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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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We demonstrate how optical cavities can be exploited to control both valence- and core-excitations in a prototypical model transition metal complex, ferricyanide ([Fe( iii )(CN) 6 ] 3− ), in an aqueous environment.
A fully microscopic model of the doping-dependent exciton and trion linewidths in the absorption spectra of monolayer transition metal dichalcogenides in the low temperature and low-doping regime is explored. The approach is based on perturbation theory and avoids the use of phenomenological parameters. In the low-doping regime, we find that the trion linewidth is relatively insensitive to doping levels, while the exciton linewidth increases monotonically with doping. On the other hand, we argue that the trion linewidth shows a somewhat stronger temperature dependence. The magnitudes of the linewidths are likely to be masked by phonon scattering for T ≥ 20 K in encapsulated samples in the low-doping regime. We discuss the breakdown of perturbation theory, which should occur at relatively low-doping levels and low temperatures. Our work also paves the way toward understanding a variety of related scattering processes, including impact ionization and Auger scattering in clean 2D samples
This slide presentation reviews Friction Stir Welding (FSW) and the attempts to model the process in order to optimize and improve the process. The studies are ongoing to validate and refine the model of metal flow in the FSW process. There are slides showing the conventional FSW process, a couple of weld tool designs and how the design interacts with the metal flow path. The two basic components of the weld tool are shown, along with geometries of the shoulder design. Modeling of the FSW process is reviewed. Other topics include (1) Microstructure features, (2) Flow Streamlines, (3) Steady-state Nature, and (4) Grain Refinement Mechanisms
Aluminum oxide (Al 2 O 3 ) nanopowder is spin-coated onto both sides of commercial polypropene separator to create artificial solid-electrolyte interphase (SEI) and artificial cathode electrolyte interface (CEI) in potassium metal batteries (KMBs). Here, this significantly enhances the stability, including of KMBs with Prussian Blue (PB) cathodes. For example, symmetric cells are stable after 1,000 cycles at 0.5 mA/cm 2 –0.5 mAh/cm 2 and 3.0 mA/cm 2 –0.5 mAh/cm 2 . Alumina modified separators promote electrolyte wetting and increase ionic conductivity (0.59 vs. 0.2 mS/cm) and transference number (0.81 vs. 0.23). Cryo-stage focused ion beam (cryo-FIB) analysis of cycled modified anode demonstrates dense and planar electrodeposits, versus unmodified baseline consisting of metal filaments (dendrites) interspersed with pores and SEI. Alumina-modified CEI also suppresses elemental Fe crossover and reduces cathode cracking. Mesoscale modeling of metal – SEI interactions captures crucial role of intrinsic heterogeneities, illustrating how artificial SEI affects reaction current distribution, conductivity and morphological stability.
Stochastic lattice-gas models provide the natural framework for analysis of the surface diffusion-mediated evolution of crystalline metal nanostructures on the appropriate time scale (often 10 1 –10 4 s) and length scale. Model behavior can be precisely assessed by kinetic Monte Carlo simulation, typically incorporating a rejection-free algorithm to efficiently handle the broad range of Arrhenius rates for hopping of surface atoms. The model should realistically prescribe these rates, or the associated barriers, for a diversity of local surface environments. However, commonly used generic choices for barriers fail, even qualitatively, to simultaneously describe diffusion for different low-index facets, for terrace vs step edge diffusion, etc. We introduce an alternative Unconventional Interaction–Conventional Interaction formalism to prescribe these barriers, which, even with few parameters, can realistically capture most aspects of behavior. Here, the model is illustrated for single-component fcc metal systems, mainly for the case of Ag. It is quite versatile and can be applied to describe both the post-deposition evolution of 2D nanostructures in homoepitaxial thin films (e.g., reshaping and coalescence of 2D islands) and the post-synthesis evolution of 3D nanocrystals (e.g., reshaping of nanocrystals synthesized with various faceted non-equilibrium shapes back to 3D equilibrium Wulff shapes).
The AC impedance spectra of thin polypyrrole films were obtained at open circuit potentials from -0.4 to 0.4 V vs SCE. Two limiting cases are discussed for which simplified equivalent circuits are applicable. At very positive potentials, the predominantly nonfaradaic AC impedance of polypyrrole is very similar to that observed previously for finite porous metallic films. Modeling of the data with the appropriate equivalent circuit permits effective pore diameter and pore number densities of the oxidized film to be estimated. At potentials from -0.4 to -0.3 V, the polypyrrole film is essentially nonelectronically conductive and diffusion of polymer oxidized sites with their associated counterions can be assumed to be linear from the film/substrate electrode interface. The equivalent circuit for the polypyrrole film at these potentials is that previously described for metal oxide, lithium intercalation thin films. Using this model, counterion diffusion coefficients are determined for both semi-infinite and finite diffusion domains. In addition, the limiting low frequency resistance and capacitance of the polypyrrole thin fims was determined and compared to that obtained previously for thicker films of the polymer. The origin of the observed potential dependence of these low frequency circuit components is discussed.
