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NASA NTRSDate not supplied

Nomenclature for the OSIRIS-REx Returned Sample Collection to be Curated at NASA Johnson Space Center

The Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) space-craft collected material from the asteroid Bennu on October 20, 2020. The OSIRIS-REx Sample Return Capsule (SRC) is planned to return to Earth on September 24, 2023. The OSIRIS-REx returned sample collection to be curated at NASA Johnson Space Center (JSC) will include both the asteroid material and the flight hardware. We expect most of the asteroid material to be inside the head of the Touch-and-Go Sample Acquisition Mechanism (TAGSAM), and that this material will include a broad range of particles sizes from as large as a few centimeters to less than a micrometer across in their longest dimension. In addition, asteroid material may have been returned along with the flight hardware: intentionally by the contact pads or screens on the witness plates, or serendipitously wedged into or adhering to hardware items. The nomenclature for this new astromaterials collection must accommodate the different types of samples it comprises.

asteroid↗

DOE OSTI2022

A Universal Machine Learning Model for Elemental Grain Boundary Energies

The grain boundary (GB) energy has a profound influence on the grain growth and properties of polycrystalline metals. Here, we show that the energy of a GB, normalized by the bulk cohesive energy, can be described purely by four geometric features. By machine learning on a large computed database of 361 small Σ (Σ<10) GBs of more than 50 metals, we develop a model that can predict the grain boundary energies to within a mean absolute error of 0.13 J m –2 . More importantly, this universal GB energy model can be extrapolated to the energies of high Σ GBs without loss in accuracy. These results highlight the importance of capturing fundamental scaling physics and domain knowledge in the design of interpretable, extrapolatable machine learning models for materials science.

36 MATERIALS SCIENCE↗

DOE OSTI2023

A deep neural network regressor for phase constitution estimation in the high entropy alloy system Al-Co-Cr-Fe-Mn-Nb-Ni

High Entropy Alloys (HEAs) are composed of more than one principal element and constitute a major paradigm in metals research. The HEA space is vast and an exhaustive exploration is improbable. Therefore, a thorough estimation of the phases present in the HEA is of paramount importance for alloy design. Machine Learning presents a feasible and non-expensive method for predicting possible new HEAs on-the-fly. A deep neural network (DNN) model for the elemental system of: Mn, Ni, Fe, Al, Cr, Nb, and Co is developed using a dataset generated by high-throughput computational thermodynamic calculations using Thermo-Calc. The features list used for the neural network is developed based on literature and freely available databases. A feature significance analysis matches the reported HEAs phase constitution trends on elemental properties and further expands it by providing so far-overlooked features. The final regressor has a coefficient of determination ( r 2 ) greater than 0.96 for identifying the most recurrent phases and the functionality is tested by running optimization tasks that simulate those required in alloy design. The DNN developed constitutes an example of an emulator that can be used in fast, real-time materials discovery/design tasks.

36 MATERIALS SCIENCE↗

NASA NTRS1984

Characterization of surficial geologic units on Venus from Pioneer Venus radar data: A progress report

A classification database using the reflectivity (derived from the altimetry data), rms slope, and the first principal component of altimetry and topographic slope is presented. The resultant clustered data is examined qualitatively as well as quantitatively, to establish the statistical integrity of each cluster by use of an interactive, ternary plotting algorithm. This algorithm plots, for a cluster, the position of each of its pixels within a ternary diagram whose apices represent reflectivity, rms slope, and the first principal component. The digital values in these three databases are normalized such that unity is represented by a value of 255 in each database. The frequencies of each plotted point within the ternary diagram are recorded in order to establish the mode of each cluster. The pixels of each cluster are displayed as one separate color; their ternary plot will show not only the interrelations between clusters, but also the presence of any anomalous points within a cluster. Existing lunar and terrestrial analog radar data is used to establish fields within this ternary diagram that are indicative of as many different geologic materials and tectonics settings as possible. The resultant fields are used to determine empirically the geologic significance of the clusters resulting from the cluster analysis.

