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Development of Optical Window Material Database for Spaceflight Environments
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"TPSX: Thermal Protection System Expert and Material Property Database"
The Thermal Protection Branch at NASA Ames Research Center has developed a computer program for storing, organizing, and accessing information about thermal protection materials. The program, called Thermal Protection Systems Expert and Material Property Database, or TPSX, is available for the Microsoft Windows operating system. An "on-line" version is also accessible on the World Wide Web. TPSX is designed to be a high-quality source for TPS material properties presented in a convenient, easily accessible form for use by engineers and researchers in the field of high-speed vehicle design. Data can be displayed and printed in several formats. An information window displays a brief description of the material with properties at standard pressure and temperature. A spread sheet window displays complete, detailed property information. Properties which are a function of temperature and/or pressure can be displayed as graphs. In any display the data can be converted from English to SI units with the click of a button. Two material databases included with TPSX are: 1) materials used and/or developed by the Thermal Protection Branch at NASA Ames Research Center, and 2) a database compiled by NASA Johnson Space Center 9JSC). The Ames database contains over 60 advanced TPS materials including flexible blankets, rigid ceramic tiles, and ultra-high temperature ceramics. The JSC database contains over 130 insulative and structural materials. The Ames database is periodically updated and expanded as required to include newly developed materials and material property refinements.
A materials-informatics based study of solid electrolytes and protective coatings for Li batteries
All-solid-state batteries with Li metal anode can address the safety issues surrounding traditional Li-ion batteries as well as the demand for higher energy densities. However, the development of solid electrolytes and protective coatings simultaneously possessing high ionic conductivity and wide electrochemical stability has proven to be a challenge. Here, we present a data-driven approach to explore the Li compound space for promising solid electrolytes and coatings. This is accomplished through the generation of a large database of battery-related materials properties of Li compounds by computing Li+ migration barriers using bond-valence-based pair potentials, and stability windows using density functional theory energies. Using this database, we implement machine learning models that can accurately predict migration barriers and electrochemical stability windows for any new Li compound. Through feature engineering, we ensure that our models are both accurate and interpretable. We perform feature importance analysis on our models to highlight materials properties that can be tuned for future design of coatings/electrolytes. Our database and informatics approach provide a valuable tool for the rapid discovery of new solid-state battery chemistries.
Dataset describing two reference models for full-spectral lighting and daylight simulations together with implementations for two software systems
A dataset of two spectral lighting simulation reference models - one office and one factory hall - is presented. It aims to demonstrate and support full-spectral daylight and electric lighting simulations and facilitate evaluation of non-visual effects of light. The dataset includes Rhino CAD geometry, comprehensive spectral material and light source data and window system BSDF data. Example implementations in the two software tools, Radiance and OWL, enable reproducible workflows and support adoption in other software. The dataset is openly available on Zenodo. The office model reproduces Room 518 at the University of Innsbruck, including a west-facing façade and interior furnishings. The factory hall model follows the proposed geometry in the European standard 15193 for building energy performance. Interior reflectances in the office were measured in-situ using a handheld spectrometer. Exterior spectra and factory hall materials matching specified reflectances were obtained from an online spectral materials database. Glazing transmittance was derived from IGDB data using LBNL Optics/WINDOW. BSDFs for venetian blinds at various tilt angles, and for a diffusing pane adapted from the Complex Glazing Database, were generated in WINDOW. Luminaires in both models are specified with photometric files (Eulumdat/IES) and lamp spectra (Fluorescent 840, 4000 K LED). The provided example implementations (Radiance, OWL) include prepared input data and scripts to run first spectral simulations; example results are also included. The dataset is prepared to support reuse by researchers, designers and software developers for method validation, software engineering and comparison, and development of spectral metrics and controls.
