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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Effect of plasma treatment on LMPAEK/CF tape and composites manufactured by automated tape placement (ATP)

Automated tape placement (ATP) process is widely used in aerospace for its advanced process control and multi-axis capabilities but faces issues like limited choice of materials and suboptimal tape consolidation. This study investigates air plasma treatment on ATP carbon fiber thermoplastic feedstock tape to address these challenges. The effects on low melt Polyaryletherketone/carbon fiber unidirectional tape (LMPAEK/CF UD tape) were analyzed. Treated and untreated tapes were used to fabricate composites and evaluated for physical, thermal, mechanical, and interfacial properties. Atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared (FTIR) analyses revealed surface roughness changes (on LMPAEK), extent of oxidation, and the presence of hydroxyl/carboxyl groups. Composites from plasma-treated tapes showed a 7.6% increase in tensile strength, 8% in tensile modulus, 18% in flexural strength, and 8.3% in flexural modulus. Further, the interlaminar shear strength improved by 18.7%. Failure analysis showed untreated composites failed via inter-ply and fiber-matrix delamination, while treated composites experienced matrix cracking and fiber breakage. This study highlights atmospheric plasma treatment as a solution to ATP’s limitations, significantly enhancing LMPAEK/CF UD tape composites’ properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Development of an Enhanced Radiation Physics Toolset for Modeling Spectral and Imaging Signatures in the Warm Dense Matter Experiments

Radiative and atomic processes in plasmas play a critical role in a wide variety of high energy density laboratory plasma (HEDLP) experiments. The emission, absorption, and transport of radiation can strongly affect the overall energetics and evolution of such plasmas. In addition, radiation-based diagnostics – including imaging, spectroscopy, and absolute flux measurements – are widely used to determine key features of HEDLPs. To advance our understanding of HEDLP science, it is vital to have high-fidelity computational physics tools that have well-tested radiation physics modeling, and that are readily accessible to researchers in the HEDLP community. Simulations play an extremely important role for planning and designing the experiments, as well as for post-experiment data analysis. Prism Computational Sciences develops software that is used by National Laboratories and universities (including five members of LaserNetUS network). Prominent examples of such research efforts include z-pinch and short-pulse laser experiments designed to study the basic physics of photoionized plasmas and photoionization fronts, as well as their application to astrophysical plasmas. The main effort was dedicated to the development of non-equilibrium equation-of-state (EOS) models within the HELIOS-CR code, a hydrodynamics code with inline collisional-radiative atomic kinetics. Gas cell experiments on Z and Omega demonstrated the importance of non-equilibrium effects on atomic kinetics in photoionized plasmas. Recent proof-of-principle experiments on Omega EP confirmed the advantages of using a short-pulse laser to create an intense radiation drive, leading to additional experiments being proposed. Photoionization front experiments at LLE also emphasizes the importance of radiation and atomic physics. In both studies, HELIOS-CR simulations played a crucial role in computing non-equilibrium opacities and ionization distributions. A newly developed non-LTE EOS model will help addressing possible non-equilibrium effects, on for example specific heat, and their influence in plasma evolution. Prism also implemented support for open-source atomic data generated by the Flexible Atomic Code. This allows researchers to generate custom atomic tables and use them within the complex framework of simulation tools developed by Prism. The ability to use open-source atomic data would be extremely valuable for hydrodynamics and spectroscopic simulations that include high-Z materials, e.g., picosecond x-ray pulse generation experiments. Support for new atomic structures was fully implemented, and the data can be used by all simulation tools developed at Prism: radiation-hydrodynamics, imaging and spectroscopy, EOS and opacity. The development resulted in a significant fidelity enhancement to the simulations tools developed by Prism that are currently used in other cutting-edge experiments including: opacity measurement experiments performed to both understand the basic radiative and atomic properties of plasmas as well as provide data for more accurately modeling the internal structure of the Sun and other stars, high-intensity short-pulse laser experiments performed to develop short-wavelength light sources for use as backlighters and to investigate fast ignition concepts for inertial fusion energy; capsule implosion experiments designed to develop inertial fusion as an energy source, etc.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Ultra-high gamma irradiation of calcium silicate hydrates: Impact on mechanical properties, nanostructure, and atomic environments