Davis, P. A.↗

NASA NTRS1996

X-Ray Spectral Variability in NGC 7469

We present analyses of two Ginga observations and two observations from the ROSAT database of NGC 7469, focusing on the spectral variability observed on timescales of days and longer. During the 1988 Ginga observation, the hardness ratio (8-21 keV/3.4-5.7 keV) increased significantly as the total flux decreased by 30%. As the spectrum is well fit by the reflection model and since the spectra variability dominates the higher energy band, this could be explained by either a variation in the power law index or in the effective covering fraction of the reflecting material. This ambiguity is inherent in reflection modeling of Ginga spectra from moderate flux Seyfert 1 galaxies. Assuming that the power law index did not change, we find that the reflected flux is consistent with being constant, suggesting that much of the reflecting material may be located more than 3 light-days from the continuum source with the molecular torus being a plausible site. This scenario is also supported by the report of a narrow rather than broad iron K-alpha line in the ASCA data by Guainazzi et al. NGC 7469 was faint during the 1989 Ginga observation, but variability was observed with doubling timescale of 5 hr, and the spectrum was harder. A reflection component could not be constrained, and the change in the spectrum could be explained by an increase in neutral absorption. The brighter of two ROSAT spectra was significantly softer, and in both spectra there was evidence of spectral complexity, as has been previously reported by Turner, George, & Mushotzky and Brandt et al. The spectrum could be fit by a variety of two-component models, including a warm absorber model, an ionized disk model, and a thermal model with single-component blackbody spectrum, but joint fitting of the 1988 average Ginga spectrum and the nonsimultaneous ROSAT spectra favored thermal models, and other models required an anomalously high reflection ratio. This model is supported by the observation of a soft excess component and the lack of ionized absorption edges in the ASCA spectrum by Guainazzi et al. The long-term spectral variability could be explained by relative variability between the power-law and soft excess component normalizations, perhaps implying that hard X-ray reprocessing in thermal material does not dominate on long timescales.

Leighly, Karen↗

NASA NTRS2011

Crew Health and Performance Improvements with Reduced Carbon Dioxide Levels and the Resource Impact to Accomplish Those Reductions

Carbon dioxide (CO2) removal is one of the primary functions of the International Space Station (ISS) atmosphere revitalization systems. Primary CO2 removal is via the ISS s two Carbon Dioxide Removal Assemblies (CDRAs) and the Russian carbon dioxide removal assembly (Vozdukh); both of these systems are regenerable, meaning that their CO2 removal capacity theoretically remains constant as long as the system is operating. Contingency CO2 removal capability is provided by lithium hydroxide (LiOH) canisters, which are consumable, meaning that their CO2 removal capability disappears once the resource is used. With the advent of 6 crew ISS operations, experience showing that CDRA failures are not uncommon, and anecdotal association of crew symptoms with CO2 values just above 4 mmHg, the question arises: How much lower do we keep CO2 levels to minimize the risk to crew health and performance, and what will the operational cost to the CDRAs be to do it? The primary crew health concerns center on the interaction of increased intracranial pressure from fluid shifts and the increased intracranial blood flow induced by CO2. Typical acute symptoms include headache, minor visual disturbances, and subtle behavioral changes. The historical database of CO2 exposures since the beginning of ISS operations has been compared to the incidence of crew symptoms reported in private medical conferences. We have used this database in an attempt to establish an association between the CO2 levels and the risk of crew symptoms. This comparison will answer the question of the level needed to protect the crew from acute effects. As for the second part of the question, operation of the ISS s regenerable CO2 removal capability reduces the limited life of constituent parts. It also consumes limited electrical power and thermal control resources. Operation of consumable CO2 removal capability (LiOH) uses finite consumable materials, which must be replenished in the long term. Therefore, increased CO2 removal means increased resource use, with increased logistical capability to maintain necessary resources on board ISS. We must strike a balance between sufficiently low CO2 levels to maintain crew health and CO2 levels which are operationally feasible for the ISS program

James, John T.↗

NASA NTRS2015

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.

Hyde, J. L.↗

NASA NTRS2016

Using CubeSats to Monitor Debris Flux

Recent updates to NASA's Orbital Debris Engineering Model (ORDEM 3.0) include a population of small particles (1-2 mm in size) composed of high-density materials (e.g., steel) that drive much of the predicted risk for satellites in the 700-1000 km altitude regime. This modeled population was based on the analysis of returned surfaces of the Shuttle, which flew below 600 km altitude. The cessation of Shuttle missions, plus the lack of in situ data above 600 km means that a data source is being sought to either confirm or modify this high-density population. One possible data source would be a database of anomalous sporadic changes in spacecraft orbit/orientation that might be due to momentum transfer from small particles too small to seriously damage the spacecraft. Because the momentum imparted from an impact would be tiny, it would most likely show up in the orbital behavior of cubesats and other small satellites. While such small satellites were few in number, this was not a particularly attractive option, but now with the proliferation of cubesats in multiple orbit planes and altitudes, the possible collecting area has increased significantly. This presentation will discuss the physics of momentum-transferring impacts from hypervelocity collisions, and make predictions about rates, directions, and locations of such impacts. In addition, it will include recommendations for satellite users on what kind of data might be worth archiving and investigating.