A new solution to the observed Galactic globular cluster metallicity distribution is proposed by considering inhomogeneous collapse of a centrally condensed proto-Galaxy. In contrast to the standard one-zone model, it is shown that, for inhomogeneous models, the metallicity distribution can be reproduced without the need to decrease the nucleosynthetic yield for metal-poor stars. Chemical evolution in free fall is calculated analytically. A hybrid hydroparticle code is developed to study the effect of supernova induced pressure.
Ultraviolet spectra of four O stars in the Magellanic Clouds obtained with the faint object spectrograph of the Hubble Space Telescope are analyzed with respect to their metallicity. The metal abundances are derived from the stellar parameters and the mass loss rate with a two step procedure: hydrodynamic radiation-driven wind models with metallicity as a free parameter are constructed to fit the observed wind momentum rate and thus yield a dynamical metallicity, and synthetic spectra are computed for different metal abundances and compared to the observed spectra in order to obtain a spectroscopic metallicity.
The general theory of internal state variables are reviewed to apply it to inelastic metals in use in high temperature environments. In this process, certain constraints and clarifications will be made regarding internal state variables. It is shown that the Helmholtz free energy can be utilized to construct constitutive equations which are appropriate for metallic superalloys. Internal state variables are shown to represent locally averaged measures of dislocation arrangement, dislocation density, and intergranular fracture. The internal state variable model is demonstrated to be a suitable framework for comparison of several currently proposed models for metals and can therefore be used to exhibit history dependence, nonlinearity, and rate as well as temperature sensitivity.
We present the results of spectroscopic analyses of hot horizontal branch (HB) stars in M13 and M3, which form a famous second parameter pair. From the spectra we derived - for the first time in M13 - atmospheric parameters (effective temperature and surface gravity) as well as abundances of helium, magnesium, and iron. Consistent with analyses of hot HB stars in other globular clusters we find evidence for helium depletion and iron enrichment in stars hotter than about 12,000 K in both M3 and M13. Accounting for the iron enrichment substantially improves the agreement with canonical evolutionary models, although the derived gravities and masses are still somewhat too low. This remaining discrepancy may be an indication that scaled-solar metal-rich model atmospheres do not adequately represent the highly non-solar abundance ratios found in blue HB stars with radiative levitation. We discuss the effects of an enhancement in the envelope helium abundance on the atmospheric parameters of the blue HB stars, as might be caused by deep mixing on the red giant branch or primordial pollution from an earlier generation of intermediate mass asymptotic giant branch stars.
We present the results of spectroscopic analyses of hot horizontal branch (HB) stars in M 13 and M 3, which form a famous "second parameter" pair. F rom the spectra and Stromgren photometry we derived - for the first time in M 13 - atmospheric parameters (effective temperature and surface gravity). For stars with Stromgren temperatures between 10,000 and 12,000 K we found excellent agreement between the atmospheric parameters derived from Stromgren photometry and those derived from Balmer line profile fits. However, for cooler stars there is a disagreement in the parameters derived by the two methods, for which we have no satisfactory explanation. Stars hotter than 12,000 K show evidence for helium depletion and iron enrichment, both in M 3 and M 13. Accounting for the iron enrichment substantially improves the agreement with canonical evolutionary models, although the derived gravities and masses are still somewhat too low. This remaining discrepancy may be an indication that scaled-solar metal-rich model atmospheres do not adequately represent the highly non-solar abundance ratios found in blue HB stars affected by diffusion. We discuss the effects of an enhancement in the envelope helium abundance on the atmospheric parameters of the blue HB stars, as might be caused by deep mixing on the red giant branch or primordial pollution from an earlier generation of intermediate mass asymptotic giant branch stars. Key words. Stars: atmospheres - Stars: evolution - Stars: horizontal branch - Globular clusters: individual: M 3 - Globular clusters: individual: M 13
The simulation and modeling of part-level distortion and residual stress in diverse metal additive manufacturing (AM) geometries has great potential to enable the rapid adoption of this technology in engineering design. Moreover, the use of additive manufacturing component libraries (CLs) offer a computationally efficient means of quantifying these part-level defects resultant from AM processing. We report on how the individual simulations of simple shapes, potential entries in a CL, can be superimposed to provide an indication of distortion and residual stresses in complex geometries. Laser powder bed fusion AM was used to construct test geometries of varied shapes and their combinations in the form of CLs in an effort to characterize location-dependent and feature-dependent distortion distributions. Blue light scanning was used to experimentally measure 3D distortions in order to investigate the interaction between the component shapes and local boundary conditions. Overall, part-level distortions were highly dependent on test component geometry, local boundary conditions, and shape combination. Commercial finite element software was used to verify experimental trends and to make predictions of distortion. The use of CLs resulted in over 20 times savings in computational cost while reproducing overall trends in distortion for test geometry assemblies. Therefore, it is anticipated that the use of CLs for L-PBF AM geometries has demonstrated potential to facilitate efficient simulations of full component AM assemblies, thereby reducing the need for costly trial-and-error-type experimental analysis.