The concrete biological shield in a nuclear power plant receives ~100–200 MGy gamma dosage during an 80-year design life. However, precise changes in the mechanical properties and atomic environments of C-S-H at ultrahigh irradiation dosages have not been systematically documented. Here, we report that irradiation decreases C-S-H basal spacing (~ 0.6 ± 0.1 Å for 189 MGy) and increases its Young's modulus, which is attributed to the lower basal spacing as the nano porosity potentially increased and microporosity remained unchanged. Irradiation also decreased the molecular water content and increased hydroxyl groups in C-S-H, showing that interlayer water removal reduces the basal spacing. Finally, 1 H and 29 Si NMR results indicate some disorder in the local proton CaO-H species and slight depolymerization of the silicate structure. Together, these results indicate that the C-S-H gel stiffens upon ultrahigh gamma irradiation dosage, a finding which concerns long-term nuclear power plants operations worldwide.

1H NMR↗
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 OSTI2023

Machine learning predictions of high-Curie-temperature materials

Technologies that function at room temperature often require magnets with a high Curie temperature, $T$ C , and can be improved with better materials. Discovering magnetic materials with a substantial $T$ C is challenging because of the large number of candidates and the cost of fabricating and testing them. Using the two largest known datasets of experimental Curie temperatures, we develop machine-learning models to make rapid $T$ C predictions solely based on the chemical composition of a material. We train a random-forest model and a k -NN one and predict on an initial dataset of over 2500 materials and then validate the model on a new dataset containing over 3000 entries. The accuracy is compared for multiple compounds' representations (“descriptors”) and regression approaches. A random-forest model provides the most accurate predictions and is not improved by dimensionality reduction or by using more complex descriptors based on atomic properties. Further, a random-forest model trained on a combination of both datasets shows that cobalt-rich and iron-rich materials have the highest Curie temperatures for all binary and ternary compounds. An analysis of the model reveals systematic error that causes the model to over-predict low-$T$ C materials and under-predict high-$T$ C materials. For exhaustive searches to find new high-$T$ C materials, analysis of the learning rate suggests either that much more data is needed or that more efficient descriptors are necessary.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Electric-field-induced crossover of polarization reversal mechanisms in Al 1–x Sc x N ferroelectrics

Scandium-doped aluminum nitride, Al 1–x Sc x N, represents a new class of displacive ferroelectric materials with high polarization and sharp hysteresis along with high-temperature resilience, facile synthesizability and compatibility with standard CMOS fabrication techniques. The fundamental physics behind the transformation of unswitchable piezoelectric AlN into switchable Al–Sc–N ferroelectrics depends upon important atomic properties such as local structure, dopant distributions and the presence of competing mechanism of polarization switching in the presence of an applied electric-field that have not been understood. We computationally synthesize Al 1–x Sc x N to quantify the inhomogeneity of Sc distribution and phase segregation, and characterize its crystal and electronic structure as a function of Sc-doping. Nudged elastic band calculations of the potential energy surface and quantum molecular dynamics simulations of direct electric-field-driven ferroelectric switching reveal a crossover between two polarization reversal mechanisms—inhomogeneous nucleation-and-growth mechanism originating near Sc-rich regions in the limit of low applied fields and nucleation-limited-switching in the high-field regime. Finally, understanding polarization reversal pathways for these two mechanisms as well as the role of local Sc concentration on activation barriers provides design rules to identify other combinations of dopant elements, such as Zr, Mg etc. to synthesize superior AlN-based ferroelectric materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Advanced Fabrication Techniques of Metal Hydrides for Science and Technology Applications (Abbreviated Final Report)

Lithium Hydride (LiH) atomic properties make it an excellent candidate for thermal energy storage, hydrogen storage, and nuclear reactor technology. High Energy Density (HED) experiments on LiH at the National Ignition Facility (NIF) can also provide critical Equation of State (EOS) and Hugoniot data. Density requirements for LiH vary per application and therefore physical and structural requirements for LiH are non-uniform. Historical production of LiH relies on casting processesthat are limited by density and grain-size control, which leads to unfavorable machinable characteristics. LiH manufacturing is further hindered due to its chemical reactivity and propensity to readily react with moisture. This work aimed at exploring advanced fabrication techniques for LiH such as 1) uniaxial powder pressing methods and 2) laser powder bed fusion (L-PBF) additive manufacturing. Uniaxial powder compaction offers advantageous tailorable mechanical and physical properties via density control, and L-PBF can produce net-shaped complex parts with unique microstructure. Uniaxial pressing proved successful in readily producing LiH with density control.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Advanced Fabrication Techniques of Metal Hydrides for Science and Technology Applications (Full Technical Report)