Matney, Mark↗

DOE OSTI2024

High-throughput approach for investigating interdiffusion in medium- and high-entropy alloys

Interdiffusion experiments are usually time-consuming and tedious since diffusion couples must be annealed at several temperatures for a long time. The efforts required to study interdiffusion in multicomponent alloys increase dramatically as multiple diffusion couples are required to cover broad composition ranges and determine the diffusivities of individual elements in different chemical environments. To circumvent this challenge, we present a high-throughput approach applicable to single-phase and compositionally complex alloys, which are assumed to approximate ideal solid solutions. Here, a simple diffusion-multiple experiment combined with a physically based kinetic model is proposed to efficiently determine the diffusion coefficients of the constituent elements in quaternary CrFeCoNi alloys. Compared with tracer diffusivities reported in the literature, the results, thus, obtained do not differ by more than a factor of 2 and were obtained from a single interdiffusion experiment. In contrast, the diffusivities simulated with commercial mobility and thermodynamic databases are strongly overestimated by a factor ranging from 1 to 16. Therefore, our approach enables high-throughput determination of diffusivities and can help in the design of alloys for high-temperature applications where diffusion plays a key role.

36 MATERIALS SCIENCE↗

NASA NTRS1998

Diode laser absorption sensors for gas-dynamic and combustion flows

Recent advances in room-temperature, near-IR and visible diode laser sources for tele-communication, high-speed computer networks, and optical data storage applications are enabling a new generation of gas-dynamic and combustion-flow sensors based on laser absorption spectroscopy. In addition to conventional species concentration and density measurements, spectroscopic techniques for temperature, velocity, pressure and mass flux have been demonstrated in laboratory, industrial and technical flows. Combined with fibreoptic distribution networks and ultrasensitive detection strategies, compact and portable sensors are now appearing for a variety of applications. In many cases, the superior spectroscopic quality of the new laser sources compared with earlier cryogenic, mid-IR devices is allowing increased sensitivity of trace species measurements, high-precision spectroscopy of major gas constituents, and stable, autonomous measurement systems. The purpose of this article is to review recent progress in this field and suggest likely directions for future research and development. The various laser-source technologies are briefly reviewed as they relate to sensor applications. Basic theory for laser absorption measurements of gas-dynamic properties is reviewed and special detection strategies for the weak near-IR and visible absorption spectra are described. Typical sensor configurations are described and compared for various application scenarios, ranging from laboratory research to automated field and airborne packages. Recent applications of gas-dynamic sensors for air flows and fluxes of trace atmospheric species are presented. Applications of gas-dynamic and combustion sensors to research and development of high-speed flows aeropropulsion engines, and combustion emissions monitoring are presented in detail, along with emerging flow control systems based on these new sensors. Finally, technology in nonlinear frequency conversion, UV laser materials, room-temperature mid-IR materials and broadly tunable multisection devices is reviewed to suggest new sensor possibilities.

Non-NASA Center↗

NASA NTRSDate not supplied

New York Ecological Forecasting: Utilizing NASA Earth Observations to Map Ash Distribution and Inform Emerald Ash Borer Control

Since their first sightings in the U.S. in 2002, emerald ash borer beetles (Agrilus planipennis; EAB) have killed millions of native ash (Fraxinus spp.) trees across 35 states. Infected ash stands frequently exhibit complete mortality, with the predicted result being the functional extinction of native ash in U.S. forests. In August of 2020, EAB was discovered in the 6.1-million-acre Adirondack Park. The team’s partners at the Adirondack Park Invasive Plant Program (APIPP) desired ash tree distribution and EAB susceptibility information to help improve EAB bio-control efficiency and apply the methodology to future invasive programs. To assist, the team mapped ash tree distribution using NASA Earth observations from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Shuttle Radar Topography Mission (SRTM), along with hyperspectral imagery from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Field data from the Monitoring and Managing Ash (MaMA) project, iMapInvasives and iNaturalist databases, and the New York State Department of Environmental Conservation (NYSDEC) provided ground truthing for mapping and modeling. Results indicate that for ash detection, the team’s Spectral Angle Mapping (SAM) hyperspectral classification is slightly more sensitive but less accurate than multispectral Random Forest (RF) classification, though neither method was above a ~20% detection rate. End products include maps of ash extent derived from both imagery types, a model forecasting future spread scenarios based on current EAB presence, and outreach materials. These products inform APIPP’s management decisions and facilitate public awareness of EAB’s threat to communities within the region.

