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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Microgravity Science Laboratory (MSL-1)

The MSL-1 payload first flew on the Space Shuttle Columbia (STS-83) April 4-8, 1997. Due to a fuel cell problem, the mission was cut short, and the payload flew again on Columbia (STS-94) July 1-17, 1997. The MSL-1 investigations were performed in a pressurized Spacelab module and the Shuttle middeck. Twenty-nine experiments were performed and represented disciplines such as fluid physics, combustion, materials science, biotechnology, and plant growth. Four accelerometers were used to record and characterize the microgravity environment. The results demonstrate the range of quality science that can be conducted utilizing orbital laboratories in microgravity.

Robinson, M. B.↗
DOE OSTI2022

Accurate temperature diagnostics for matter under extreme conditions

The experimental investigation of matter under extreme densities and temperatures, as in astrophysical objects and nuclear fusion applications, constitutes one of the most active frontiers at the interface of material science, plasma physics, and engineering. The central obstacle is given by the rigorous interpretation of the experimental results, as even the diagnosis of basic parameters like the temperature T is rendered difficult at these extreme conditions. Here, we present a simple, approximation-free method to extract the temperature of arbitrarily complex materials in thermal equilibrium from X-ray Thomson scattering experiments, without the need for any simulations or an explicit deconvolution. Our paradigm can be readily implemented at modern facilities and corresponding experiments will have a profound impact on our understanding of warm dense matter and beyond, and open up a variety of appealing possibilities in the context of thermonuclear fusion, laboratory astrophysics, and related disciplines.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1999

Reciprocal Space Mapping of Macromolecular Crystals in the Home Laboratory

Reciprocal space mapping techniques are used widely by the materials science community to provide physical information about their crystal samples. We have used similar methods at synchrotron sources to look at the quality of macromolecular crystals produced both on the ground and under microgravity conditions. The limited nature of synchrotron time has led us to explore the use of a high resolution materials research diffractometer to perform similar measurements in the home laboratory. Although the available intensity is much reduced due to the beam conditioning necessary for high reciprocal space resolution, lower resolution data can be collected in the same detail as the synchrotron source. Experiments can be optimized at home to make most benefit from the synchrotron time available. Preliminary results including information on the mosaicity and the internal strains from reciprocal space maps will be presented.

Snell, Edward H.↗
NASA NTRS2004

New Polymer Electrolyte Cell Systems

PAPERS PUBLISHED: 1. Pappenfus, Ted M.; Henderson, Wesley A.; Owens, Boone B.; Mann, Kent R.; Smyrl, William H. Complexes of Lithium Imide Salts with Tetraglyme and Their Polyelectrolyte Composite Materials. Journal of the Electrochemical Society (2004), 15 1 (2), A209-A2 15. 2. Pappenfus, Ted M.; Henderson, Wesley A.; Owens, Boone B.; Mann, Kent R.; Smyrl, William H. Ionic-liquidlpolymer electrolyte composite materials for electrochemical device applications. Polymeric Materials Science and Engineering (2003), 88 302. 3. Pappenfus, Ted R.; Henderson, Wesley A.; Owens, Boone B.; Mann, Kent R.; and Smyrl, William H. Ionic Conductivity of a poly(vinylpyridinium)/Silver Iodide Solid Polymer Electrolyte System. Solid State Ionics (in press 2004). 4. Pappenfus Ted M.; Mann, Kent R; Smyrl, William H. Polyelectrolyte Composite Materials with LiPFs and Tetraglyme. Electrochemical and Solid State Letters, (2004), 7(8), A254.

Smyrl, William H.↗
DOE OSTI2020

Nanoscale Mass Spectrometry Multimodal Imaging via Tip-Enhanced Photothermal Desorption

