is to be treated using low temperature stabilization (such as cementation), then it is important to demonstrate both how past storage activities have contributed to the removal (by vacuum evaporation), or destruction (by in situ decomposition) of the LDR organics and how future retrieval and waste feed preparation will contribute to their removal (by filtration and ion exchange). Demonstrating these processes helps validate that cementation without additional organic treatment does not necessarily represent impermissible dilution. To aid in implementing cementitious solidification of Low Activity Waste (LAW), WRPS has been developing a regulatory and processing LDR treatment variance strategy termed “Sampleand-Send” that relies, in part, on demonstrating that in situ decomposition reactions along with historic evaporation of tank waste has destroyed or removed most of the LDR organics possibly associated with Hanford Tank Waste (SRNL-STI-2020-00582, SRNL-STI-2021-00453, SRNL-STI-2022-00391). Under the Sample-and-Send concept, Hanford tank waste would be retrieved, processed through a Tank-Side Cesium Removal-like system, and staged as a candidate feed that would then be sampled to confirm the waste acceptance criteria is met for solidification in an LAW cementitious treatment facility. If it can be shown that LDR organics are at concentrations below the waste acceptance criteria (WAC) for cementitious stabilization and have been sufficiently removed (by historic evaporation or by filtration and ion exchange during Cs removal), destroyed (by historic in situ decomposition), or are not soluble in LAW above the WAC then additional organic treatment is not needed prior to creating a cementitious final waste form and the concept of Sample-and-Send would be proposed to establish a non-rulemaking site-specific treatment variance using the specified method of treatment “STABL” to remove sampling requirements of the waste form after treatment. Waste not meeting the WAC could either be routed to the Hanford Waste Treatment and Immobilization Plant for LAW vitrification, or further processed by evaporation or chemical oxidation before solidifying in a cementitious waste form. A key component in implementing the Sample-and-Send strategy is identifying which of the 207 LDR organic compounds associated with the RCRA Part A permit application waste codes for the Double Shell Tanks (DSTs) and Single Shell Tanks (SSTs) and any applicable Underlying Hazardous Constituents (UHCs) from 40 CFR 268.48 should be considered as potentially present and thus subject to regulation. In addition, it is also necessary to understand the solubility volatility, and reactivity of these compounds in LAW to identify which of the potentially present LDR organic compounds are not soluble above regulatory levels or are likely to have been removed by historic evaporation or destroyed by in situ decomposition reactions. If there are potentially present LDR organic compounds that have not been removed or destroyed and are soluble above regulatorily significant concentrations then a treatability variance may be needed for these species to eliminate any concerns pertaining to impermissible dilution. The spreadsheet accompanying this calculation report contains the data and logic computations needed to screen the list of 207 LDR organics associated with Hanford tank waste to identify those potentially present and to indicate which compounds may need to be included in a treatability variance.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Strategies for using membrane-based separations to extract critical metals from waste streams

Critical metals are currently extracted by mining followed by their purification. These processes are costly and not environmentally very desirable. In this perspective paper we discuss the potential of extracting these critical metals from a range waste-streams available in abundance globally. These waste streams include brine from desalination plants, effluents from oil drilling and hydraulic fracturing, as well as discharges from various industrial processes such as metal finishing, electroplating, mining, and chemical manufacturing. We show that with a range of new separation processes being developed their separation is showing potential of being both technologically and economically feasible. We also show how high performance computing can be combined with computational models to screen and accelerate the development of new technologies for extracting critical metals from waste streams.

36 MATERIALS SCIENCE↗
NASA NTRS1971

Global trajectory targeting via computer graphics

A technique is described in which the two-point boundary value problem (TPBVP) may be solved with the aid of interactive computer graphics. The particular TPBVP considered is the optimal electric propulsion space trajectory problem. An appropriate two-dimensional projection of the TPBVP mapping, or trajectory, is displayed on the computer's television screen, and a man-in-the-loop varies selected trajectory starting conditions in the fashion of a nonlinear walk until the viewed trajectory endpoint lies near a displayed target. Once global targeting is accomplished in this manner, program internal logic can easily handle local targeting to strongly solve the TPBVP.

Mann, F. I.↗
NASA NTRS1989

Multiplying Video Mixer

Video mixing circuit places transparent overlay image on all or portion of normal image on television screen. Overlay computer-generated graphics, text, or another image. Background video brightness signal fed into one input terminal of circuit, while overlay brightness signal fed into other input terminal. Amplitude of background brightness signal modulated by overlay brightness signal, resulting in video image in which background image appears as though viewed through overlay. Multiplying video mixer, combined with additional circuitry, places transparent or opaque overlay images on normal (background) video images.