Liam Megraw↗

NASA NTRSDate not supplied

The Containment Assurance Risk Framework of the Mars Sample Return Program

The Mars Sample Return campaign aims at bringing rock and atmospheric samples from Mars to Earth through a series of robotic missions. These missions would collect the samples being cached and deposited on Martian soil by the Perseverance rover, place them in a container, and launch them into Martian orbit for subsequent capture by an orbiter that would bring them back. Given there exists a non-zero probability that the samples contain biological material, precautions are being taken to design systems that would break the chain of contact between Mars and Earth. These include techniques such as sterilization of Martian particles, redundant containment vessels, and a robust reentry capsule capable of accurate landings without a parachute. Requirements exist that the probability of containment not assured of Martian-contaminated material into Earth’s biosphere be less than one in a million. To demonstrate compliance with this strict requirement, a statistical framework was developed to assess the likelihood of containment loss during each sample return phase and make a statement about the total combined mission probability of containment not assured. The work presented here describes this framework, which considers failure modes or fault conditions that can initiate failure sequences ultimately leading to containment not assured. Reliability estimates are generated from databases, design heritage, component specifications, or expert opinion in the form of probability density functions or point estimates and provided as inputs to the mathematical models that simulate the different failure sequences. The probabilistic outputs are then combined following the logic of several fault trees to compute the ultimate probability of containment not assured. Given the multidisciplinary nature of the problem and the different types of mathematical models used, the statistical tools needed for analysis are required to be computationally efficient. While standard Monte Carlo approaches are used for fast models, a multi-fidelity approach to rare event probabilities is proposed for expensive models. In this paradigm, inexpensive low-fidelity models are developed for computational acceleration purposes while the expensive high-fidelity model is kept in the loop to retain accuracy in the results. This work presents an example of end-to-end application of this framework highlighting the computational benefits of a multi-fidelity approach.

Giuseppe Cataldo↗

DOE OSTI2023

Expanding Linker Dimensionality in Metal‐organic Frameworks for sub‐Ångstrom Pore Control for Separation Applications

Abstract Metal‐organic frameworks (MOFs) are a class of porous materials with high surface areas, which are acquiring rapid attention on an exponential basis. A significant characteristic of MOFs is their ability to act as adsorbents to selectively separate component mixtures of similar size, thereby addressing the technological need for an alternative approach to conventional distillation methods. Recently, MOFs comprising a 3‐Dimensional (3D) linker have shown outstanding capabilities for difficult separations compared to the parent 2‐Dimensional (2D) analogue. 3D‐linkers with a polycyclic core are underrepresented in the MOF database due to the widespread preferred use of 2D‐linkers and the misconceived high‐cost of 3D linkers. We summarize the recent research of 3D‐linker MOFs and highlight their beneficial employment for selective gas and hydrocarbon adsorption and separation. Furthermore, we outline forecasts in this area to create a platform for widespread adoption of 3D‐linkers in MOF synthesis.

Macreadie, Lauren K.↗

DOE OSTI2023

Expanding Linker Dimensionality in Metal‐organic Frameworks for sub‐Ångstrom Pore Control for Separation Applications