Materials ranging from adhesives, pharmaceuticals, lubricants, and personal care products are traditionally studied using macroscopic characterization techniques. However, their functionality is in reality defined by details of chemical organization on often noncrystalline matter with characteristic length scales on the order of microns to nanometers. Additionally, these materials are traditionally difficult to analyze using standard vacuum-based approaches that provide nanoscale chemical characterization due to their volatile and beam-sensitive nature. Therefore, approaches that operate under ambient conditions need to be developed that allow probing of nanoscale chemical phenomena and correlated functionality. Here, we demonstrate a tool for probing and visualizing local chemical environments and correlating them to material structure and functionality using advanced multimodal chemical imaging on a combined atomic force microscopy (AFM) and mass spectrometry (MS) system using tip-enhanced photothermal desorption with atmospheric pressure chemical ionization (APCI). We demonstrate enhanced performance metrics of the technique for correlated imaging and point sampling and illustrate the applicability for the analysis of trace chemicals on a human hair, additives in adhesives on paper, and pharmaceuticals samples notoriously difficult to analyze in a vacuum environment. Overall, this approach of correlating local chemical environments to structure and functionality is key to advancing research in many fields ranging from biology, to medicine, to material science.

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

Machine learned synthesizability predictions aided by density functional theory

Abstract A grand challenge of materials science is predicting synthesis pathways for novel compounds. Data-driven approaches have made significant progress in predicting a compound’s synthesizability; however, some recent attempts ignore phase stability information. Here, we combine thermodynamic stability calculated using density functional theory with composition-based features to train a machine learning model that predicts a material’s synthesizability. Our model predicts the synthesizability of ternary 1:1:1 compositions in the half-Heusler structure, achieving a cross-validated precision of 0.82 and recall of 0.82. Our model shows improvement in predicting non-half-Heuslers compared to a previous study’s model, and identifies 121 synthesizable candidates out of 4141 unreported ternary compositions. More notably, 39 stable compositions are predicted unsynthesizable while 62 unstable compositions are predicted synthesizable; these findings otherwise cannot be made using density functional theory stability alone. This study presents a new approach for accurately predicting synthesizability, and identifies new half-Heuslers for experimental synthesis.

Lee, Andrew (ORCID:0000000153014295)↗
NASA NTRS2004

Lunar and Planetary Science XXXV: Undergraduate Education and Research Programs, Facilities, and Information Access

The titles in this section include: 1) GRIDVIEW: Recent Improvements in Research and Education Software for Exploring Mars Topography; 2) Software and Hardware Upgrades for the University of North Dakota Asteroid and Comet Internet Telescope (ACIT); 3) Web-based Program for Calculating Effects of an Earth Impact; 4) On-Line Education, Web- and Virtual-Classes in an Urban University: A Preliminary Overview; 5) Modelling Planetary Material's Structures: From Quasicrystalline Microstructure to Crystallographic Materials by Use of Mathematica; 6) How We Used NASA Lunar Set in Planetary and Material Science Studies: Textural and Cooling Sequences in Sections of Lava Column from a Thin and a Thick Lava-Flow, from the Moon and Mars with Terrestrial Analogue and Chondrule Textural Comparisons; 7) Classroom Teaching of Space Technology and Simulations by the Husar Rover Model; 8) New Experiments (In Meteorology, Aerosols, Soil Moisture and Ice) on the New Hunveyor Educational Planetary Landers of Universities and Colleges in Hungary; 9) Teaching Planetary GIS by Constructing Its Model for the Test Terrain of the Hunveyor and Husar; 10) Undergraduate Students: An Untapped Resource for Planetary Researchers; 11) Analog Sites in Field Work of Petrology: Rock Assembly Delivered to a Plain by Floods on Earth and Mars; 12) RELAB (Reflectance Experiment Laboratory): A NASA Multiuser Spectroscopy Facility; 13) Full Text Searching and Customization in the NASA ADS Abstract Service.

Source record↗
DOE OSTI2026

Design, characterization and shape recovery behavior of 3D/4D printed shape memory polymers (SMPs)

