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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 163 records · Page 9

Optimization of Magnesium-Doped Lithium Metal Anode for High Performance Lithium Metal Batteries through Modeling and Experiment

Lithium (Li)-magnesium (Mg) alloy with limited Mg amount, which can also be called Mg-doped Li (Li-Mg), has been considered as a potential alternative anode for high energy density rechargeable Li metal batteries. However, the optimum doping-content of Mg in Li-Mg anode and the mechanism of the improved performance are not well understood. In this study, density functional theory (DFT) calculations are used to investigate the effect of Mg amount in Li-Mg anode. The Li-Mg with about 5 wt. % Mg (abbreviated as Li-Mg5) has the lowest absorption energy of Li, thus all the surface area can be “controlled” by Mg atoms, leading to the smooth and continuous deposition of Li on the surface around the Mg center. A localized high concentration electrolyte enables Li-Mg5 to exhibit the best cycling stability in Li metal batteries with high-loading cathode and lean electrolyte under 4.4 V high-voltage, which is approaching the demand of practical application. This electrolyte also helps generate an inorganic-rich solid electrolyte interphase, which leads to smooth, compact and less corrosion layer on the Li-Mg5 surface. Both theoretical simulations and experimental results prove that Li-Mg5 has optimum Mg content and gives best battery cycling performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of hydrothermal corrosion model and BWR metal coating for CVD SiC in light water reactors

SiC/SiC fiber composites with CVD SiC overcoats are potential candidates for light water reactor advanced accident tolerant cladding materials. Understanding its corrosion kinetics in Light Water Reactor (LWR) conditions is essential to evaluate the concept's viability. Existing models only account for the temperature and oxygen concentration effect on the hydrothermal corrosion behavior applicable to LWR operating conditions. However, the development of a general corrosion rate for CVD SiC that accounts for the impact of irradiated microstructure, flow rate, electrical resistivity, pH, and surface roughness is critical for the practical realization of SiC/SiC-based cladding concepts. After a rigorous experimental campaign, this work updates the existing hydrothermal corrosion model to predict hydrothermal corrosion in LWRs. Numerical radiation and coolant chemistry analysis for LWRs conducted based on the updated corrosion kinetic models suggests that CVD SiC is likely a viable environmental barrier coating for Pressurized Water Reactors while questionable for Boiling Water Reactors (BWR) when the effect of irradiation damage on SiC corrosion is considered. An effective mitigation strategy for the double-layer metal coating is proposed for BWR applications. The double-layer metal coating comprising a FeCrAl overcoat with an intermediate Cr bond coating was observed to provide a stable protective barrier against SiC dissolution in BWR conditions. Finally, the proposed metal coating was also fully adherent following quench and burst tests.

36 MATERIALS SCIENCE↗

Unified constitutive model development for metal matrix composites at high temperature

Structural alloys used in high temperature applications exhibit complex thermomechanical behavior that is time dependent and hereditary. Recent attention is being focused on metal matrix composite materials for high temperature applications where they exhibit all the complexities of conventional alloys and their strong anisotropy adds further complexities. Here, a proven constitutive model for isotropic materials in which the inelastic strain rate and internal state are expressible as gradients of a dissipation potential is taken to depend on invariants that reflect local transverse isotropy. Applications illustrate the capability of the theory of representing the time dependent, hereditary, anisotropic behavior typical of these materials at high temperature.

Robinson, D. N.↗

Secondary metallicity in analytic models of chemical evolution of galaxies

Analytic models of the chemical evolution of galactic regions that grow in mass owing to the continuous infall of matter are characterized, emphasizing the solutions for secondary nuclei (defined as those nuclei whose stellar yields are proportional to the abundance of a primary seed nucleus) in the families of models described by Clayton (1984 and 1985). Wide variations in time dependence of both primary and secondary nuclei as well as in the ratio of secondary to primary are displayed by these model families, confirming again the usefulness of these families as interpretive guides if galaxies do in fact evolve with substantial infall. Additionally, analytic solutions are presented for two other possible interesting systems: the evolution of abundances if the primary metallicity in the infall is increasing in time, and the evolution of abundances if the primary yield changes linearly with time owing to continuous changes in the stellar mass function, the opacity, or other astrophysical agents. Finally, test evaluations of the instantaneous recycling approximation on which these analytic models rely are presented.