Macreadie, Lauren K.↗

DOE OSTI2020

Stabilizing the crystal structures of NaFePO 4 with Li substitutions

Due to the high cost and insufficient resources of lithium, alternative sodium-ion batteries have been widely investigated for large-scale applications. NaFePO 4 has the highest theoretical capacity of 154 mA h g -1 among the iron-based phosphates, which makes it an attractive cathode material for Na-ion batteries. Experimentally, LiFePO 4 has been highly successful as a cathode material in Li-ion batteries because its olivine crystal structure provides a stable framework during battery cycling. In NaFePO 4 , maricite replaces olivine as the most stable phase. However, the maricite phase is experimentally found to be electrochemically inactive under normal battery operating voltages (0–4.5 V). We found that partial substitutions of Na with Li stabilize the olivine structure and may be a way to improve the performance of NaFePO 4 cathodes. Using the previously developed structural LiFePO 4 database, here we examine the low-energy crystal structures in the system when we replace Li with Na. The known maricite and olivine NaFePO 4 phases are reconfirmed and an unreported phase with energy between them is identified by our calculations. Besides, the Li-doped olivine type compound Li x Na 1- x FePO 4 with mixed alkali ions retains better energetic stability compared with the other two types of structures of the same composition, as long as the proportion of Li exceeds 0.25. The thermodynamic stability of o-type Li x Na 1- x FePO 4 can be further improved at finite temperatures. The primary limitation of the calculations is that we mainly focus on the zero-temperature condition; however, the relative stability of the structures may vary depending on the ambient temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Machine learning for design principles for single atom catalysts towards electrochemical reactions

Machine learning (ML) integrated density functional theory (DFT) calculations have recently been used to accelerate the design and discovery of heterogeneous catalysts such as single atom catalysts (SACs) through the establishment of deep structure–activity relationships. Here, this review provides recent progress in the ML-aided rational design of heterogeneous catalysts with the focus on SACs in terms of structure–activity relationships, feature importance analysis, high-throughput screening, stability, and metal–support interactions for electrochemistry. Support vector machine (SVM), random forest regression (RFR), and deep neural networks (DNN) along with atomic properties are mainly used for the design of SACs. The ML results have shown that the number of electrons in the d orbital, oxide formation enthalpy, ionization energy, Bader charge, d-band center, and enthalpy of vaporization are mainly the most important parameters for the defining of the structure–activity relationships for electrochemistry. However, the black-box nature of ML techniques occasionally makes a physical interpretation of descriptors, such as the Bader charge, d-band center, and enthalpy of vaporization, non-trivial. At the current stage, ML application is limited by the lack of a large and high-quality database. Future prospects for the development of a large database and a generalized ML algorithm for SAC design are discussed to give insights for further studies in this field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Thermophysical Properties Experimentally Tested for NaCl-KCl-MgCl 2 Eutectic Molten Salt as a Next-Generation High-Temperature Heat Transfer Fluids in Concentrated Solar Power Systems

A new eutectic chloride molten salt, MgCl 2 -KCl-NaCl (wt% 45.98–38.91–15.11), has been recognized as one of the most promising high-temperature heat transfer fluids (HTF) for both heat transfer and thermal storage for the third-generation concentrated solar power (CSP) systems. For the first time, some essential thermophysical properties of this eutectic chloride molten salt needed for basic heat transfer and energy storage analysis in the application of concentrating solar power systems have been experimentally tested and provided as functions of temperature in the range from 450 °C to 700 °C. The studied properties include heat capacity, melting point, heat of fusion, viscosity, vapor pressure, density, and thermal conductivity. The property equations provide essential database for engineers to use to calculate convective heat transfer in concentrated solar receivers, heat exchangers, and thermal storage for concentrated solar power plants.

14 SOLAR ENERGY↗

NASA NTRS2013

Elastic-Plastic J-Integral Solutions or Surface Cracks in Tension Using an Interpolation Methodology. Appendix C -- Finite Element Models Solution Database File, Appendix D -- Benchmark Finite Element Models Solution Database File

No closed form solutions exist for the elastic-plastic J-integral for surface cracks due to the nonlinear, three-dimensional nature of the problem. Traditionally, each surface crack must be analyzed with a unique and time-consuming nonlinear finite element analysis. To overcome this shortcoming, the authors have developed and analyzed an array of 600 3D nonlinear finite element models for surface cracks in flat plates under tension loading. The solution space covers a wide range of crack shapes and depths (shape: 0.2 less than or equal to a/c less than or equal to 1, depth: 0.2 less than or equal to a/B less than or equal to 0.8) and material flow properties (elastic modulus-to-yield ratio: 100 less than or equal to E/ys less than or equal to 1,000, and hardening: 3 less than or equal to n less than or equal to 20). The authors have developed a methodology for interpolating between the goemetric and material property variables that allows the user to reliably evaluate the full elastic-plastic J-integral and force versus crack mouth opening displacement solution; thus, a solution can be obtained very rapidly by users without elastic-plastic fracture mechanics modeling experience. Complete solutions for the 600 models and 25 additional benchmark models are provided in tabular format.

Allen, Phillip A.↗