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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Sharp Refractory Composite Leading Edges on Hypersonic Vehicles

On-going research of advanced sharp refractory composite leading edges for use on hypersonic air-breathing vehicles is presented in this paper. Intense magnitudes of heating and of heating gradients on the leading edge lead to thermal stresses that challenge the survivability of current material systems. A fundamental understanding of the problem is needed to further design development. Methodology for furthering the technology along with the use of advanced fiber architectures to improve the thermal-structural response is explored in the current work. Thermal and structural finite element analyses are conducted for several advanced fiber architectures of interest. A tailored thermal shock parameter for sharp orthotropic leading edges is identified for evaluating composite material systems. The use of the tailored thermal shock parameter has the potential to eliminate the need for detailed thermal-structural finite element analyses for initial screening of material systems being considered for a leading edge component.

Walker, Sandra P.↗
DOE OSTI2025

High-Temperature Gas Sensor Materials with Properties Predicted via First-Principles Calculations with Machine Learning Modeling and Experimental Corroboration

Understanding the temperature dependence of functional properties of sensing materials is vital for their applications in combustion environments. The electron-phonon coupling that derives the electronic structure change with temperatures is a key property of interest as it affects other sensing responses. Herein, we first assess the temperature dependence of band gap renormalization in sensing materials by employing Allen-Heine-Cardona (AHC) theory with density functional theory (DFT) simulations corroborated with experimental observation. As the AHC calculations are impractical for high-throughput screening of materials, we employ data-driven Gaussian process regression to predict the parameters employed in the O’Donnell empirical model from a set of physical features. To mitigate the reliability issues arising from the small size of the dataset, we apply a Bayesian technique to improve the generalizability of the data-driven models as well as to quantify the uncertainty associated with theoretical predictions. These models capture well the overall trend of the O’Donnell parameters with respect to a reduced feature set obtained by transforming the available physical features. Quantifying the associated uncertainty helps us understand the reliability of the predictions and, therefore, the variation of bandgap as a function of temperature for other novel materials. The predicted candidates from machine learning models are further validated by experiments and DFT calculations.

bandgap renormalization↗
NASA NTRS1975

A new arc heater shroud test technique for thermo-structural testing of full-scale, nose-tip skirt materials

An arc heater shroud test technique was developed for thermostructural testing of full-scale, missile nose tip-skirt assemblies. Reentry trajectory simulation is provided by changing the arc heater operation in a prescribed manner through manual and automatic controls. Excellent test repeatability allows screening of materials by direct comparison of test results. Continuous recordings of model surface temperature, pressure, heat flux, and model internal temperatures are made at several locations during the test.

Williams, R. R.↗
DOE OSTI2021

Computation-guided discovery of coating materials to stabilize the interface between lithium garnet solid electrolyte and high-energy cathodes for all-solid-state lithium batteries

All-solid-state batteries with a lithium metal anode, enabled by lithium garnet solid electrolytes such as Li 7 La 3 Zr 2 O 12 (LLZO), are a promising next-generation energy-storage technology. The further development of all-solid-state battery requires the integration of high-energy cathodes such as LiNi 1-x-y Mn x Co y O 2 (NMC) with the garnet solid electrolyte with stable and low-resistance interfaces, which requires a coating layer to stabilize the interface during high-temperature sintering and electrochemical cycling. In order to guide the future development of interfacial coatings, we perform high-throughput thermodynamic analyses based on first-principles computation to investigate the stability of LLZO garnet and high-energy NMC cathodes with a wide range of materials chemistries. Here our study reveals the factors governing the materials stability with LLZO garnet and NMC cathodes, and identifies the mechanisms of good coating layers stable with LLZO and NMC. In addition to classifying known coating layers, our study provides detailed guiding charts and multiple new materials systems as promising coatings for stabilizing LLZO—NMC interfaces to enable high-energy-density garnet-based all-solid-state batteries. Our demonstrated computation scheme and high-throughput analyses are generally applicable to investigate and screen coating materials for stabilizing interfaces in energy-related applications.