Shape memory polymers (SMPs) represent a paradigm shift in material science, uniquely capable of undergoing reversible shape transformations triggered by external stimuli, positioning them as pivotal in developing next-generation biomedical devices, aerospace components, and adaptive structures. Extensive research has been done on SMPs with a major focus on high-temperature programming methods, which can limit energy efficiency and applicability with temperature-sensitive materials. Additionally, while various SMP blends have demonstrated great potential, limited work has been done on the suitability for 3D printing these materials, particularly under high-strain and ambient temperature programming conditions. In this study, a three-component optimized SMP composition was evaluated by 3D printing via the Material Extrusion (MEX) technique and investigating its ambient temperature-programming behavior at high strains. The SMP formulation studied was a tailored blend of thermoplastic polyurethane (TPU), polycaprolactone (PCL), and an octadecane diol-based copolymer (OBC) that exhibits robust shape memory behavior, high strain tolerance, and efficient force generation. Rigorous thermal, mechanical, and shape recovery analyses, along with optimized printing parameters and consistent shape recovery rates of up to 90%, were achieved under dynamic mechanical analysis (DMA), even under ambient programming conditions. This work demonstrates the SMP composition’s potential for adaptive, self-deployable systems with 4D printing characteristics ideal for bio-inspired structures and artificial muscle fibers.

Sudan, Kavish [University of Louisville, KY]↗
NASA NTRS2019

Discrete Lattice Material Vacuum Airship

Vacuum airships fueled by renewable energy would reduce reliance on fossil fuel-based modes of transport, lessen the need for limited and non-renewable lifting gases, and can be achieved using novel manufacturing techniques for ultra-light, discrete lattice material systems.The Discrete Lattice Material Vacuum Airships (DLMVA) system combines novel material science and manufacturing technologies for new modes of mass transportation, resulting in a disruptive approach to reduce national resource consumption and emissions. Through the use of high performance building block elements, modular, scalable and extensible aircraft can be rapidly assembled into positive net-buoyancy systems utilizing a vacuum instead of a lifting gas. By using architected lattice material principles, show that lattice materials can overcome stability limitations of previous vacuum balloon designs. Additionally, we show that lattice vacuum balloons are strength limited, rather than stability limited. As a result,airborne infrastructure can be developed to support the proliferation of modern systems such as e-commerce and distributed communications, while simultaneously reducing dependence on finite, non-renewable, emission-heavy resources.

Jenett, Benjamin E.↗
DOE OSTI2023

Prepare Ground States of Highly Frustrated Magnetic Clusters on Quantum Computers

Solving challenging problems in physical, chemical, and materials sciences is one of the most promising applications of quantum utility that can be realized on current noisy hardware, considering (i) the direct map (encoding) from the quantum particles and their interactions to the qubits and their entangling gates and (ii) the rapidly improved quantum hardware and advanced error-mitigation techniques. Understanding quantum spin liquid in frustrated magnetic materials is a longstanding challenge in condensed matter physics and the nature of the ground-state phases is highly debated among researchers. Using IBM quantum computers with superconducting qubits, we implemented a variational quantum eigensolver (VQE) algorithm to prepare the ground states of two 12-site cluster approximations of these highly frustrated magnetic materials. The interaction graphs of the two corresponding Hamiltonians are (a) the six-pointed star graph (a unit cell of the kagome lattice) and (b) the cuboctahedral graph (the kagome on a sphere). These are also two instances of Quantum Max Cut problem. With the VQE based on the Hamiltonian variational ansatz acting on a valence bond solid initial trial state, we prepared the ground states and obtained the exact ground energy on simulator and high accuracy on noisy hardware. The deep ansatz necessary to reach the ground state of the cuboctahedral graph indicates that it is a hard instance of Quantum Max Cut.

Wang, Yan↗
DOE OSTI2022

The Geothermal Data Repository: Ten Years of Supporting the Geothermal Industry with Open Access to Geothermal Data: Preprint

The Department of Energy's (DOE) Geothermal Data Repository (GDR) is celebrating its tenth anniversary! Over the last decade it has grown from the simple idea of storing public data in a centralized location to a valuable tool at the center of the US geothermal scientific community and an integral part of the DOE Geothermal Technologies Office (DOE GTO) project management strategy. Researchers funded by the DOE GTO have contributed over 1,300 data submissions to the GDR. These data have been used to further advancements in geothermal science, economic analysis, exploration, research, development, and operational efficiency. The adoption of open data methodologies and a data management strategy that prioritizes universal open access and standardized, interoperable data have further increased the value of GDR data, making them available across a distributed network of data sharing partners and improving their utility to other industries and related fields, including material science and space exploration. Incorporating feedback from users has been critical to the GDRs success, allowing it to grow over the years to meet the evolving needs of the geothermal community. This paper will explore some of many changes that occurred throughout the GDRs tenure and the lessons learned along the way, as well as highlight some of the new features and recent improvements that been implemented to support innovation, reduce duplication of effort, and advance the geothermal industry as a whole.

