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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Experimentally Verified Alkane Adsorption Isotherms in Nanoporous Materials from Literature Meta-Analysis

Identification of independent experimental replicate measurements of well-defined physical properties provides a useful way to assess the reproducibility of literature reports of these properties. Prior meta-analysis of this kind for single-component adsorption of CO 2 and alcohols in nanoporous materials showed that ~20% of reported isotherms for these molecules were inconsistent with available replicate measurements. Here, we extend this analysis to the single-component adsorption of alkanes in nanoporous materials using a collection of 2998 experimental isotherms. Among these isotherms, 846 replicates were identified and analyzed. Many more replicates are available for CH 4 adsorption than for any other alkane. Our analysis finds that 15% of the replicate alkane isotherms are inconsistent with other replicate measurements. Furthermore, after discarding these outlier isotherms we report graphical and numerical consensus isotherms for 93 independent combinations of adsorbate, adsorbent, and temperature as well as an assessment of another 124 independent systems for which two replicate isotherms are available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2007

Emissivity Results on High Temperature Coatings for Refractory Composite Materials

The directional emissivity of various refractory composite materials considered for application for reentry and hypersonic vehicles was investigated. The directional emissivity was measured at elevated temperatures of up to 3400 F using a directional spectral radiometric technique during arc-jet test runs. A laboratory-based relative total radiance method was also used to measure total normal emissivity of some of the refractory composite materials. The data from the two techniques are compared. The paper will also compare the historical database of Reinforced Carbon-Carbon emissivity measurements with emissivity values generated recently on the material using the two techniques described in the paper.

Ohlhorst, Craig W.↗
DOE OSTI2023

A mechanistic model for creep and thermal aging in Alloy 709

This report describes a physics-based model for creep and thermal aging in Alloy 709. Alloy 709 is an advanced austenitic alloy, targeted for use in future Sodium Fast Reactors (SFRs) and other advanced reactors. The material has superior high temperature properties compared to currently qualified 316 and 304 stainless steels. However, the available creep and thermal aging test database for Alloy 709 is significantly more limited compared to the historical materials. The physics-based model developed here is one way to accelerate the qualification of the material by providing more accurate long-term predictions for creep properties and thermal aging, compared to current empirical time-extrapolate techniques. The crystal plasticity finite element model is used to predict the deformation and failure of alloy 709. The same setup for the CPFE model is used in both the baseline model calibration process and the simulation campaigns for parameter inference. Specific constitutive choices are made for Alloy 709 to capture the primary deformation mechanisms. The dislocation creep formulation developed by Hu and Cocks is extended to account for coupled precipitation formation and the grain boundary cavitation model developed by Sham, Needleman, et al. is used to model grain boundary cavitation-induced failure. A novel update algorithm is proposed to render the semi-discrete constitutive update for the Sham-Needleman model unconditionally stable. A progressive calibration approach is adopted based on the observations that several types of material responses can be effectively decoupled. A surrogate model is trained based on full-fledged CPFE simulations to accelerate the forward model evaluations, and stochastic variational inference (SVI) is used to calibrate the unknown microstructural model parameters. The calibrated mechanistic model is used to predict the long-term creep life of Alloy 709, and the predictions are compared against classical empirical approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Virtual node graph neural network for full phonon prediction

Understanding the structure-property relationship is crucial for designing materials with desired properties. The past few years have witnessed remarkable progress in machine-learning methods for this connection. However, substantial challenges remain, including the generalizability of models and prediction of properties with materials-dependent output dimensions. Here we present the virtual node graph neural network to address the challenges. By developing three virtual node approaches, we achieve Γ-phonon spectra and full phonon dispersion prediction from atomic coordinates. We show that, compared with the machine-learning interatomic potentials, our approach achieves orders-of-magnitude-higher efficiency with comparable to better accuracy. This allows us to generate databases for Γ-phonon containing over 146,000 materials and phonon band structures of zeolites. Additionally, our work provides an avenue for rapid and high-quality prediction of phonon band structures enabling materials design with desired phonon properties. The virtual node method also provides a generic method for machine-learning design with a high level of flexibility. In this study, the authors present a virtual node graph neural network to enable the prediction of material properties with variable output dimensions. This method offers fast and accurate predictions of phonon band structures in complex solids.