25 ENERGY STORAGE↗
DOE OSTI2022

Experimental screening of salt hydrates for thermochemical energy storage for building heating application

The selection of a suitable salt hydrate for use in a thermochemical energy storage system is challenging. In this work, the most promising salts to store intermediate heat energy were selected and tested. The criteria set are; volumetric energy density of >500 kWh m-3 with a dehydration temperature of <100 degrees C, material cost of <3.5 USD kg-1 (<15 USD kWh-1), melting does not occur during dehydration and safety. Based on that, the salt hydrates SrCl 2 , MgSO 4 , Na 3 PO 4 , MgCl 2 and SrBr 2 were selected and tested experimentally. A constant temperature and humidity chamber was used to measure moisture sorption of different salts. The hydration is investigated under the conditions of 20 degrees C and 20, 30, 40, 60 and 80% RH, while dehydration is investigated under the conditions of 70, 100 and 140 degrees C using an oven. These dehydration temperatures of <100 degrees C are suitable for solar application whereas the dehydration temperature of 140 degrees C is suitable for waste heat. Furthermore, the salts are cycled over 30 times under the hydration conditions of 20 degrees C, 60% RH with a dehydration temperature of 100 degrees C. From these results, it is concluded that SrCl 2 and SrBr 2 are the most promising salts. This study outlines both the advantages and disadvantages of each salt and states the conditions they are most suitable for.

25 ENERGY STORAGE↗
NASA NTRS1997

A Comparison of Atomic Oxygen Degradation in Low Earth Orbit and in a Plasma Etcher

In low Earth orbit (LEO) significant degradation of certain materials occurs from exposure to atomic oxygen (AO). Orbital opportunities to study this degradation for specific materials are limited and expensive. While plasma etchers are commonly used in ground-based studies because of their low cost and convenience, the environment produced in an etcher chamber differs greatly from the LEO environment. Because of the differences in environment, the validity of using etcher data has remained an open question. In this paper, degradation data for 22 materials from the orbital experiment Evaluation of Oxygen Interaction with Materials (EOIM-3) are compared with data from EOIM-3 control specimens exposed in a typical plasma etcher. This comparison indicates that, when carefully considered, plasma etcher results can produce order-of-magnitude estimates of orbital degradation. This allows the etcher to be used to screen unacceptable materials from further, more expensive tests.

Townsend, Jacqueline A.↗
NASA NTRS1979

An investigation of the adhesive bonding of Teflon solar cell covers

The concept of introducing organic agents into silicone resins to stabilize these materials against the ravages of ultraviolet radiation is presented. A screening of coating materials, cover materials and ultraviolet screening agents is described. Fabrication processes were developed for the application of thin 25 micrometer coatings to Teflon. Temperature shock and temperature-humidity tests were conducted.

Rayl, G. J.↗
NASA NTRS1990

Microcracking mechanisms and interface toughening of semi-IPN polyimide matrix composites

A new research program was initiated as a preliminary phase. The following three objectives are being pursued for the overall program: to elucidate the mechanisms of microcracking for graphite fiber-reinforced semi-IPN polyimide matrix composites under mechanical and thermal cyclic loading; to devise material engineering solutions for possible improvement of fatigue damage resistance (or the increase of fatigue endurance strength) of semi-IPN matrix composites by tailoring of modulus and toughness of fiber-resin interface region; and to assess processing characteristics of the composites and their roles in controlling the resistance of composites to microcracking and the effectiveness of interface toughening. The main emphasis was placed upon the initial screening of material systems and optimization of processing conditions for semi-IPN matrix composites with tailored interface. As a first set of control material systems to study, the composites were prepared with unsized Celion 6000 graphite fiber reinforcement and the following resin matrices of varied fracture toughness: PMR-15 thermoset polyimide, semi-IPN of PNR-15 thermoset polyimide and NR150B2 thermoplastic polyimide in 75/25 ratio, and semi-IPN of PMR-15 and NR150B2 in 50/50 ratio. For the composites with the resin matrix of semi-IPN in 75/25 ratio, interface tailoring was attempted by using graphite fibers coated with the resins of systematically varied fracture toughness. In the continuing work, a broad range of interlayer toughness will be achieved by coating the fibers with reactants of semi-IPN having lower or higher content of thermoplastic constituent in comparison with the composition of surrounding resin matrix. In pursuing the objectives of the overall research program, the respective roles and interaction of critical parameters were defined.