Lithium Hydride (LiH) atomic properties make it an excellent candidate for thermal energy storage, hydrogen storage, and nuclear reactor technology. High Energy Density (HED) experiments on LiH at the National Ignition Facility (NIF) can also provide critical Equation of State (EOS) and Hugoniot data. Density requirements for LiH vary per application and therefore physical and structural requirements for LiH are non-uniform. Historical production of LiH relies on casting processes that are limited by density and grain-size control, which leads to unfavorable machinable characteristics. LiH manufacturing is further hindered due to its chemical reactivity and propensity to readily react with moisture. This work aimed at exploring advanced fabrication techniques for LiH such as 1) uniaxial powder pressing methods and 2) laser powder bed fusion (L-PBF) additive manufacturing. Uniaxial powder compaction offers advantageous tailorable mechanical and physical properties via density control, and L-PBF can produce net-shaped complex parts with unique microstructure. Uniaxial pressing proved successful in readily producing LiH with density control.

36 MATERIALS SCIENCE↗
DOE OSTI2020

X-ray Spectroscopic Studies of a Solid-Density Germanium Plasma Created by a Free Electron Laser

The generation of solid-density plasmas in a controlled manner using an X-ray free electron laser (XFEL) has opened up the possibility of diagnosing the atomic properties of hot, strongly coupled systems in novel ways. Previous work has concentrated on K-shell emission spectroscopy of low Z (<= 14) elements. Here, we extend these studies to the mid-Z(=32) element Germanium, where the XFEL creates copious L-shell holes, and the plasma conditions are interrogated by recording of the associated L-shell X-ray emission spectra. Given the desirability of generating as uniform a plasma as possible, we present here a study of the effects of the FEL photon energy on the temperatures and electron densities created, and their uniformity in the FEL beam propagation direction. We show that good uniformity can be achieved by tuning the photon energy of the XFEL such that it does not overlap significantly with L-shell to M-shell bound-bound transitions, and lies below the L-edges of the ions formed during the heating process. Reasonable agreement between experiment and simulations is found for the emitted X-ray spectra, demonstrating that for these higher Z elements, the selection of appropriate XFEL parameters is important for achieving uniformity in the plasma conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Machine-Guided Design of Oxidation-Resistant Superconductors for Quantum Information Applications

Decoherence in superconducting qubits has long been attributed to two-level systems arising from the surfaces and interfaces present in real devices. A recent significant step in reducing decoherence was the replacement of superconducting niobium by superconducting tantalum, resulting in a tripling of transmon qubit lifetimes (T1). The identity, thickness, and quality of the native surface oxide, is thought to play a major role, as tantalum only has one oxide whereas niobium has several. Here we report the development of a thermodynamic metric to rank materials based on their potential to form a well-defined, thin, surface oxide. We first computed this metric for known binary and ternary metal alloys using data available from the Materials Project and experimentally validated the strengths and limits of this metric through the preparation and controlled oxidation of eight known metal alloys. Then we trained a convolutional neural network to predict the value of this metric from atomic composition and atomic properties. This allowed us to compute the metric for materials that are not present in the Materials Project, including a large selection of known superconductors, and, when combined with Tc, allowed us to identify new candidate superconductors for quantum information science and engineering (QISE) applications. We tested the oxidation resistance of a pair of these predictions experimentally. Our results are expected to lay the foundation for the tailored and rapid selection of improved superconductors for QISE.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Alpha Shape Analysis (ASA) Framework for Post- Clustering Property Determination in Atom Probe Tomographic Data

While application of clustering algorithms to atom probe tomography data have enabled quantification of solute clusters in terms of number density, size, and subcomposition there exist other properties (e.g., volume, surface area, and composition) that are better determined by defining an interface between the cluster and the surrounding matrix. The limitation in composition results from an ion selection step where the expected matrix ion types are omitted from the cluster search algorithm to enhance the contrast between the matrix and cluster and to reduce the complexity of the search. Previously, composition determination within solute clusters has utilized a secondary envelopment and erosion step on top of conventional methods such as maximum separation. In this work, we present a novel stochastic method that combines the particle identification fidelity of a conventional clustering algorithm with the analytical flexibility of mesh-based approaches through the generation of alpha shapes for each identified cluster. Furthermore, the corresponding mesh accounts for concave components of the clusters and determines the volume and surface area of the clusters; additionally, the mesh boundary is utilized to update the total composition according to the internal ions.