Computational evaluation of new lithium-3 garnets for lithium-ion battery applications as anodes, cathodes, and solid-state electrolytes
In this work, we explore a set of new garnet oxide structures that can be used as an anode, cathode or solid-electrolyte in lithium-ion batteries (LIBs) using high-throughput density functional theory. Specifically, we tested around 180 combinations of elemental substitutions for the dodecahedral X sites and octahedral Y sites in the Li 3 X 3 Y 2 O 12 type garnet structure and identified 19 stable (i.e., on the convex hull) and 11 nearly stable (i.e., within 50 meV/atom of the convex hull) Li 3 garnets with respect to decomposition to other stable phases in the Open Quantum Materials Database in the respective four-dimensional Li-X-Y -O chemical spaces. Our high-throughput screening strategy allows us to elucidate rules for garnet stability in terms of the ionic radii of the constituent elements. We evaluated the electrochemical window of these new, stable/nearly stable Li3-garnet compounds and classify each for potential applications as an anode, cathode, or solid-state electrolyte to be used in LIBs. Finally, Li + ion diffusivity is calculated for the representative Li 3 Nd 3 W 2 O 12 model system. The results we present here are expected to serve as a guideline for designing new garnet oxides for Li-ion battery applications.
Final Results of Shuttle MMOD Impact Database
The Shuttle Hypervelocity Impact Database documents damage features on each Orbiter thought to be from micrometeoroids (MM) or orbital debris (OD). Data is divided into tables for crew module windows, payload bay door radiators and thermal protection systems along with other miscellaneous regions. The combined number of records in the database is nearly 3000. Each database record provides impact feature dimensions, location on the vehicle and relevant mission information. Additional detail on the type and size of particle that produced the damage site is provided when sampling data and definitive spectroscopic analysis results are available. Guidelines are described which were used in determining whether impact damage is from micrometeoroid or orbital debris impact based on the findings from scanning electron microscopy chemical analysis. Relationships assumed when converting from observed feature sizes in different shuttle materials to particle sizes will be presented. A small number of significant impacts on the windows, radiators and wing leading edge will be highlighted and discussed in detail, including the hypervelocity impact testing performed to estimate particle sizes that produced the damage.
High-Throughput Screening of Solid-State Li-Ion Conductors Using Lattice-Dynamics Descriptors
Low lithium-ion migration barriers have recently been associated with low average vibrational frequencies or phonon band centers, further helping identify descriptors for superionic conduction. To further explore this correlation, here we present the computational screening of ~14,000 Li-containing compounds in the Materials Project database using a descriptor based on lattice dynamics reported recently to identify new promising Li-ion conductors. An efficient computational approach was optimized to compute the average vibrational frequency or phonon band center of ~1,200 compounds obtained after pre-screening based on structural stability, band gap, and their composition. Combining a low computed Li phonon band center with large computed electrochemical stability window and structural stability, 18 compounds were predicted to be promising Li-ion conductors, one of which, Li 3 ErCl 6 , has been synthesized and exhibits a reasonably high room-temperature conductivity of 0.05–0.3 mS/cm, which shows the promise of Li-ion conductor discovery based on lattice dynamics.
Using the Shuttle In Situ Window and Radiator Data for Meteoroid Measurements
Every time NASA's Space Shuttle flew in orbit, it was exposed to the natural meteoroid and artificial debris environment. NASA Johnson Space Center maintains a database of impact cratering data of 60 Shuttle missions flown since the mid‐1990's that were inspected after flight. These represent a total net exposure time to the space environment of 2 years. Impact damage was recorded on the windows and radiators, and in many cases information on the impactor material was determined by later analysis of the crater residue. This information was used to segregate damage caused by natural meteoroids and artificial space debris. The windows represent a total area of 3.565 sq m, and were capable of resolving craters down to about 10 micrometers in size. The radiators represent a total area of 119.26 sq m, and saw damage from objects up to approximately 1 mm in diameter. These data were used extensively in the development of NASA's ORDEM 3.0 Orbital Debris Environment Model, and gives a continuous picture of the orbital debris environment in material type and size ranging from about 10 micrometers to 1 mm. However, the meteoroid data from the Shuttles have never been fully analyzed. For the orbital debris work, special "as flown" files were created that tracked the pointing of the surface elements and their shadowing by structure (such as the ISS during docking). Unfortunately, such files for the meteoroid environment have not yet been created. This talk will introduce these unique impact data and describe how they were used for orbital debris measurements. We will then discuss some simple first‐order analyses of the meteoroid data, and point the way for future analyses.
