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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Orbit-averaging and deposition accuracy for runaway electron beams in hybrid kinetic-MHD simulations of the runaway plateau

We develop a new procedure that combines the kinetic orbit runaway electron code (KORC) and the NIMROD extended-magnetohydrodynamic code to simulate runaway electrons (REs) in the post-disruption plateau. KORC integrates guiding-center orbits, with a barycentric-based binary search strategy providing initial guesses for the Newton–Raphson logical-to-physical coordinate inversion, ensuring reliable particle-to-mesh mapping in NIMROD, whose fields remain static for the present study. Samples are drawn in accord with experimental parallel current profiles of RE beams during the plateau phase. Deposition in NIMROD is verified through comparison with a Python-based finite-element code that ensures periodicity in the poloidal direction and continuity at the magnetic axis. Accurate representation of near-axis fields requires finer mesh resolution to prevent under- and overshoots in current density from orbit inaccuracies. Yet, at a fixed particle count, increasing mesh resolution amplifies statistical noise in the deposited fields. An orbit-averaging method accumulates partial current deposits over multiple kinetic steps and reduces the statistical noise with little added computational cost. By coupling kinetic routines from KORC directly into the NIMROD codebase, these developments lay essential groundwork for future self-consistent KORC–NIMROD coupling.

Algorithms and data structure↗
DOE OSTI2022

Nonlocal Interactions in Moiré Hubbard Systems

Moiré materials formed in two-dimensional semiconductor heterobilayers are quantum simulators of Hubbard-like physics with unprecedented electron density and interaction strength tunability. Compared to atomic scale Hubbard-like systems, electrons or holes in moiré materials are less strongly attracted to their effective lattice sites because these are defined by finite-depth potential extrema. As a consequence, nonlocal interaction terms like interaction-assisted hopping and intersite exchange are more relevant. Here, we theoretically demonstrate the possibility of tuning the strength of these coupling constants to favor unusual states of matter, including spin liquids, insulating ferromagnets, and superconductors.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The Dynamics of Ions on Phased Radio-frequency Carpets in High Pressure Gases and Application for Barium Tagging in Xenon Gas Time Projection Chambers

Radio-frequency (RF) carpets with ultra-fine pitches are examined for ion transport in gases at atmospheric pressures and above. We develop new analytic and computational methods for modeling RF ion transport at densities where dynamics are strongly influenced by buffer gas collisions. An analytic description of levitating and sweeping forces from phased arrays is obtained, then thermodynamic and kinetic principles are used to calculate ion loss rates in the presence of collisions. This methodology is validated against detailed microscopic SIMION simulations. We then explore a parameter space of special interest for neutrinoless double beta decay experiments: transport of barium ions in xenon at pressures from 1 to 10 bar. Our computations account for molecular ion formation and pressure dependent mobility as well as finite temperature effects. We discuss the challenges associated with achieving suitable operating conditions, which lie beyond the capabilities of existing devices, using presently available or near-future manufacturing techniques.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Characterization of Fe-6Si Soft Magnetic Alloy Produced by Laser-Directed Energy Deposition Additive Manufacturing

Abstract Commercial electrical steels, Fe-Si alloys with < 4 wt.% Si, are inexpensive and efficient materials for electrical power conversion. Further efficiency improvements require increasing the silicon concentration to 6 wt.%, at which point the material becomes brittle and difficult to form by conventional rolling and sheet fabrication methods. Additive manufacturing stands to overcome challenges with commercial manufacturing techniques by leveraging near-net-shape fabrication. The wide array of process conditions provides additive manufacturing with increased flexibility, enabling control over the microstructure and mechanical properties. This work explores the microstructures and magnetic properties of ring-shaped Fe-Si alloys produced using concentric and cross-hatch tool paths on a laser-directed energy deposition additive manufacturing system. Concentric-built samples exhibit elongated grain structures while cross-hatch-built samples comprise lower aspect ratio grain structures. Thermal finite element analysis simulations model the stress conditions produced by the different scan path geometries. Microhardness measurements probe the mechanical properties as a function of anneal temperature, providing a qualitative understanding of the intergranular defect density. Soft magnetic properties measured under quasistatic and AC conditions show frequency- and microstructure-dependent coercivity and permeability. Finally, analysis of the core loss quantifies how the build strategies and thermal treatments influence efficiency in electrical power conversion applications. Understanding the influences of scan path geometry and thermal treatment provides a pathway towards application of additively manufactured soft magnetic materials.