36 MATERIALS SCIENCE↗
NASA NTRS1991

Morphology and microstructure of composite materials

Lightweight continuous carbon fiber based polymeric composites are currently enjoying increasing acceptance as structural materials capable of replacing metals and alloys in load bearing applications. As with most new materials, these composites are undergoing trials with several competing processing techniques aimed at cost effectively producing void free consolidations with good mechanical properties. As metallic materials have been in use for several centuries, a considerable database exists on their morphology - microstructure; and the interrelationships between structure and properties have been well documented. Numerous studies on composites have established the crucial relationship between microstructure - morphology and properties. The various microstructural and morphological features of composite materials, particularly those accompanying different processing routes, are documented.

Tiwari, S. N.↗
NASA NTRS1996

Frequency scanning capaciflector for capacitively determining the material properties

A capaciflector sensor system scanned in frequency is used to detect the permittivity of the material of an object being sensed. A capaciflector sensor element, coupled to current-measuring voltage follower circuitry, is driven by a frequency swept oscillator and generates an output which corresponds to capacity as a function of the input frequency. This swept frequency information is fed into apparatus e.g. a digital computer for comparing the shape of the capacitance vs. frequency curve against characteristic capacitor vs. frequency curves for a variety of different materials which are stored, for example, in a digital memory of the computer or a database. Using a technique of pattern matching, a determination is made as to the identification of the material. Also, when desirable, the distance between the sensor and the object can be determined.

Campbell, Charles E.↗
NASA NTRS2015

Computational Process Modeling for Additive Manufacturing (OSU)

Powder-Bed Additive Manufacturing (AM) through Direct Metal Laser Sintering (DMLS) or Selective Laser Melting (SLM) is being used by NASA and the Aerospace industry to "print" parts that traditionally are very complex, high cost, or long schedule lead items. The process spreads a thin layer of metal powder over a build platform, then melts the powder in a series of welds in a desired shape. The next layer of powder is applied, and the process is repeated until layer-by-layer, a very complex part can be built. This reduces cost and schedule by eliminating very complex tooling and processes traditionally used in aerospace component manufacturing. To use the process to print end-use items, NASA seeks to understand SLM material well enough to develop a method of qualifying parts for space flight operation. Traditionally, a new material process takes many years and high investment to generate statistical databases and experiential knowledge, but computational modeling can truncate the schedule and cost -many experiments can be run quickly in a model, which would take years and a high material cost to run empirically. This project seeks to optimize material build parameters with reduced time and cost through modeling.

Bagg, Stacey↗
DOE OSTI2020

Quantum anomalous Hall effect in two-dimensional magnetic insulator heterojunctions

Abstract Recent years have witnessed tremendous success in the discovery of topological states of matter. Particularly, sophisticated theoretical methods in time-reversal-invariant topological phases have been developed, leading to the comprehensive search of crystal database and the prediction of thousands of topological materials. In contrast, the discovery of magnetic topological phases that break time reversal is still limited to several exemplary materials because the coexistence of magnetism and topological electronic band structure is rare in a single compound. To overcome this challenge, we propose an alternative approach to realize the quantum anomalous Hall (QAH) effect, a typical example of magnetic topological phase, via engineering two-dimensional (2D) magnetic van der Waals heterojunctions. Instead of a single magnetic topological material, we search for the combinations of two 2D (typically trivial) magnetic insulator compounds with specific band alignment so that they can together form a type-III broken-gap heterojunction with topologically non-trivial band structure. By combining the data-driven materials search, first-principles calculations, and the symmetry-based analytical models, we identify eight type-III broken-gap heterojunctions consisting of 2D ferromagnetic insulators in the MXY compound family as a set of candidates for the QAH effect. In particular, we directly calculate the topological invariant (Chern number) and chiral edge states in the MnNF/MnNCl heterojunction with ferromagnetic stacking. This work illustrates how data-driven material science can be combined with symmetry-based physical principles to guide the search for heterojunction-based quantum materials hosting the QAH effect and other exotic quantum states in general.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Statistics on magnetic properties of Co compounds: A database-driven method for discovering Co-based ferromagnets