Heckt, Neil W.↗
NASA NTRS2011

Generalized Software Architecture Applied to the Continuous Lunar Water Separation Process and the Lunar Greenhouse Amplifier

This innovation provides the user with autonomous on-screen monitoring, embedded computations, and tabulated output for two new processes. The software was originally written for the Continuous Lunar Water Separation Process (CLWSP), but was found to be general enough to be applicable to the Lunar Greenhouse Amplifier (LGA) as well, with minor alterations. The resultant program should have general applicability to many laboratory processes (see figure). The objective for these programs was to create a software application that would provide both autonomous monitoring and data storage, along with manual manipulation. The software also allows operators the ability to input experimental changes and comments in real time without modifying the code itself. Common process elements, such as thermocouples, pressure transducers, and relative humidity sensors, are easily incorporated into the program in various configurations, along with specialized devices such as photodiode sensors. The goal of the CLWSP research project is to design, build, and test a new method to continuously separate, capture, and quantify water from a gas stream. The application is any In-Situ Resource Utilization (ISRU) process that desires to extract or produce water from lunar or planetary regolith. The present work is aimed at circumventing current problems and ultimately producing a system capable of continuous operation at moderate temperatures that can be scaled over a large capacity range depending on the ISRU process. The goal of the LGA research project is to design, build, and test a new type of greenhouse that could be used on the moon or Mars. The LGA uses super greenhouse gases (SGGs) to absorb long-wavelength radiation, thus creating a highly efficient greenhouse at a future lunar or Mars outpost. Silica-based glass, although highly efficient at trapping heat, is heavy, fragile, and not suitable for space greenhouse applications. Plastics are much lighter and resilient, but are not efficient for absorbing longwavelength infrared radiation and therefore will lose more heat to the environment compared to glass. The LGA unit uses a transparent polymer antechamber that surrounds part of the greenhouse and encases the SGGs, thereby minimizing infrared losses through the plastic windows. With ambient temperatures at the lunar poles at 50 C, the LGA should provide a substantial enhancement to currently conceived lunar greenhouses. Positive results obtained from this project could lead to a future large-scale system capable of running autonomously on the Moon, Mars, and beyond. The software for both applications needs to run the entire units and all subprocesses; however, throughout testing, many variables and parameters need to be changed as more is learned about the system operation. The software provides the versatility to permit the software operation to change as the user requirements evolve.

Perusich, Stephen↗
DOE OSTI2021

Computationally Accelerated Discovery and Experimental Demonstration of Gd0.5La0.5Co0.5Fe0.5O3 for Solar Thermochemical Hydrogen Production

Solar thermochemical hydrogen (STCH) production is a promising method to generate carbon neutral fuels by splitting water utilizing metal oxide materials and concentrated solar energy. The discovery of materials with enhanced water-splitting performance is critical for STCH to play a major role in the emerging renewable energy portfolio. While perovskite materials have been the focus of many recent efforts, materials screening can be time consuming due to the myriad chemical compositions possible. This can be greatly accelerated through computationally screening materials parameters including oxygen vacancy formation energy, phase stability, and electron effective mass. In this work, the perovskite Gd 0.5 La 0.5 Co 0.5 Fe 0.5 O 3 (GLCF), was computationally determined to be a potential water splitter, and its activity was experimentally demonstrated. During water splitting tests with a thermal reduction temperature of 1,350°C, hydrogen yields of 101 μmol/g and 141 μmol/g were obtained at re-oxidation temperatures of 850 and 1,000°C, respectively, with increasing production observed during subsequent cycles. This is a significant improvement from similar compounds studied before (La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3 and LaFe 0.75 Co 0.25 O 3 ) that suffer from performance degradation with subsequent cycles. Confirmed with high temperature x-ray diffraction (HT-XRD) patterns under inert and oxidizing atmosphere, the GLCF mainly maintained its phase while some decomposition to Gd 2-x La x O 3 was observed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1980

Capillary device refilling

An analytical and experimental study was conducted dealing with refilling start baskets (capillary devices) with settled fluid. A computer program was written to include dynamic pressure, screen wicking, multiple-screen barriers, standpipe screens, variable vehicle mass for computing vehicle acceleration, and calculation of tank outflow rate and vapor pullthrough height. An experimental apparatus was fabricated and tested to provide data for correlation with the analytical model; the test program was conducted in normal gravity using a scale-model capillary device and ethanol as the test fluid. The test data correlated with the analytical model; the model is a versatile and apparently accurate tool for predicting start basket refilling under actual mission conditions.