Adamczyk, Jesse M.↗
DOE OSTI2021

Inverse Design of Plasma Metamaterial Devices for Optical Computing

We apply inverse-design methods to produce two-dimensional plasma metamaterial (PMM) devices. Backpropagated finite-difference frequency-domain (FDFD) simulations are used to design waveguides and demultiplexers operating under both TE and TM modes. Demultiplexing and waveguiding are demonstrated for devices composed of plasma elements with reasonable plasma densities of approximately 7 GHz, allowing for future in situ training and experimental realization of these designs. We also explore the possible applicability of PMMs to nonlinear boolean operations for use in optical computing. Functionally complete logical connectives (or and and) are achieved in the TM mode.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Multipole responses in fissioning nuclei and their uncertainties

Electromagnetic multipole responses are key inputs to model the structure, decay, and reactions of atomic nuclei. With the introduction of the finite amplitude method (FAM), large-scale calculations of the nuclear linear response in heavy deformed nuclei have become possible. This work provides a detailed study of multipole responses in actinide nuclei with Skyrme energy density functionals. We quantify both systematic and statistical uncertainties induced by the functional parametrization in FAM calculations. We also extend the FAM formalism to perform blocking calculations with the equal filling approximation for odd-mass and odd-odd nuclei, and analyze the impact of blocking configurations on the response. In conclusion, by examining the entire plutonium isotopic chain from the proton to the neutron drip line, we find a large variability of the response with the neutron number and study how it correlates with the deformation of the nuclear ground state.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Predicting metal–metal interactions. I. The influence of strain on nanoparticle and metal adlayer stabilities

Strain-engineering of bimetallic nanomaterials is an important design strategy for developing new catalysts. In this paper, we introduce an approach for including strain effects into a recently introduced, density functional theory (DFT)-based alloy stability model. The model predicts adsorption site stabilities in nanoparticles and connects these site stabilities with catalytic reactivity and selectivity. Strain-based dependencies will increase the model’s accuracy for nanoparticles affected by finite-size effects. In addition to the stability of small nanoparticles, strain also influences the heat of adsorption of epitaxially grown metal-on-metal adlayers. In this respect, we successfully benchmark the strain-including alloy stability model with previous experimentally determined trends in the heats of adsorption of Au and Cu adlayers on Pt (111). For these systems, our model predicts stronger bimetallic interactions in the first monolayer than monometallic interactions in the second monolayer. We explicitly quantify the interplay between destabilizing strain effects and the energy gained by forming new metal–metal bonds. While tensile strain in the first Cu monolayer significantly destabilizes the adsorption strength, compressive strain in the first Au monolayer has a minimal impact on the heat of adsorption. Hence, this study introduces and, by comparison with previous experiments, validates an efficient DFT-based approach for strain-engineering the stability, and, in turn, the catalytic performance, of active sites in bimetallic alloys with atomic level resolution.

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

Quantum simulation of quantum phase transitions using the convex geometry of reduced density matrices

Transitions of many-particle quantum systems between distinct phases at absolute-zero temperature, known as quantum phase transitions, require an exacting treatment of particle correlations. Here in this work, we present a general quantum-computing approach to quantum phase transitions that exploits the geometric structure of reduced density matrices. While typical approaches to quantum phase transitions examine discontinuities in the order parameters, the origin of phase transitions—their order parameters and symmetry breaking—can be understood geometrically in terms of the set of two-particle reduced density matrices (2-RDMs). The convex set of 2-RDMs provides a comprehensive map of the quantum system including its distinct phases as well as the transitions connecting these phases. Because 2-RDMs can potentially be computed on quantum computers at nonexponential cost, even when the quantum system is strongly correlated, they are ideally suited for a quantum-computing approach to quantum phase transitions. We compute the convex set of 2-RDMs for a Lipkin-Meshkov-Glick spin model on IBM superconducting-qubit quantum processors. Even though computations are limited to few-particle models due to device noise, comparisons with a classically solvable 1000-particle model reveal that the finite-particle quantum solutions capture the key features of the phase transitions including the strong correlation and the symmetry breaking.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Microstructure Generation via Generative Adversarial Network for Heterogeneous, Topologically Complex 3D Materials