42 ENGINEERING↗
DOE OSTI2024

Macroscale properties and atomic-scale mechanisms of ash removal in low-temperature hydrothermal carbonization

Biogenic ash is a significant impediment to the utilization of agricultural residues in biofuel production. Such challenge can be addressed by various treatments, as demonstrated in this study on the experimental and computational mechanisms involved in the hydrothermal treatment (HT) of wheat straw. A combination of classical (all-atom) molecular dynamics simulations of cellulose carrying silica and calcium species, along with first principles quantum chemical calculations, indicates the dissociation of inorganics from the cellulose with increased HT temperature. Here, this observation is confirmed by experimental evidence of effective ash removal by HT, showing at least 50% removal of sulfur, chlorine, potassium, and calcium, and 12.5% of silica, leading to a reduced total ash content (from 6.7% to 4.2%).Changes in structural features upon HT, such as surface cellular structure and porosity, were revealed, accompanied by an increased specific surface area (from 1.17 to 6.34 m 2 /g). Our simulations suggest that silica binds tightly to the hydrophobic face of cellulose at room temperature, but HT significantly reduces the binding free energy of association with both hydrophobic and hydrophilic surfaces. Most significantly, ash removal leads to an increased calorific value, rising from approximately 16 MJ/kg to about 19 MJ/kg, along with improved thermal behavior. The improved integration combustion index parameter S indicates that the combustion properties improve with ash removal efficiency. The proposed atomic-level mechanism for the observed removal of inorganics during mild HT underscores the potential of such treatment in producing energy-dense wheat straw, a widely available agricultural residue.

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

Atomic isotropic hyperfine properties for first row elements (B–F) revisited

Benchmark quality isotropic hyperfine properties have been obtained for first row elements (B–F) using a systematic composite approach consisting of a sequence of core/valence correlation consistent basis sets, up through aug-cc-pCV8Z, along with configuration interaction and coupled cluster theory methods. The best nonrelativistic final values (in MHz) are 10.64 (B), 20.22 (C), 10.59 (N), –31.74 (O), and 318.30 (F) and are in very good agreement with available experimental values for these difficult-to-describe properties. Agreement is especially close in the case of N, which has the most accurate experimental value. The spin densities derived from the best composite level of theory were found to closely follow a simple quadratic scaling with the atomic number, Z. Finally, observed convergence rates in the 1-particle and n-particle expansions obtained here may be useful in judging likely accuracy that can be expected in studies of molecular systems.

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

Atomic isotropic hyperfine properties for second row elements (Al–Cl)

Isotropic hyperfine properties have been obtained for the second row elements Al–Cl using a systematic composite approach consisting of a sequence of core/valence correlation consistent basis sets, up through aug-cc-pCV7Z, along with configuration interaction and coupled cluster methods. The best nonrelativistic final values for the atomic ground states (in MHz) are -1.80 27 Al ( 2 P o 1/2 ), -24.31 29 Si ( 3 P 0 ), 63.70 31 P ( 4 So 3/2 ), 20.77 33 S ( 3 P 2 ), and 35.42 35 Cl ( 2 P o 3/2 ). We find a large K shell contribution to the spin density at the nucleus that is almost canceled by the L and M shell contributions. The spin density in atomic units is approximately linear with respect to the atomic number.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Nanoscale Structure and Interfacial Electrochemical Reactivity of Moiré-Engineered Atomic Layers

Here, the electronic properties of atomically thin van der Waals (vdW) materials can be precisely manipulated by vertically stacking them with a controlled offset (for example, a rotational offset─i.e., twist─between the layers, or a small difference in lattice constant) to generate moiré superlattices. In recent years, the application of this “twistronics” concept to interfacial electrochemistry has unveiled unique pathways for tailoring the electrochemical reactivity. Furthermore, this Account provides an overview of our work that leveraged a suite of structural characterization methods, such as interferometric four-dimensional scanning transmission electron microscopy, dark-field transmission electron microscopy, and scanning tunneling microscopy, along with nanoscale electrochemical measurement techniques, namely, scanning electrochemical cell microscopy (SECCM), to uncover and dissect the profound impact of electrode electronic structure, controlled by interlayer twist, on interfacial electron transfer kinetics.

Charge transfer↗