Lee, Byung L.↗
NASA NTRS1981

Ultrasonic velocity for estimating density of structural ceramics

The feasibility of using ultrasonic velocity as a measure of bulk density of sintered alpha silicon carbide was investigated. The material studied was either in the as-sintered condition or hot isostatically pressed in the temperature range from 1850 to 2050 C. Densities varied from approximately 2.8 to 3.2 g cu cm. Results show that the bulk, nominal density of structural grade silicon carbide articles can be estimated from ultrasonic velocity measurements to within 1 percent using 20 MHz longitudinal waves and a commercially available ultrasonic time intervalometer. The ultrasonic velocity measurement technique shows promise for screening out material with unacceptably low density levels.

Klima, S. J.↗
DOE OSTI2023

Emerging opportunities for hybrid perovskite solar cells using machine learning

While there are several bottlenecks in hybrid organic–inorganic perovskite (HOIP) solar cell production steps, including composition screening, fabrication, material stability, and device performance, machine learning approaches have begun to tackle each of these issues in recent years. Different algorithms have successfully been adopted to solve the unique problems at each step of HOIP development. Specifically, high-throughput experimentation produces vast amount of training data required to effectively implement machine learning methods. Here, we present an overview of machine learning models, including linear regression, neural networks, deep learning, and statistical forecasting. Experimental examples from the literature, where machine learning is applied to HOIP composition screening, thin film fabrication, thin film characterization, and full device testing, are discussed. These paradigms give insights into the future of HOIP solar cell research. As databases expand and computational power improves, increasingly accurate predictions of the HOIP behavior are becoming possible.

Hering, Abigail R. (ORCID:0000000270806953)↗
DOE OSTI2023

Strain‐Control of Cycloidal Spin Order in a Metallic Van der Waals Magnet

Abstract The manipulation of magnetism through strain control is a captivating area of research with potential applications for low‐power devices that do not require dissipative currents. Recent investigations of insulating multiferroics have unveiled tunable relationships among polar lattice distortions, Dzyaloshinskii–Moriya interactions (DMI), and cycloidal spin orders that break inversion symmetry. These findings have raised the possibility of utilizing strain or strain gradient to manipulate intricate magnetic states by changing polarization. However, the effectiveness of manipulating cycloidal spin orders in “metallic” materials with screened magnetism‐relevant electric polarization remains uncertain. In this study, the reversible strain control of cycloidal spin textures in a metallic van der Waals magnet, Cr 1/3 TaS 2 , through the modulation of polarization and DMI induced by strain is demonstrated. With thermally‐induced biaxial strains and isothermally‐applied uniaxial strains, systematic manipulation of the sign and wavelength of the cycloidal spin textures is realized, respectively. Additionally, unprecedented reflectivity reduction under strain and domain modification at a record‐low current density are also discovered. These findings establish a connection between polarization and cycloidal spins in metallic materials and present a new avenue for utilizing the remarkable tunability of cycloidal magnetic textures and optical functionality in van der Waals metals with strain.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Exploring Approaches for Accelerated Mass Spectrometric Detection of Fluorochemicals from Aqueous Solutions Using Indirect, Adsorbent-Facilitated Desorption Ionization

There is a growing need for rapid, low-cost analytical tools to screen water supplies for persistent contaminants. Due to their ubiquitous presence in the environment and their detrimental effects on human health, there is a public interest in widespread testing for perfluoroalkyl substances (PFAS). However, the most common methods for PFAS analysis can be time-intensive, requiring a preconcentration step followed by liquid chromatography–mass spectrometry (LC–MS), and are cost-prohibitive for most members of the public. To address these challenges, this study explores a novel method for rapid analysis of aqueous analytes by concentrating analytes on solid adsorbents and detecting them using mass spectrometric analysis via desorption ionization directly from the adsorbent surface. We demonstrate this general approach of indirect solution analysis (ISA) with desorption electrospray ionization (ISA-DESI) and laser desorption ionization (ISA-LDI). Various adsorbent materials were screened, including commercial mesoporous carbons, alumina, and metal–organic frameworks (MOFs). Using ISA-DESI, we consistently detect concentrations as low as 5–100 parts per trillion (ppt) for perfluorooctanoic acid (PFOA) and 10–100 ppt for perfluoroundecanoic acid (PFUnDA). This approach enables rapid detection in under 5 min, making it suitable for applications requiring trace detection with fast response times. We further demonstrate the use of ISA-DESI on a range of environmentally relevant contaminants. Advantages of this indirect solution analysis approach include simplified sample preparation, accelerated analysis, and low cost with readily available materials, making it a promising tool to accelerate mass spectrometric PFAS detection for identifying contaminated sites, performing laboratory studies, and monitoring industrial waste streams.