Discovery of Energy Storage Molecular Materials Using Quantum Chemistry-Guided Multiobjective Bayesian Optimization
Redox flow batteries (RFBs) are a promising technology for stationary energy storage applications due to their flexible design, scalability, and low cost. In RFBs, energy is carried in flowable redoxactive materials (redoxmers) which are stored externally and pumped to the cell during operation. Further improvements in the energy density of RFBs necessitates redoxmer designs with wider redox potential windows and higher solubility. Additionally, designing redoxmers with a fluorescence-enabled self-reporting functionality allows monitoring of the state of health of RFBs. To accelerate the discovery of redoxmers with desired properties, state-of-the- art machine learning ( ML) methods, such as multiobjective Bayesian optimization (MBO), are useful. Here, we first employed density functional theory calculations to generate a database of reduction potentials, solvation free energies, and absorption wavelengths for 1400 redoxmer molecules based on a 2,1,3-benzothiadiazole (BzNSN) core structure. From the computed properties, we identified 22 Pareto-optimal molecules that represent best trade-off among all of the desired properties. We further utilized these data to develop and benchmark an MBO approach to identify candidates quickly and efficiently with multiple targeted properties. With MBO, optimal candidates from the 1400-molecule data set can be identified at least 15 times more efficiently compared to the brute force or random selection approach. Importantly, we utilized this approach for discovering promising redoxmers from an unseen database of 1 million BzNSN-based molecules, where we discovered 16 new Pareto-optimal molecules with significant improvements in properties over the initial 1400 molecules. Furthermore, we anticipate that this active learning technique is general and can be utilized for the discovery of any class of functional materials that satisfies multiple desired property criteria.
Highly tunable band inversion in AB 2 X 4 (A=Ge, Sn, Pb; B=As, Sb, Bi; X=Se, Te) compounds
Topological materials have been discovered so far largely by searching for existing compounds in crystallographic databases, but there are potentially new topological materials with desirable features that have not been synthesized. One of the desirable features is high tunability resulting from the band inversion with a very small direct band gap, which can be tuned by changes in pressure or strain to induce a topological phase transition. Here, using density-functional theory (DFT) calculations, we have studied the septuple layered AB 2 X 4 series compounds, where A=(Ge, Sn and Pb), B=(As, Sb and Bi), and X=(Se and Te). With the DFT thermodynamic stability validated by the already-reported compounds in these series, we predict stable Se compounds, which are not found in crystallographic database. Among them, we find that GeBi 2 Se 4 and GeSb 2 Se 4 having a small direct band gap at the Z point are very close to a strong topological insulator, which can be tuned by a moderate pressure to induce the band inversion. Importantly, the topological features with the small direct band gap are well isolated in both momentum and energy windows, which offers high tunability for studying the topological phase transition.
A method and tool to determine the colorimetric and photobiological properties of light transmitted through glass and other optical materials
Here we describe a framework and provides a computational tool to characterize the color quality and biological potential of light that is transmitted through glass and other optical materials. The IES TM-30 framework and Excel computation tool were adapted to evaluate color quality, with measures from CIE S 026, UL 24480, and the WELL Building Standard v2 added to evaluate biological potential. The user selects a pre-transmittance spectral power distribution (SPD), such as for a CIE D-Series Illuminant, Planckian radiation, electric lamp, or measurement of daylight at a building site. The tool allows a user to populate a database with spectral data for glazing or other optical materials, comprising spectral transmission and the spectral reflectance of both sides. The user creates a unit with one, two, or three panes of glazing or other optical materials, and the tool calculates the composite spectral transmittance accounting for reflections between materials. The tool computes the transmitted SPD, then determines colorimetric and photobiological outputs using the transmitted SPD as the test source. Glass, window, and skylight manufacturers can employ the tool to optimize glazing spectral transmission to achieve intentional colorimetric and photobiological performance with transmitted light. Electric lighting manufacturers, designers, and researchers can use the tool to evaluate the impact of glazing units and other optical materials on the color quality and biological potential of transmitted light.