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Material Testing 2.0 (MT2.0) is a paradigm that advocates for the use of rich, full-field data, such as from digital image correlation and infrared thermography, for material identification. By employing heterogeneous, multi-axial data in conjunction with sophisticated inverse calibration techniques such as finite element model updating and the virtual fields method, MT2.0 aims to reduce the number of specimens needed for material identification and to increase confidence in the calibration results. To support continued development, improvement, and validation of such inverse methods—specifically for rate-dependent, temperature-dependent, and anisotropic metal plasticity models—we provide here a thorough experimental data set for 304L stainless steel sheet metal. The data set includes full-field displacement, strain, and temperature data for seven unique specimen geometries tested at different strain rates and in different material orientations. Commensurate extensometer strain data from tensile dog bones is provided as well for comparison. We believe this complete data set will be a valuable contribution to the experimental and computational mechanics communities, supporting continued advances in material identification methods.
Aircraft engine components invariably are subjected to mean stresses over and above the cyclic loads. In monolithic materials, it has been observed that tensile mean stresses are detrimental and compressive mean stresses are beneficial to fatigue life in comparison to a base of zero mean stress. Several mean stress models exist for monolithic metals, but each differ quantitatively in the extent to which detrimental or beneficial effects are ascribed. There have been limited attempts to apply these models to metal matrix composites. At the NASA Lewis Research Center, several mean stress models--the Smith-Watson- Topper, Walker, Normalized Goodman, and Soderberg models--were examined for applicability to this class of composite materials. The Soderberg approach, which normalizes the mean stress to a 0.02-percent yield strength, was shown to best represent the effect of mean stresses over the range covered. The other models varied significantly in their predictability and often failed to predict the composite behavior at very high tensile mean stresses. This work is the first to systematically demonstrate the influence of mean stresses on metal matrix composites and model their effects. Attention also was given to fatigue-cracking mechanisms in the Ti-15-3 matrix and to micromechanics analyses of mean stress effects.
Understanding the role of microstructural heterogeneities on the shock wave propagation and defect evolution behavior is essential to predicting the dynamic response of metals. Heterogeneities, such as voids, provide challenges to understanding the wave propagation behavior as the shock-void interaction can collapse the void and result in large plastic strains and significant heating (hot spot formation) in the metal. Accurate modeling of this phenomenon requires predicting the void collapse mechanisms and the related heat generation and dissipation mechanisms (hotspot formation) that determine the microstructure evolution. While molecular dynamics (MD) simulations can model the void collapse behavior, the time/length scale capabilities pose a challenge to connect with continuum models or the experimental scales. Here, this study presents the capability of the newly developed quasi-coarse-grained dynamics (QCGD) method that extends the MD simulations to larger system sizes and longer times to model this phenomenon. This study uses QCGD simulations to investigate the mechanisms of shock wave interactions with pre-existing voids in single-crystal Ta microstructures for variations in shock pressures, void size, and loading orientations. For a given orientation, the plasticity contributions and rates of void collapse are observed to vary with shock pressures and void size. The larger void sizes and higher pressures result in increased temperatures (hot spots) and faster void collapse rates and unravel the variations in the plasticity contributions. In addition, QCGD simulations investigate the post-collapse microstructure evolution as a release wave travels through the hot spot region. The simulations reveal that the reduction in temperatures due to heat dissipation initiates the dynamic recrystallization behavior in the hotspot regions.
We review recent advances in machine-learning (ML) force-field methods for Landau–Lifshitz–Gilbert simulations of itinerant electron magnets, focusing on their scalability and transferability. Built on the principle of locality, a deep neural-network model is developed to efficiently and accurately predict electron-mediated forces governing spin dynamics. Symmetry-aware descriptors constructed through a group-theoretical approach ensure rigorous incorporation of both lattice and spin-rotation symmetries. The framework is demonstrated using the prototypical s-d exchange model widely employed in spintronics. ML-enabled large-scale simulations reveal novel nonequilibrium phenomena, including anomalous coarsening of tetrahedral spin order on the triangular lattice and the freezing of phase-separation dynamics in lightly hole-doped, strong-coupling square-lattice systems. These results establish ML force-field frameworks as scalable, accurate, and versatile tools for modeling nonequilibrium spin dynamics in itinerant magnets.