Clayton, D. D.↗

Temporally continuous thermofluidic–thermomechanical modeling framework for metal additive manufacturing

Additive manufacturing (AM) is known to generate large magnitudes of residual stresses (RS) within builds due to steep and localized thermal gradients. In the current state of commercial AM technology, manufacturers generally perform heat treatments in effort to reduce the generated RS and its detrimental effects on part distortion and in-service failure. Computational models that effectively simulate the deposition process can provide valuable insights to improve RS distributions. Accordingly, it is common to employ Computational fluid dynamics (CFD) models or finite element (FE) models. While CFD can predict geometric and thermal-fluid behavior, it cannot predict the structural response (e.g., stress–strain) behavior. On the other hand, an FE model can predict mechanical behavior, but it lacks the ability to predict geometric and fluid behavior. Thus, an effectively integrated thermofluidic–thermomechanical modeling framework that exploits the benefits of both techniques while avoiding their respective limitations can offer valuable predictive capability for AM processes. In contrast to previously published efforts, the work herein describes a one-way coupled CFD-FEA framework that abandons major simplifying assumptions, such as geometric steady-state conditions, the absence of material plasticity, and the lack of detailed RS evolution/accumulation during deposition, as well as insufficient validation of results. Here, the presented framework is demonstrated for a directed energy deposition (DED) process, and experiments are performed to validate the predicted geometry and RS profile. Both single- and double-layer stainless steel 316L builds are considered. Geometric data is acquired via 3D optical surface scans and X-ray micro-computed tomography, and residual stress is measured using neutron diffraction (ND). Comparisons between the simulations and measurements reveal that the described CFD-FEA framework is effective in capturing the coupled thermomechanical and thermofluidic behaviors of the DED process. The methodology presented is extensible to other metal AM processes, including power bed fusion and wire-feed-based AM.

42 ENGINEERING↗

Comparing Classical and Machine Learning Force Fields for Modeling Deformation of Metal–Organic Frameworks Relevant for Direct Air Capture

Deformation of metal–organic frameworks (MOFs) induced by adsorbate molecules can affect adsorption properties such as capacity and selectivity, but most computational studies of MOFs assume framework rigidity to simplify calculations. Although flexible force fields (FFs) for MOFs have been parametrized for specific materials, the generality of FFs for reliably modeling adsorbate-induced deformation to accuracy nearing that of density functional theory (DFT) has not been established. This work confirms using DFT calculations that adsorbate-induced deformation can affect CO 2 and H 2 O adsorption energies in a considerable fraction of MOFs promising for direct air capture (DAC). We then benchmark the efficacy of several general-purpose FFs in describing adsorbate-induced deformation for DAC against DFT. Our results show that current classical FFs are insufficient for describing MOF deformation, especially in cases of interest for DAC where strong interactions exist between adsorbed molecules and MOF frameworks. Some emerging machine learning force fields (MLFFs) we tested, particularly CHGNet, MACE-MP-0, and Equiformer V2, appear to be more promising than the classical FF for emulating the deformation behavior described by DFT. The best performing FF (CHGNet), however, fails to achieve the accuracy required for practical predictions with a mean absolute adsorption energy error of 0.124 eV.

adsorption↗

Mechanism and models for zinc metal morphology in alkaline media

Based on experimental observations, a mechanism is presented to explain existence of the different morphologies of electrodeposited zinc in alkaline solution. The high current density dendrites appear to be due to more rapid growth on the nonbasal crystallographic planes than on the basal plane. The low current density moss apparently results from dissolution from the nonbasal planes at low cathodic voltages. Electrochemical models were sought which would produce such a phenomenon. The fundamental plating mechanism alone accounts only for different rates on different planes, not for zinc dissolution from a plane in the cathodic region. Fourteen models were explored; two models were in accord with the proposed mechanism. One involves rapid disproportionation of the zinc +1 species on the nonbasal planes. The other involves a redox reaction (corrosion) between the zinc-zincate and hydrogen-water systems.

May, C. E.↗

Thermal modeling of a metallic thermal protection tile for entry vehicles

The thermal Energy Flow Simulation (TEFS) computer program was developed to simulate transient heat transfer through composite solids and predict interfacial temperatures. The program and its usage are described. A simulation of the thermal response of a new thermal protection tile design for the Space Shuttle Orbiter is presented and graphically compared with actual data. An example is also provided which shows the program's usage as a design tool for theoretical models.