ARES Biennial Report 2012 Final
Since the return of the first lunar samples, what is now the Astromaterials Research and Exploration Science (ARES) Directorate has had curatorial responsibility for all NASA-held extraterrestrial materials. Originating during the Apollo Program (1960s), this capability at Johnson Space Center (JSC) included scientists who were responsible for the science planning and training of astronauts for lunar surface activities as well as experts in the analysis and preservation of the precious returned samples. Today, ARES conducts research in basic and applied space and planetary science, and its scientific staff represents a broad diversity of expertise in the physical sciences (physics, chemistry, geology, astronomy), mathematics, and engineering organized into three offices (figure 1): Astromaterials Research (KR), Astromaterials Acquisition and Curation (KT), and Human Exploration Science (KX). Scientists within the Astromaterials Acquisition and Curation Office preserve, protect, document, and distribute samples of the current astromaterials collections. Since the return of the first lunar samples, ARES has been assigned curatorial responsibility for all NASA-held extraterrestrial materials (Apollo lunar samples, Antarctic meteorites - some of which have been confirmed to have originated on the Moon and on Mars - cosmic dust, solar wind samples, comet and interstellar dust particles, and space-exposed hardware). The responsibilities of curation consist not only of the longterm care of the samples, but also the support and planning for future sample collection missions and research and technology to enable new sample types. Curation provides the foundation for research into the samples. The Lunar Sample Facility and other curation clean rooms, the data center, laboratories, and associated instrumentation are unique NASA resources that, together with our staff's fundamental understanding of the entire collection, provide a service to the external research community, which relies on access to the samples. The curation efforts are greatly enhanced by a strong group of planetary scientists who conduct peerreviewed astromaterials research. Astromaterials Research Office scientists conduct peer-reviewed research as Principal or Co-Investigators in planetary science (e. g., cosmochemistry, origins of solar systems, Mars fundamental research, planetary geology and geophysics) and participate as Co-Investigators or Participating Scientists in many of NASA's robotic planetary missions. Since the last report, ARES has achieved several noteworthy milestones, some of which are documented in detail in the sections that follow. Within the Human Exploration Science Office, ARES is a world leader in orbital debris research, modeling and monitoring the debris environment, designing debris shielding, and developing policy to control and mitigate the orbital debris population. ARES has aggressively pursued refinements in knowledge of the debris environment and the hazard it presents to spacecraft. Additionally, the ARES Image Science and Analysis Group has been recognized as world class as a result of the high quality of near-real-time analysis of ascent and on-orbit inspection imagery to identify debris shedding, anomalies, and associated potential damage during Space Shuttle missions. ARES Earth scientists manage and continuously update the database of astronaut photography that is predominantly from Shuttle and ISS missions, but also includes the results of 40 years of human spaceflight. The Crew Earth Observations Web site (http://eol.jsc.nasa.gov/Education/ESS/crew.htm) continues to receive several million hits per month. ARES scientists are also influencing decisions in the development of the next generation of human and robotic spacecraft and missions through laboratory tests on the optical qualities of materials for windows, micrometeoroid/orbital debris shielding technology, and analog activities to assess surface science operations. ARES serves as host to numerous students and visiting scientists as part of the services provided to the research community and conducts a robust education and outreach program. ARES scientists are recognized nationally and internationally by virtue of their success in publishing in peer-reviewed journals and winning competitive research proposals. ARES scientists have won every major award presented by the Meteoritical Society, including the Leonard Medal, the most prestigious award in planetary science and cosmochemistry; the Barringer Medal, recognizing outstanding work in the field of impact cratering; the Nier Prize for outstanding research by a young scientist; and several recipients of the Nininger Meteorite Award. One of our scientists received the Department of Defense (DoD) Joint Meritorious Civilian Service Award (the highest civilian honor given by the DoD). ARES has established numerous partnerships with other NASA Centers, universities, and national laboratories. ARES scientists serve as journal editors, members of advisory panels and review committees, and society officers, and several scientists have been elected as Fellows in their professional societies. This biennial report summarizes a subset of the accomplishments made by each of the ARES offices and highlights participation in ongoing human and robotic missions, development of new missions, and planning for future human and robotic exploration of the solar system beyond low Earth orbit.