The search for new ferromagnetic compounds is often targeted at known structure families, particularly those containing iron, cobalt, and manganese. Here, we propose a method to expand this search to lesser-known structure types, using a database of experimental Curie and Néel temperatures. This study, in particular, illustrates the case of compounds containing the element cobalt, and we demonstrate how the use of such a database can lead to the discovery of ferromagnetic materials that had previously been overlooked. We report statistics from a literature survey of the magnetic properties of Co-based compounds with more than 33 at. % Co. We classify more than 13 000 compounds by structure type, cobalt content, and magnetic ground state. From these data, compounds TaCo 2 Ga, La 6 Co 13 Bi, and Nd 2 Co 3 were identified as potential ferromagnets, and we confirm their ferromagnetic ordering theoretically via first-principles calculations and experimentally via synthesis and characterization measurements. In addition, the analysis is focused on the collection of data trends and discovery of ferromagnetic materials with easy-axis magnetic anisotropy. Both known ferromagnetic materials with unknown magnetic anisotropy, and unstudied compounds were considered. From the subset of known ferromagnets with unknown anisotropy, the compound Co 2 Mg was synthesized, characterized, and determined to have easy-axis magnetic anisotropy at room temperature.

36 MATERIALS SCIENCE↗
NASA NTRS1987

Atlas of reflectance spectra of terrestrial, lunar, and meteoritic powders and frosts from 92 to 1800 nm

The spectra of samples of several powder and frost materials are presented to serve in a reference database for future far-UV scans of solar system bodies. The spectra cover in the 92-1800 nm wavelengths, i.e., wavenumbers 110,000-5600/cm and photon energies from 13.5-1.5 eV. Preparation procedures for the particulates are delineated. The survey includes feldspars, orthopyroxenes, clinopyroxenes, olivines, assorted minerals, achondrites, carbonaceous chondrites and ordinary chondrites, lunar soils and rocks. Frosts of H2O, CO2, NH3 and SO2 gases were also examined. The data are expected to aid in obtaining spectral matches for asteroids and meteoroids when far-UV telescopy of solar system bodies is performed.

Wagner, Jeffrey K.↗
NASA NTRS1992

Wiring for aerospace applications

In this paper, the authors summarize the current state of knowledge of arc propagation in aerospace power wiring and efforts by the National Aeronautics and Space Administration (NASA) towards the understanding of the arc tracking phenomena in space environments. Recommendations will be made for additional testing. A database of the performance of commonly used insulating materials will be developed to support the design of advanced high power missions, such as Space Station Freedom and Lunar/Mars Exploration.

Christian, J. L., Jr.↗
NASA NTRS2005

RP-1 Thermal Stability and Copper Based Materials Compatibility Study

A series of electrically heated tube tests was performed at the NASA Glenn Research Center s Heated Tube Facility to investigate the effect that sulfur content, test duration, and tube material play in the overall thermal stability and materials compatibility characteristics of RP-1. Scanning-electron microscopic (SEM) analysis in conjunction with energy dispersive spectroscopy (EDS) were used to characterize the condition of the tube inner wall surface and any carbon deposition or corrosion formed during these runs. Results of the parametric study indicate that tests with standard RP-1 (total sulfur -23 ppm) and pure copper tubing are characterized by a depostion/deposit shedding process producing local wall temperature swings as high as 500 F. The effect of this shedding is to keep total carbon deposition levels relatively constant for run times from 20 minutes up to 5 hours, though increasing tube pressure drops were observed in all runs. Reduction in the total sulfur content of the fuel from 23 ppm to less than 0.1 ppm resulted in the elimination of deposit shedding, local wall temperature variation, and the tube pressure drop increases that were observed in standard sulfur level RP-1 tests. The copper alloy GRCop-84, a copper alloy developed specifically for high heat flux applications, was found to exhibit higher carbon deposition levels compared to identical tests performed in pure copper tubes. Results of the study are consistent with previously published heated tube data which indicates that small changes in fuel total sulfur content can lead to significant differences in the thermal stability of kerosene type fuels and their compatibility with copper based materials. In conjunction with the existing thermal stability database, these findings give insight into the feasibility of cooling a long life, high performance, high-pressure liquid rocket combustor and nozzle with RP-1.