Wiese, M. R.↗

Modeling of the metal–insulator transition temperature in alio-valently doped VO 2 through symbolic regression

The correlated semiconductor vanadium dioxide (VO 2 ) exhibits an insulator–metal transition (IMT) near room temperature, which is of interest in various device applications. Precise IMT temperature control is crucial to determine the use cases across technologies such as thermochromic windows, actuators for robots or neuronal oscillators. Doping the cation or anion sites can modulate the IMT by several tens of degrees and control hysteresis. However, modeling the effects of control parameters (e.g., doping concentration, type of dopants) is challenging due to complex experimental procedures and limited data, hindering the use of traditional data-driven machine learning approaches. Symbolic regression (SR) can bridge this gap by identifying nonlinear expressions connecting key input parameters to target properties, even with small data sets. In this work, we develop SR models to capture the IMT trends in VO 2 influenced by different dopant parameters. Using experimental data from the literature, our study reveals a dual nature of the IMT temperature with varying tungsten (W) doping concentrations. The symbolic model captures data trends and accounts for experimental variability, providing a complementary approach to first-principles calculations. Our feature-driven analysis across a broader class of dopants informs selectivity and provides qualitative insights into tuning phase transition properties valuable for neuromorphic computing and thermochromic windows.

36 MATERIALS SCIENCE↗

Assessing Metal Ion Assignment Accuracy in Protein Data Bank Models via Elemental Spectroscopy

Accurate representation of metal ions in macromolecular structures is critical for chemical interpretation, computational modeling, and machine-learning methods that rely on Protein Data Bank (PDB) entries. However, the elemental identity of metals modeled in crystallographic structures is often inferred indirectly and rarely validated experimentally. Here, we combine Particle Induced X-ray Emission (PIXE) and X-ray Fluorescence Spectroscopy (XRFS) to determine the elemental composition of protein samples used to generate 70 deposited metalloprotein crystal structures. By analyzing the original protein material employed for crystallization, but before the addition of crystallization buffer solutions, we assess whether the modeled metal ions in deposited structures are consistent with experimentally detectable elemental content. We find that in a majority of cases, the metals modeled in the corresponding PDB entries are inconsistent with the metals present in the protein samples before crystallization, or that additional metals are present but not represented in the structural models. Spectroscopic results were integrated with automated crystallographic validation metrics, including real-space Z-difference (RSZD) analysis and systematic rerefinement, to evaluate atomic-number mismatch at metal sites. PIXE and XRFS show strong agreement for dominant elemental signals and provide complementary, scalable approaches for identifying suspect metal assignments. This work does not address physiological or functional metalation but instead highlights a widespread data integrity issue in deposited macromolecular structures, PDB-wide. These results establish an experimentally corroborated link between elemental identity and crystallographic validation metrics, enabling the large-scale detection of chemically inconsistent annotations in structural databases used for computational modeling and machine learning.

Crystallization↗

Assessment of the BISON Metallic Fuel Performance Models

The US Department of Energy is leading a project to design and construct a fast spectrum test reactor called the Versatile Test Reactor (VTR). The BISON nuclear fuel performance code will be used to model VTR driver fuel, including looking at the effects of differences between the VTR driver fuel element design and the legacy fuel designs and experiments on which it is based. Simulations will be conducted to help determine whether the design’s behavior and performance are properly understood and to assess the margins to cladding failure and fuel melting relative to those predicted for past metallic fuel experiments. These predictions are expected to streamline VTR design and operation by helping inform the VTR driver fuel element design and by providing supplemental information for the fuel design safety basis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

An ICME Modeling Framework for Metal Matrix Composites Focusing on Ultrahigh Temperature Matrix Material and Tungsten Carbide Reinforcement Particulate (Final CRADA Report)

Ultra High Temperature Metal Matrix Composites (UHT-MMCs) are of interest to the due to their potential defense and aerospace applications. These materials consist of a metal matrix reinforced with a stiff ceramic or cermet. Based on a preliminary literature survey, this project will focused on a pure titanium (Ti) matrix reinforced with tungsten carbide-cobalt (WC-Co). UHT-MMC technology is still at a nascent stage of development and requires extensive experimental work to optimize the structure and resulting material properties of a particular UHT-MMC material system. An accurate and complete high-performance computing (HPC) model of the Ti/WC-Co material system could greatly accelerate the development and deployment Ti/WC-Co materials by connecting processing parameters to material properties. This type of model could then be used in an integrated computational materials engineering approach to optimize the material structure to achieve a targeted level of performance.