Bays, Nathan Robert [Sandia National Laboratories ↗
DOE OSTI2021

Accelerated Discovery and Design of Ultralow Lattice Thermal Conductivity Materials Using Chemical Bonding Principles

Semiconductors with very low lattice thermal conductivities are highly desired for applications relevant to thermal energy conversion and management, such as thermoelectrics and thermal barrier coatings. Although the crystal structure and chemical bonding are known to play vital roles in shaping heat transfer behavior, material design approaches of lowering lattice thermal conductivity using chemical bonding principles are uncommon. In this work, an effective strategy of weakening interatomic interactions and therefore suppressing lattice thermal conductivity based on chemical bonding principles is presented and a high-efficiency approach of discovering low κ L materials by screening the local coordination environments of crystalline compounds is developed. The resulting first-principles calculations uncover 30 hitherto unexplored compounds with (ultra)low lattice thermal conductivities from 13 prototype crystal structures contained in the Inorganic Crystal Structure Database. Furthermore, an approach of rationally designing high-performance thermoelectrics is demonstrated by additionally incorporating cations with stereochemically active lone-pair electrons. Here these results not only provide atomic-level insights into the physical origin of the low lattice thermal conductivity in a large family of copper/silver-based compounds but also offer an efficient approach to discover and design materials with targeted thermal transport properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Uncovering fast solid-acid proton conductors based on dynamics of polyanion groups and proton bonding strength

Achieving high proton conductivity in inorganic solids is key for advancing many electrochemical technologies, including low-energy nano-electronics and energy-efficient fuel cells and electrolyzers. A quantitative understanding of the physical traits of a material that regulate proton diffusion is necessary for accelerating the discovery of fast proton conductors. In this work, we have mapped the structural, chemical and dynamic properties of solid acids to the elementary steps of the Grotthuss mechanism of proton diffusion. Our approach combines ab initio molecular dynamics simulations, analysis of phonon spectra and atomic structure calculations. We have identified the donor–hydrogen bond lengths and the acidity of polyanion groups as key descriptors of local proton transfer and the vibrational frequencies of the cation framework as the key descriptor of lattice flexibility. The latter facilitates rotations of polyanion groups and long-range proton migration in solid acid proton conductors. The calculated lattice flexibility also correlates with the experimentally reported superprotonic transition temperatures. Using these descriptors, we have screened the Materials Project database and identified potential solid acid proton conductors with monovalent, divalent and trivalent cations, including Ag + , Sr 2+ , Ba 2+ and Er 3+ cations, which go beyond the traditionally considered monovalent alkali cations (Cs + , Rb + , K + , and NH 4 + ) in solid acids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A machine learning approach for determining temperature-dependent bandgap of metal oxides utilizing Allen–Heine–Cardona theory and O’Donnell model parameterization