Using a large-scale, experimentally captured 3D microstructure dataset, we implement the generative adversarial network (GAN) framework to learn and generate 3D microstructures of solid oxide fuel cell electrodes. The generated microstructures are visually, statistically, and topologically realistic, with distributions of microstructural parameters, including volume fraction, particle size, surface area, tortuosity, and triple phase boundary density, being highly similar to those of the original microstructure. These results are compared and contrasted with those from an established, grain-based generation algorithm (DREAM.3D). Importantly, simulations of electrochemical performance, using a locally resolved finite element model, demonstrate that the GAN generated microstructures closely match the performance distribution of the original, while DREAM.3D leads to significant differences. Finally, the ability of the generative machine learning model to recreate microstructures with high fidelity suggests that the essence of complex microstructures may be captured and represented in a compact and manipulatable form.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A new interatomic potential for mixed Mg-Al-Ga-In spinels

While density functional theory (DFT) has become the de facto approach for accurate simulation of materials at the atomic scale, there are many aspects of materials that are simply out of reach of DFT methods. In particular, finite temperature properties such as diffusivities, the structure and properties of grain boundaries and interfaces, and the study of defect properties in complex alloys are computationally challenging for DFT methods. Recently, a new class of spinels in which three cations order over two sublattices was discovered. In order to predict the properties of these types of structures, classical potentials are a must. Here, in this work, we derive a new classical potential for Mg-bearing spinels in which the B cations are Al, Ga, and/or In. The potential does well in describing the DFT energetics of various spinel structures as a function of chemistry and inversion. In particular, it reproduces the thermodynamically favorable MgAlGaO 4 structure while correctly predicting that neither MgAlInO 4 nor MgGaInO 4 are stable. Further, it reproduces physical trends in elastic properties as compared against experiment.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Dynamic data-driven multiscale modeling for predicting the degradation of a 316L stainless steel nuclear cladding material

Here, we have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Procedures for Assessing the Stability of Proposed Topological Materials

Here, we investigate the stability of MnPb 2 Bi 2 Te 6 (MPBT), which is predicted to be a magnetic topological insulator (TI), using density functional theory calculations. Our analysis includes various measures such as enthalpies of formation, Helmholtz free energies, defect formation energies, and dynamical stability. Our thermodynamic analysis shows that the phonon contribution to the energy gain from finite temperature is estimated to be less than 10 meV/atom, which may not be sufficient to stabilize MPBT at high temperatures, even with the most favorable reactions starting from binaries. While MPBT is generally robust against the formation of various defects, we find that the anti-site defect formation of MnPb is the most likely to occur, with a corresponding energy less than 60 meV. This can be attributed to the significant energy cost from compressive strain at the PbTe layer. Our findings suggest that MPBT is on the brink of stability in terms of thermodynamics and defect formation, underscoring the importance of conducting systematic analyses of the stability of proposed TIs, including MPBT, for their practical utilization. This study offers valuable insights into the design and synthesis of desirable magnetic TI materials with robust stabilities.

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

Observation of polarization density waves in SrTiO 3

The nature of the incipient ferroelectric transition in SrTiO 3 has been a long-standing puzzle in condensed matter physics. One explanation involves the competition between ferroelectricity and an instability characterized by the mesoscopic modulation of the polarization. These polarization density waves, which should intensify near the quantum critical point, break local inversion symmetry and are difficult to characterize with conventional X-ray scattering methods. Here, in this study, we probe inversion symmetry breaking at finite momenta and visualize the instability of the polarization at the nanometre scale in SrTiO3 by combining a femtosecond X-ray free-electron laser with terahertz coherent control methods. We found polar-acoustic collective modes that are soft, particularly at the tens of nanometre scale. These precursor collective excitations provide evidence for the conjectured mesoscopic-modulated phase in SrTiO 3 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Optimized Highly Efficient SSCB Using Organic Substrate Packaging for Electric Vehicle Applications