Carbon Management Projects (CONNECT) Database and Explorer
Overview The Carbon Management Projects (CONNECT) Toolkit is an online exploratory visualization tool developed by the U.S. Department of Energy's (DOE) Office of Fossil Energy and Carbon Management (FECM) with support from other federal agencies such as the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Transportation (DOT). It provides a single point of access to authoritative information on federal agency investment in a portfolio of research, development, and demonstration (RD&D) projects that have been publicly announced to advance technologies for point source carbon capture, carbon dioxide removal, transport, storage, and conversion, collectively referred to as carbon management. The RD&D programs covered in this tool are authorized by annual congressional appropriations ("Base Program") and the 2021 Infrastructure Investment and Jobs Act (IIJA). The tool also incorporates public information on other federal initiatives, such as the Regional Clean Hydrogen Hubs, and public information released by other government agencies, such as the Environmental Protection Agency's (EPA) and Primacy States’ Underground Injection Control Class VI permits and EPA’s facility level greenhouse gas (GHG) emissions. Developed in a geographic information system, the tool organizes carbon management projects into five groups based on the primary technology that a project aims to advance, each visually represented as a digital layer ("carbon management project layer"). Only federally funded projects are included, which can be awarded projects that are completed or ongoing, or projects that have been selected but are currently under negotiation. Project information can be viewed in the map or in the attribute table below it when turned on. In the map view, each project is displayed at either its host site (for field work), where available, or its performer site (project lead's location, further explained in the table below). Host sites and performer sites are represented in distinct icons. Several reference layers offer additional public information on infrastructural and natural resource environment for carbon management. These reference layers, combined with multiple geographical basemaps, enable users to visualize the carbon management project layers in context. Carbon management project information will be updated monthly based on feedback and information availability. Carbon management project layers Point Source Carbon Capture (PSC) This layer contains DOE-funded projects focused on capturing carbon dioxide (CO2) from power plants or industrial facilities. Carbon Dioxide Removal (CDR) This layer contains DOE-funded projects focused on capturing CO2 from the atmosphere, including direct air capture (DAC) and DAC hubs, direct ocean capture, enhanced mineralization, and biomass carbon removal and storage. For projects with multiple host sites, each of the sites are displayed individually with the project cost and cost sharing information representing the total for the entire project. Carbon Transport This layer contains DOE- and DOT-funded projects focused on CO2 transport. The Transport Research and Development sublayer contains projects that do not involve physical infrastructure; the Proposed Transport Corridor sublayer contains projects for which either a route for the transport infrastructure has been proposed or a general area for the transport infrastructure has been identified. Carbon Storage This layer contains DOE-funded key projects focused on CO2 storage. For projects with multiple field-work sites, each of the sites are displayed individually on the map with the project cost and cost sharing information representing the overall total for the entire project. Carbon Conversion This layer contains DOE-funded projects focused on converting CO2 into economically valuable products. Reference layers The following layers provide additional information in the geographic proximity of carbon management projects. Users should reference the original sources for more details (weblinks provided below and in pop-up windows on the map). Regional Clean Hydrogen Hub and Facility These layers illustrate the approximate areas of the Regional Clean Hydrogen Hubs announced by DOE's Office of Clean Energy Demonstrations (OCED) and the approximate locations of individual facilities that constitute the hubs (see "Where are the H2Hubs located?" on the webpage linked above). EPA Facility Level GHG Emissions (direct emitter) This layer shows direct CO2 emissions from stationary sources in 2022, using data extracted from EPA's Facility Level Information on GreenHouse gases Tool (FLIGHT). Captured and injected CO2 are not deducted from direct emitters’ total emissions. Contact EPA for additional details. Underground Injection Control Class VI permit/permit application This layer shows the locations of CO2 injection wells that are granted or in the process of applying for an Underground Injection Control Class VI permit by EPA or a Primacy State (currently Louisiana, North Dakota, and Wyoming). The URLs for the permits or permit applications are provided in the pop-up windows associated with the well locations. Contact EPA for additional details. Carbon Storage Resource This layer contains information on prospective CO2 storage resources in saline formations and oil and gas reservoirs provided by the National Carbon Sequestration Database and Geographic Information System (NATCARB) spatial database. Contact NETL for additional details. Existing CO2 pipeline This layer shows active CO2 pipelines based on information digitized from the map issued by the Pipeline and Hazardous Materials Safety Administration (PHMSA). Contact PHMSA for additional details.