accessibility↗
DOE OSTI2022

The Geothermal Data Repository: Ten Years of Supporting the Geothermal Industry with Open Access to Geothermal Data

The Department of Energy's (DOE) Geothermal Data Repository (GDR) is celebrating its tenth anniversary! Over the last decade it has grown from the simple idea of storing public data in a centralized location to a valuable tool at the center of the US geothermal scientific community and an integral part of the DOE Geothermal Technologies Office (DOE GTO) project management strategy. Researchers funded by the DOE GTO have contributed over 1,300 data submissions to the GDR. These data have been used to further advancements in geothermal science, economic analysis, exploration, research, development, and operational efficiency. The adoption of open data methodologies and a data management strategy that prioritizes universal open access and standardized, interoperable data have further increased the value of GDR data, making them available across a distributed network of data sharing partners and improving their utility to other industries and related fields, including material science and space exploration. Incorporating feedback from users has been critical to the GDR's success, allowing it to grow over the years to meet the evolving needs of the geothermal community. This paper will explore some of many changes that occurred throughout the GDRs tenure and the lessons learned along the way, as well as highlight some of the new features and recent improvements that been implemented to support innovation, reduce duplication of effort, and advance the geothermal industry as a whole.

access↗
DOE OSTI2025

Low-Cost, Scalable Sorbents with Balanced Capacity-Kinetics-Thermodynamics for H2 Storage

The goal of this project is to utilize cutting-edge materials science, chemistry, and process engineering to demonstrate the feasibility of a new class of scalable sorbents with unprecedented balance of capacity-kinetics-thermodynamics for H 2 storage in fossil fuel power plants . The core fabrication leverages the unique exotic properties (e.g., high H 2 affinity, ultrahigh surface area, and exceptional thermal, mechanical and chemical stability) of the emerging 2D materials i.e. hexagonal boron nitride (hBN) followed by strategic coupling with alkali metals (Li, Na) dopants and optimal interlayer distance to deliver a stable, long-term energy storage for the grid. Figure 1 shows how this technology works.

08 HYDROGEN↗
DOE OSTI2020

High-Temperature and High-Pressure In Situ Magic Angle Spinning Nuclear Magnetic Resonance Spectroscopy

Nuclear magnetic resonance (NMR) spectroscopy represents an important technique to understand the structure and bonding environment of molecules. There exists a drive to conduct characterization experiment under conditions relevant to the chemical process of interest. To address this, in situ high-temperature, high-pressure MAS NMR methods have been developed to enable the observation of chemical interactions over a range of pressures (vacuum to several hundred bar) and temperatures (well below 0°C to 250°C). Further, the chemical identity of the samples can be comprised of solids, liquids, and gases or mixtures of the three. The method incorporates all-zirconia NMR rotors (sample holder for MAS NMR) which can be sealed using a threaded cap to compress an O-ring. This rotor exhibits great chemical resistance, temperature compatibility, low NMR background, and can withstand high pressures. These factors combined enable its use in a wide range of system combinations which permit its use in diverse fields as carbon sequestration, catalysis, material science, geochemistry, and biology. The flexibility of this technique makes it an attractive option for scientists from numerous disciplines.

Nuclear Magnetic Resonance, NMR, in situ, spectros↗
NASA NTRS2019

Intern Designed Modules for Conducting Potential Microgravity Solidification Experiments Aboard the International Space Station

MMaJIC (Microgravity Materials Joining Investigation Chamber) is a modular experiment chamber for performing materials science investigations. MMaJIC was initially designed to provide a controlled and sealed test environment to accommodate a wide variety of soldering and brazing experiments. However, its modular cartridge design is well suited to easily conduct any number and variety of science experiments. SoLIDD (Solid Liquid Interface Directional Device) is an apparatus for conducting directional solidification experiments with low melting temperature alloys. It has capability for varying the sample’s temperature gradient and growth velocity thus ensuring microstructural development under controlled conditions. ICED-T (Interface Control Experiment with Directional Translation) is an apparatus that conducts directional solidification experiments of transparent materials such that direct observation/recording of the advancing solid/liquid interface can be made. Currently, it is a functional breadboard that consists of the components mounted to a surface that allows the sample to be placed in an upright position. Orientation of the experiment (solid on the bottom, liquid on top) is important during testing ground samples to maintain stability. Ultimately, the goal of MMaJIC, SoLIDD and ICED-T is to conduct successful ground tests and then be re-configured for eventual use by aboard the ISS.