To evaluate the high temperature sensing properties of metal oxide and perovskite materials suitable for use in combustion environments, it is necessary to understand the temperature dependence of their bandgaps. Although such temperature-driven changes can be calculated via the Allen–Heine–Cardona (AHC) theory, which assesses electron–phonon coupling for the bandgap correction at given temperatures, this approach is computationally demanding. Another approach to predict bandgap temperature-dependence is the O’Donnell model, which uses analytical expressions with multiple fitting parameters that require bandgap information at 0 K. This work employs data-driven Gaussian process regression (GPR) to predict the parameters employed in the O’Donnell model from a set of physical features. We use a sample of 54 metal oxides for which density functional theory has been performed to calculate the bandgap at 0 K, and the AHC calculations have been carried out to determine the shift in the bandgap at non-zero temperatures. As the AHC calculations are impractical for high-throughput screening of materials, the developed GPR model attempts to alleviate this issue by predicting the O'Donnell parameters purely from physical features. To mitigate the reliability issues arising from the very small size of the dataset, we apply a Bayesian technique to improve the generalizability of the data-driven models as well as quantify the uncertainty associated with the predictions. The method captures well the overall trend of the O’Donnell parameters with respect to a reduced feature set obtained by transforming the available physical features. Quantifying the associated uncertainty helps us understand the reliability of the predictions of the O’Donnell parameters and, therefore, the bandgap as a function of temperature for any novel material.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Prediction of O and OH Adsorption on Transition Metal Oxide Surfaces from Bulk Descriptors

In the search for stable and active catalysts, density functional theory and machine learning (ML) based models can accelerate the screening of materials. While stability is conveniently addressed on the bulk level of computation, the modelling of catalytic activity requires expensive surface simulations. Here, in this work, we develop models for the surface adsorption energy of O and OH intermediates across a consistent and extensive dataset of pure transition metal oxide surfaces. We show that adsorption energies across metal oxidation states of +2 to +6 are well captured from the metal-oxygen bond strength extracted from the bulk level calculation. Specifically, we calculate the integrated crystal orbital Hamiltonian population (ICOHP) of the metal-oxygen bond in the bulk oxide and employ a simple normalization scheme to obtain a strong correlation with adsorption energetics. By combining our ICOHP descriptor with non DFT features in a Gaussian Process regression (GPR) model, we achieve high model accuracy with mean absolute errors of 0.166 and 0.219 eV for OH and O adsorption, respectively. By targeting the O-OH adsorption energy difference with our GPR model, we predict the the oxygen evolution reaction (OER) activity from bulk descriptors only. Furthermore, we utilize the strong correlation between the COHP and metal oxygen bond lengths to rapidly predict adsorption energetics and catalytic activity from the optimized bulk geometry. Our approach can enable an efficient search for active catalysts by eliminating the need for surface calculations in the initial screening phase.

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

How to Decarbonize Our Energy Systems: Process‐Informed Design of New Materials for Carbon Capture

Decarbonisation from a variety of industrial and power emission sectors highlights a marked need for capture technologies that can be optimized for different CO 2 sources and integrated into an equally diverse range of applications of captured CO 2 as a feedstock. Some capture technologies are already operated at an industrial scale but may not be optimal for all required applications. Advanced tailored sorbent-based technologies allow flexible operation and reduced costs as they offer higher capture capacities and significantly lower energy penalties than the state-of-the-art systems. To accelerate the discovery, development, and deployment of novel advanced materials, it is critically important that efforts between experimentalists, theoreticians, and process engineers are coordinated. The PrISMa project addresses this challenge by integrating materials design with process design and environmental considerations to allow for tailor-making carbon capture solutions optimally tuned for local sources and sinks. In this article, we highlight some of the recent results obtained with the PrISMa platform.

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

Development of ultralow-background cryogenic calorimeters for the measurement of surface α contamination

Next-generation experiments searching for rare events must satisfy increasingly stringent requirements on the bulk and surface radioactive contamination of their active and structural materials. The measurement of surface contamination is particularly challenging, as no existing technology is capable of separately measuring parts of the 232 Th and 238 U decay chains that are commonly found to be out of secular equilibrium. We will present the results obtained with a detector prototype consisting of 8 silicon wafers of 150mm diameter instrumented as bolometers and operated in a low-background dilution refrigerator at the Gran Sasso Underground Laboratory of INFN, Italy. Furthermore, the prototype was characterized by a baseline energy resolution of few keV and a background <100nBq/cm 2 in the full range of α energies, obtained with simple procedures for cleaning of all employed materials and no specific measures to prevent recontamination. Such performance, together with the modularity of the detector design, demonstrate the possibility to realize an alpha detector capable of separately measuring all alpha emitters of the 232 Th and 238 U chains, possibly reaching a sensitivity of few nBq/cm 2 .

07 ISOTOPE AND RADIATION SOURCES↗