Deciphering the Oxygen Absorption Pre-edge: A Caveat on its Application for Probing Oxygen Redox Reactions in Batteries
The pre-edges of oxygen-K X-ray absorption spectra have been ubiquitous in transition metal (TM) oxide studies in various fields, especially on the fervent topic of oxygen redox states in battery electrodes. However, critical debates remain on the use of the O-K pre-edge variations upon electrochemical cycling as evidences of oxygen redox reactions, which has been a popular practice in the battery field. This study presents an investigation of the O-K pre-edge of 55 oxides covering all 3d TMs with different elements, structures, and electrochemical states through combined experimental and theoretical analyses. It is shown unambiguously that the O-K pre-edge variation in battery cathodes is dominated by changing TM-d states. Furthermore, the pre-edge enables a unique opportunity to project the lowest unoccupied TM-d states onto one common energy window, leading to a summary map of the relative energy positions of the low-lying TM states, with higher TM oxidation states at lower energies, corresponding to higher electrochemical potentials. The results naturally clarify some unusual redox reactions, such as Cr 3+/6+ . This work provides a critical clarification on O-K pre-edge interpretation and more importantly a benchmark database of O-K pre-edge for characterizing redox reactions in batteries and other energy materials.
IRAD
IRAD (Ion Irradiation and Radiation Damage) is an open-source GUI for SRIM-like vacancy production and implanted ion profile calculations. Using updated databases, IRAD is accessible at https://code.ornl.gov/liny/irad for Windows systems. It performs energy-corrected Iradina calculations, automatically determining dpa and implanted ion concentration, considering total ion fluence. Additional results like ion trajectories, final positions, stopping power distribution, etc., are available. Advanced settings permit customization of parameters such as stopping power database, incident ion angle, and 3D target simulations.
FY18 J23X PSDT Final Report: Shock Initiation of PBX 9502 Lot HOL88H891-008
This report details a series of plate impact experiments on the insensitive explosive PBX 9502 (95% TATB, 5% Kel-F 800) with lot number HOL88H891-008. This is a ’virgin’ lot (no recycled material used), for which many detonation performance measurements are available; the addition of these 1-D shock initiation experiments will aid model calibration efforts for this material. Samples were machined from isostatically-pressed billets with anominal density of 1.89 g/cc. The evolution of the shock to a detonation was characterized by 9 embedded magnetic particle velocity gauges, and 116 embedded magnetic time of arrival gauges (AKA shock trackers). Pho-ton Doppler velocimetry (PDV) with a LiF window was used at the back surface of the samples to capture the wave profile exiting the sample. Six experiments were performed, covering a pressure range of 10.8–18.6 GPa and run distances to detonation of 2.7–12.2+ mm. The shock initiation of this lot is found to be consistent with Pop plots reported for other lots of PBX 9502. All data have been uploaded to the LANL Small Scale Database for use by the research community.
Critical statistical assessment of data in metal additive manufacturing
Obtaining high quality data reflecting the relationships between the additive manufacturing (AM) process parameters, material microstructure and mechanical properties is crucial for the use of machine learning in AM. A database of over 4,000 data entries of metal AM was created thanks to a large number of literature studies on key process parameters and indicators of build quality. Meta-analysis reveals critical biases in the literature. Firstly, majority of studies report only high quality builds, these imbalances in reporting result in weak correlation between process parameters, properties and consolidation, limiting the ability of machine learning models to generalize beyond optimized conditions. Nevertheless, the trained models accurately predict yield strength ($R^2 = 0.85$), suggesting that certain process–property relationships are effectively captured within these models. Secondly, quantitative microstructural data are largely absent, limiting the learning of the microstructure-mechanical properties relationships. Finally, current process window identification is based largely on the consolidation, despite significant uncertainty in its measurement. It is important to identify the process map on the basis of not only the consolidation, but also mechanical behaviour under loading. Such a identification shows that 316 L and Inconel have much larger process map (i.e. highly printable) in comparison to the AlSi10Mg and Ti6Al4V.