Solid State Circuit Breakers (SSCBs) are an attractive protection solution for their arcless current interruption and fast actuation speeds over mechanical breakers. This paper proposes a Bidirectional SSCB (BSSCB) with a thermally defined and digitally controlled current time profile for fault protection in EV and other low-voltage DC systems. The paper proposes an organic packaging approach utilizing flex circuitry to develop a reliable, cost-effective power module for BSSCBs. The paper studies transient heat transfer in the power modules using finite element analysis (FEA). An RC themal ladder network is extracted to define a fusing curve. To demonstrate and verify the design, a 1kV/50 A SiC MOSFET BSSCB prototype is fabricated and tested, having a power density of 60 W/cm3 and 4x reduction in form factor over presently researched breakers. Also, given are results for 750 V/150 A operation showing interruption in 2.4 μs.

organic power packaging↗
DOE OSTI2021

Approximating and incorporating model uncertainty in an inversion for seismic source functions: Preliminary results

We present preliminary work on propagating model uncertainty into the estimation of the time domain source time functions of the seismic source. Our method is based on an estimated model covariance function, which we estimate from the data. The model covariance function is then used to construct a suite of surrogate Greens functions which we use in a Monte Carlo type inversion scheme. The result is a probability density function of the six independent source time functions, each of which corresponds to an individual component of the seismic moment tensor. We compare the results of our method with those obtained using a computationally expensive finite difference Monte Carlo method and find that our new method produces results that are deficient in low frequencies. The advantage of our new method, which we term the Karhunen-Loeve Monte Carlo (KLMC) method, is that is several orders of magnitude faster than our current method, which uses a finite difference scheme to produce the suite of forward models.

42 ENGINEERING↗
DOE OSTI2022

Dynamic Data-Driven Multiscale Modeling for Predicting Microstructure and Mechanical Properties of 316L Stainless Steel

We have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Measuring the Speed of Sound Using Cumulants of Baryon Number

Here, we show that the values of the first three cumulants of the baryon number distribution can be used to calculate the isothermal speed of sound and its logarithmic derivative with respect to the baryon-number density. We discuss applications of this result to heavy-ion collision experiments and address possible challenges, including effects due to baryon-number conservation, differences between proton and baryon cumulants, and the influence of finite-number statistics on fluctuation observables in both ex periment and hadronic transport simulations. In particular, we investigate the relation between quantities calculated in infinite, continuous matter, and observables obtained in simulations using a finite number of particles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Finite boundary effects on the spherical Rayleigh–Taylor instability between viscous fluids

For the Rayleigh–Taylor unstable arrangement of a viscous fluid sphere embedded in a finite viscous fluid spherical shell with a rigid boundary and a radially directed acceleration, a dispersion relation is developed from a linear stability analysis using the method of normal modes. [Formula: see text] is the radially directed acceleration at the interface. ρ i denotes the density, μ i is the viscosity, and R i is the radius, where i = 1 is the inner sphere and i = 2 is the outer sphere. The dispersion relation is a function of the following dimensionless variables: viscosity ratio [Formula: see text], density ratio [Formula: see text], spherical harmonic mode n, [Formula: see text], [Formula: see text], and the dimensionless growth rate [Formula: see text], where σ is the exponential growth rate. We show that the boundedness provided by the outer spherical shell has a strong influence on the instability behavior, which is reflected not only in the modulation of the growth rate but also in the selection of the most unstable modes that are physically possible. This outer boundary effect is quantified by the relative magnitude of the radius ratio H. We find that when H is close to unity, lower order harmonics are excluded from becoming the most unstable within a vast region of the parameter space. In other words, the effect of H has precedence over the other controlling parameters d, B, and a wide range of s in establishing what the lowest most unstable mode can be. When H ~ 1, low order harmonics can become the most unstable only for s >> 1. However, in the limit when s → ∞, we show that the most unstable mode is n = 1 and derive the dispersion relation in this limit. The exclusion of most unstable low order harmonics caused by a finite outer boundary is not realized when the outer boundary extends beyond a certain threshold length-scale in which case all modes are equally possible depending on the value of B.

74 ATOMIC AND MOLECULAR PHYSICS↗