Stiegemeier, B. R.↗
NASA NTRS2015

3D-Laser-Scanning Technique Applied to Bulk Density Measurements of Apollo Lunar Samples

In order to better interpret gravimetric data from orbiters such as GRAIL and LRO to understand the subsurface composition and structure of the lunar crust, it is import to have a reliable database of the density and porosity of lunar materials. To this end, we have been surveying these physical properties in both lunar meteorites and Apollo lunar samples. To measure porosity, both grain density and bulk density are required. For bulk density, our group has historically utilized sub-mm bead immersion techniques extensively, though several factors have made this technique problematic for our work with Apollo samples. Samples allocated for measurement are often smaller than optimal for the technique, leading to large error bars. Also, for some samples we were required to use pure alumina beads instead of our usual glass beads. The alumina beads were subject to undesirable static effects, producing unreliable results. Other investigators have tested the use of 3d laser scanners on meteorites for measuring bulk volumes. Early work, though promising, was plagued with difficulties including poor response on dark or reflective surfaces, difficulty reproducing sharp edges, and large processing time for producing shape models. Due to progress in technology, however, laser scanners have improved considerably in recent years. We tested this technique on 27 lunar samples in the Apollo collection using a scanner at NASA Johnson Space Center. We found it to be reliable and more precise than beads, with the added benefit that it involves no direct contact with the sample, enabling the study of particularly friable samples for which bead immersion is not possible

Macke, R. J.↗
DOE OSTI2022

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.

36 MATERIALS SCIENCE↗
DOE OSTI2024

From Design to Device: Challenges and Opportunities in Computational Discovery of p -Type Transparent Conductors

A high-performance p -type transparent conductor (TC) does not yet exist but could lead to advances in a wide range of optoelectronic applications and enable new architectures for, e.g., next-generation photovoltaic (PV) devices. High-throughput computational material screenings have been a promising approach to filter databases and identify new p -type TC candidates and some of these predictions have been experimentally validated. However, most of these predicted candidates do not have experimentally achieved properties on par with n -type TCs used in solar cells and therefore have not yet been used in commercial devices. Thus, there is still a significant divide between transforming predictions into results that are actually achievable in the laboratory and an even greater lag in scaling predicted materials into functional devices. In this perspective, we outline some of the major disconnects in this materials discovery process—from scaling computational predictions into synthesizable crystals and thin films in the laboratory to scaling laboratory-grown films into real-world solar devices—and share insights to inform future strategies for TC discovery and design. Published by the American Physical Society 2024

14 SOLAR ENERGY↗
DOE OSTI2026

Database and deep-learning scalability of anharmonic phonon properties by automated brute-force first-principles calculations

Understanding the anharmonic phonon properties of crystal compounds—such as phonon lifetimes and thermal conductivities—is essential for investigating and optimizing their thermal transport behaviors. These properties also impact optical, electronic, and magnetic characteristics through interactions between phonons and other quasiparticles and fields. In this study, we develop an automated first-principles workflow to calculate anharmonic phonon properties and build a comprehensive database encompassing more than 6500 inorganic compounds. Utilizing this dataset, we train a graph neural network model to predict thermal conductivity values and spectra from structural parameters, demonstrating a scaling law in which prediction accuracy improves with increasing training data size. High-throughput screening with the model enables the identification of materials exhibiting extreme thermal conductivities—both high and low. The resulting database offers valuable insights into the anharmonic behavior of phonons, thereby accelerating the design and development of advanced functional materials.

Ohnishi, Masato [University of Tokyo (Japan); Inst↗
DOE OSTI2022

End-to-end optimization for battery materials and molecules by combining graph neural networks and reinforcement learning

The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to design new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.

25 ENERGY STORAGE↗