McElderry, Justin↗
NASA NTRS1987

Space research - At a crossroads

Efforts which must be expended if U.S. space research is to regain vitality in the next few years are discussed. Small-scale programs are the cornerstone for big science projects, giving both researchers and students a chance to practice the development of space missions and hardware and identify promising goals for larger projects. Small projects can be carried aloft by balloons, sounding rockets, the Shuttle and ELVs. It is recommended that NASA continue the development of remote sensing systems, and join with other government agencies to fund space-based materials science, space biology and medical research. Increased international cooperation in space projects is necessary for affording moderate to large scale missions, for political reasons, and to maximize available space resources. Finally, the establishment and funding of long-range goals in space, particularly the development of the infrastructure and technologies for the exploration and colonization of the planets, must be viewed as the normal outgrowth of the capabilities being developed for LEO operations.

Mcdonald, Frank B.↗
DOE OSTI2022

Fatty acid capped, metal oxo clusters as the smallest conceivable nanocrystal prototypes

Metal oxo clusters of the type M 6 O 4 (OH) 4 (OOCR) 12 (M = Zr or Hf) are valuable building blocks for materials science. Here, we synthesize a series of zirconium and hafnium oxo clusters with ligands that are typically used to stabilize oxide nanocrystals (fatty acids with long and/or branched chains). The fatty acid capped oxo clusters have a high solubility but do not crystallize, precluding traditional purification and single-crystal XRD analysis. We thus develop alternative purification strategies and we use X-ray total scattering and Pair Distribution Function (PDF) analysis as our main method to elucidate the structure of the cluster core. We identify the correct structure from a series of possible clusters (Zr3, Zr4, Zr6, Zr12, Zr10, and Zr26). Excellent refinements are only obtained when the ligands are part of the structure model. Further evidence for the cluster composition is provided by nuclear magnetic resonance (NMR), infrared spectroscopy (FTIR), thermogravimetry analysis (TGA), and mass spectrometry (MS). We find that hydrogen bonded carboxylic acid is an intrinsic part of the oxo cluster. Using our analytical tools, we elucidate the conversion from a Zr6 monomer to a Zr12 dimer (and vice versa), induced by carboxylate ligand exchange. Finally, we compare the catalytic performance of Zr12-oleate clusters with oleate capped, 5.5 nm zirconium oxide nanocrystals in the esterification of oleic acid with ethanol. The oxo clusters present a five times higher reaction rate, due to their higher surface area. Since the oxo clusters are the lower limit of downscaling oxide nanocrystals, we present them as appealing catalytic materials, and as atomically precise model systems. In addition, the lessons learned regarding PDF analysis are applicable to other areas of cluster science as well, from semiconductor and metal clusters, to polyoxometalates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Graph-EAM: An Interpretable and Efficient Graph Neural Network Potential Framework

The development of deep learning interatomic potentials has enabled efficient and accurate computations in quantum chemistry and materials science, circumventing computationally expensive ab initio calculations. However, the huge number of learnable parameters in deep learning models and their complex architectures hinder physical interpretability and affect the robustness of the derived potential. In this work, we propose graph-EAM, a lightweight graph neural network (GNN) inspired by the empirical embedded atom method to model the interatomic potential of single-element structures. Four material systems: platinum, niobium, silicon, and amorphous-carbon, for which quantum simulation data sets are publicly available, are examined to demonstrate that graph-EAM can achieve high energy and force prediction accuracy-comparable or better than existing state-of-the-art machine learning models-with much fewer parameters. It is also shown that the explicit inclusion of the angular information via three-body atomic density increases the prediction accuracy. In conclusion, the accuracy and efficiency of potentials obtained from graph-EAM can help accelerate the molecular dynamics simulation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