Blatt, M. H.↗
NASA NTRS1978

Data screening and preprocessing for Landsat MSS data

Two computer algorithms are presented. The first, called SCREEN, is used to automatically identify pixels representing clouds, cloud shadows, snow, water, or anomalous signals in Landsat-2 data. The second, called XSTAR, compensates Landsat-2 data for the effects of atmospheric haze, without requiring ground measurements or ground references. The presentation of these algorithms includes their theoretical background, algebraic details, and performance characteristics. Verification of the algorithms has for the present been limited to Landsat agricultural data. Plans for further development of the XSTAR technique are also presented.

Lambeck, P. F.↗
DOE OSTI2022

Moving closer to experimental level materials property prediction using AI

Abstract While experiments and DFT-computations have been the primary means for understanding the chemical and physical properties of crystalline materials, experiments are expensive and DFT-computations are time-consuming and have significant discrepancies against experiments. Currently, predictive modeling based on DFT-computations have provided a rapid screening method for materials candidates for further DFT-computations and experiments; however, such models inherit the large discrepancies from the DFT-based training data. Here, we demonstrate how AI can be leveraged together with DFT to compute materials properties more accurately than DFT itself by focusing on the critical materials science task of predicting “formation energy of a material given its structure and composition”. On an experimental hold-out test set containing 137 entries, AI can predict formation energy from materials structure and composition with a mean absolute error (MAE) of 0.064 eV/atom; comparing this against DFT-computations, we find that AI can significantly outperform DFT computations for the same task (discrepancies of $$>0.076$$ > 0.076 eV/atom) for the first time.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Accelerated screening of functional atomic impurities in halide perovskites using high-throughput computations and machine learning

The pressing need for novel materials that can serve rising demands in solar cell and optoelectronic technologies makes the nexus of halide perovskites, high-throughput computations, and machine learning, very promising. Ever increasing amounts of data on the structure, fundamental properties, and device performance of halide perovskites provide opportunities for learning chemical rules and design principles that make these materials attractive, and applying them across wide chemical spaces. In this work, we show that impurity properties of halide perovskites computed using density functional theory (DFT) can be combined with machine learning (ML) to deliver predictive models and quick identification of optoelectronically active impurity atoms. Our computation lead to the largest reported dataset of the formation energies and charge transition levels of Pb-site impurities in methylammonium lead halide (MAPbX 3 ) perovskites. Descriptors are defined to uniquely represent any impurity atom in any MAPbX 3 compound and mapped to the computed impurity properties using regression techniques such as Gaussian process regression, neural networks, and random forests. We use the best optimized predictive models to make predictions for hundreds of impurities across 9 MAPbX 3 compounds and create lists of dominating impurities, that is, impurities that can shift the equilibrium Fermi level in the perovskite as determined by native point defects. Finally, this accelerated screening powered by computations and machine learning can guide the identification of problematic impurities that may cause undesired recombination of charge carriers, as well as impurities that can be deliberately introduced to tune the perovskite conductivity and resulting photovoltaic absorption.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Polarization consistent dielectric screening in polarizable continuum model calculations of solvation energies

A polarization consistent framework, where dielectric screening is affected consistently in polarizable continuum model (PCM) calculations, is employed for the study of solvation energies. The computational framework combines a screened range-separated-hybrid functional (SRSH) with PCM calculations, SRSH-PCM, where dielectric screening is imposed in both PCM self-consistent reaction field (SCRF) iterations and the electronic structure Hamiltonian. We begin by demonstrating the impact of modifying the Hamiltonian to include such dielectric screening in SCRF iterations by considering the solutions of electrostatically embedded Hartree–Fock (HF) exact exchange equations. Long-range screened HF-PCM calculations are shown to capture properly the linear dependence of gap energy of frontier orbitals on the inverse of the dielectric constant, whereas unscreened HF-PCM orbital energies are fallaciously semi-constant with respect to the dielectric constant and, therefore, inconsistent with the ionization energy gaps. Similar trends affect density functional theory (DFT) calculations that aim to achieve predictive quality. Importantly, the dielectric screened calculations are shown to significantly affect DFT- and HF PCM-based solvation energies, where screened solvation energies are smaller compared to the unscreened values. Importantly, SRSH-PCM, therefore, appears to reduce the tendency of DFT-PCM to overestimate solvation energies, where we find the effect to increase with the dielectric constant and the polarity of the molecular solute, trends that enhance the quality of DFT-PCM calculations of solvation energy. Understanding the relationship of dielectric screening in the Hamiltonian and DFT-PCM calculations can ultimately benefit on-going efforts for the design of predictive and parameter free descriptions of solvation energies.

Chemistry↗