36 MATERIALS SCIENCE↗

Modeling the pseudogap metallic state in cuprates: Quantum disordered pair density wave

We present a way to quantum-disorder a pair density wave and propose it to be a candidate of the effective low-energy description of the pseudogap metal which may reveal itself in a sufficiently high magnetic field that suppresses the d-wave pairing. The ground state we construct is a small-pocket Fermi liquid with a bosonic Mott insulator in the density-wave-enlarged unit cell. At low energy, the charge density is mainly carried by charge 2e bosons, which develop a small insulating gap. As an intermediate step, we discuss the quantum disordering of a fully gapped superconductor and its excitation spectrum. A simplified 1D model, which we solve numerically, is used to illustrate the introduced concepts. Here, we discuss a number of experimental consequences. The interplay between the electron and the small-gap boson results in a step-function background in the electron spectral function which may be consistent with existing angle-resolved photoemission spectroscopy data. Optical excitation across the boson gap can explain the onset and the magnitude of the mid infrared absorption reported long ago.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A grid of model atmospheres for metal-deficient giant stars. I

A grid of flux-constant model atmospheres for stars with effective temperatures between 3750 and 6000 K, log g between 0.75 and 3.0, and (A/H) between -3.0 and 0.0 has been constructed. The line absorption is approximated by opacity distribution functions. Metal lines and molecular lines, including those from the infrared bands of CO and CN, are taken into account. The variation of the structure of the models with metal abundance and microturbulence parameter is found to be quite regular and not very drastic. The surface cooling produced by CO is important for all the models with a maximum temperature of 5000 K, while CN mainly causes a backwarming effect but is not very important for solar CNO abundances. The effects of convection, estimated by using the mixing-length approximation, are important only for the coldest models. The models compare very well with models from overlapping regions of other grids. A solar model consistent with the grid models is found to agree satisfactorily with empirical solar model atmospheres. The careful use of scaled solar models for stars with (A/H) approximately equal to zero is justified.

Gustafsson, B.↗

Aeroelastic response of metallic and composite propfan models in yawed flow

An analytical investigation of aeroelastic response of metallic and composite propfan models in yawed flow was performed. The analytical model is based on the normal modes of a rotating blade and the three dimensional unsteady lifting surface aerodynamic theory including blade mistuning. The calculated blade stresses or strains are compared with published wind tunnel data on two metallic and three composite propfan wind tunnel models. The comparison shows a good agreement between theory and experiment. Additional parametric results indicate that blade response is very sensitive to the blade stiffness and also to blade frequency and mode shape mistuning. From these findings, it is concluded that both frequency and mode shape mistuning should be included in aeroelastic response analysis. Furthermore, both calculated and measured strains show that combined blade frequency and mode shape mistuning has beneficial effects on response due to yawed flow.

Kaza, Krishna Rao V.↗

Aeroelastic response of metallic and composite propfan models in yawed flow

An analytical investigation of aeroelastic response of metallic and composite propfan models in yawed flow was performed. The analytical model is based on the normal modes of a rotating blade and the three-dimensional unsteady lifting surface aerodynamic theory including blade mistuning. The calculated blade stresses or strains are compared with published wind tunnel data on two metallic and three composite propfan wind tunnel models. The comparison shows a good agreement between theory and experiment. Additional parametric results indicate that blade response is very sensitive to the blade stiffness and also to blade frequency and mode shape mistuning. From these findings, it is concluded that both frequency and mode shape mistuning should be included in aeroelastic response analysis. Furthermore, both calculated and measured strains show that combined blade frequency and mode shape mistuning has beneficial effects on response due to yawed flow.

Kaza, Krishna Rao↗

Recent advances in Alkali Metal Thermoelectric Converter (AMTEC) electrode performance and modeling

The Alkali Metal Thermoelectric Converter (AMTEC) is a direct energy conversion device, utilizing a high sodium vapor pressure or activity ratio across a beta-double prime-alumina solid electrolyte (BASE). This paper describes progress on the remaining scientific issue which must be resolved to demonstrate AMTEC feasibility for space power systems: a stable, high power density electrode. Two electrode systems have recently been discovered at JPL that now have the potential to meet space power requirements. One of these is a very thin sputtered molybdenum film, less than 0.5 micron thick, with overlying current collection grids. This electrode has experimentally demonstrated stable performance at 0.4-0.5 W/sq cm for hundreds of hours. Recent modeling results show that at least 0.7 W/sq cm can be achieved. The model of electrode performance now includes all loss mechanisms, including charge transfer resistances at the electrode/electrolyte interface. A second electrode composition, cosputtered platinum/tungsten, has demonstrated 0.8 W/sq cm for 160 hours. Systems studies show that a stable electrode performance of 0.6 W/sq cm will enable high efficiency space power systems.

Bankston, C. P.↗