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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Corrosion behavior of a series of combinatorial physical vapor deposition coatings on SiC in a simulated boiling water reactor environment

Here, the simulated boiling water condition corrosion properties of multilayer and combinatorial physical vapor deposition metal coatings (Zr, Cr, and/or Ti) deposited on a SiC f -SiC composite were investigated. Various compositions within the ternary system were corroded to the most suitable composition preventing underlying SiC f -SiC from further attack. Mass measurements and visual observations were conducted to identify which coatings formed protective oxides and which coatings spalled. Transmission electron microscopy was conducted to observe the microstructure of the physical vapor deposition metal layer before and after corrosion as well as identify the oxide which were forming.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Toward an event-level analysis of hadron structure using differential programming

Reconstructing the internal properties of hadrons in terms of fundamental quark and gluon de- grees of freedom is a central goal in nuclear and particle physics. This effort lies at the core of major experimental programs, such as the Jefferson Lab 12 GeV program and the upcoming Electron-Ion Collider. A primary challenge is the inherent inverse problem: converting large-scale observational data from collision events into the fundamental QCD-defined densities that characterize the micro- scopic structure of hadronic systems. Recent advances in AI and machine learning have opened new avenues for addressing this challenge using deep learning techniques. A particularly promising direction is the integration of complex theoretical calculations and experimental simulations into a unified framework capable of reconstructing these densities directly from event-level information. In this document, we introduce a key algorithm called LOITS, which enables differentiable program- ming within such a framework, facilitating the use of AI/ML techniques to solve the inverse problem of QCF reconstruction at the event level.

Braga, Kevin [College of William and Mary, William↗
DOE OSTI2023

13 C Radiofrequency Amplification by Stimulated Emission of Radiation Threshold Sensing of Chemical Reactions

Conventional nuclear magnetic resonance (NMR) enables detection of chemicals and their transformations by exciting nuclear spin ensembles with a radio-frequency pulse followed by detection of the precessing spins at their characteristic frequencies. The detected frequencies report on chemical reactions in real time and the signal amplitudes scale with concentrations of products and reactants. Here, we employ Radiofrequency Amplification by Stimulated Emission of Radiation (RASER), a quantum phenomenon producing coherent emission of 13 C signals, to detect chemical transformations. The 13 C signals are emitted by the negatively hyperpolarized biomolecules without external radio frequency pulses and without any background signal from other, nonhyperpolarized spins in the ensemble. Here, we studied the hydrolysis of hyperpolarized ethyl-[1- 13 C]acetate to hyperpolarized [1- 13 C]acetate, which was analyzed as a model system by conventional NMR and 13 C RASER. The chemical transformation of 13 C RASER-active species leads to complete and abrupt disappearance of reactant signals and delayed, abrupt reappearance of a frequency-shifted RASER signal without destroying 13 C polarization. Further, the experimentally observed “quantum” RASER threshold is supported by simulations.

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

Nonlinear multi-magnon scattering in artificial spin ice

Abstract Magnons, the quantum-mechanical fundamental excitations of magnetic solids, are bosons whose number does not need to be conserved in scattering processes. Microwave-induced parametric magnon processes, often called Suhl instabilities, have been believed to occur in magnetic thin films only, where quasi-continuous magnon bands exist. Here, we reveal the existence of such nonlinear magnon-magnon scattering processes and their coherence in ensembles of magnetic nanostructures known as artificial spin ice. We find that these systems exhibit effective scattering processes akin to those observed in continuous magnetic thin films. We utilize a combined microwave and microfocused Brillouin light scattering measurement approach to investigate the evolution of their modes. Scattering events occur between resonance frequencies that are determined by each nanomagnet’s mode volume and profile. Comparison with numerical simulations reveals that frequency doubling is enabled by exciting a subset of nanomagnets that, in turn, act as nanosized antennas, an effect that is akin to scattering in continuous films. Moreover, our results suggest that tunable directional scattering is possible in these structures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Accelerated kinetic model for global macro stability studies of high-beta fusion reactors

The field reversed configuration (FRC), such as studied in the C-2W experiment at TAE Technologies, is an attractive candidate for realizing a nuclear fusion reactor. In an FRC, kinetic ion effects play the majority role in macroscopic stability, which allows global stability studies to make use of fluid-kinetic hybrid (also referred to as Ohm's law) models wherein ions are treated kinetically while electrons are treated as a fluid. The development and validation of such a hybrid particle-in-cell algorithm in the Exascale Computing Project code WarpX are reported here. Implementation of this model in the WarpX framework benefits from the numerical efficiency of WarpX as well as its scalability on large HPC systems and portability to different architectures. Performance benchmarks of the new algorithm for large, 3-dimensional, full device simulations from the Perlmutter supercomputer are presented. Results of a series of FRC simulations are discussed in which the impact of two-fluid effects on the tilt-mode growth rate was studied. It was observed that, in agreement with previous Hall-MHD studies, two-fluid effects have a stabilizing impact on the tilt mode.

Physics↗
DOE OSTI2024

Nonlinear inductive response of pinned superconducting vortices in artificial pinning sites

Using the time dependent Ginzburg-Landau equations, we simulate the inductive responses of a variety of thin-film systems containing patterned antidots with different sizes and shapes. The results for all shapes show that the kinetic inductance diverges as the applied current approaches a critical current that is below the BCS depairing current. In conclusion, exploiting the similarity of the observed current-voltage behavior to that of Josephson junctions, we obtain an empirical equation that well fits the inductivity curve as a function of the applied current.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Bipartite mutual information in classical many-body dynamics

Information theoretic measures have helped to sharpen our understanding of many-body quantum states. As perhaps the most well-known example, the entanglement entropy (or more generally, the bipartite mutual information) has become a powerful tool for characterizing the dynamical growth of quantum correlations. By contrast, although computable, the bipartite mutual information (MI) is almost never explored in classical many particle systems; this owes in part to the fact that computing the MI requires keeping track of the evolution of the full probability distribution, a feat which is rarely done (or thought to be needed) in classical many-body simulations. Here, we utilize the MI to analyze the spreading of information in 1D elementary cellular automata (CA). Broadly speaking, we find that the behavior of the MI in these dynamical systems exhibits a few different types of scaling that roughly correspond to known CA universality classes. Of particular note is that we observe a set of automata for which the MI converges parametrically slowly to its thermodynamic value. We develop a microscopic understanding of this behavior by analyzing a two-species model of annihilating particles moving in opposite directions. Furthermore, our work suggests the possibility that information theoretic tools such as the MI might enable a more fine-grained characterization of classical many-body states and dynamics.

Cellular automata↗
DOE OSTI2022

Atom-Specific Probing of Electron Dynamics in an Atomic Adsorbate by Time-Resolved X-Ray Spectroscopy

The electronic excitation occurring on adsorbates at ultrafast timescales from optical lasers that initiate surface chemical reactions is still an open question. Here, in this work, we report the ultrafast temporal evolution of x-ray absorption spectroscopy (XAS) and x-ray emission spectroscopy (XES) of a simple well-known adsorbate prototype system, namely carbon (C) atoms adsorbed on a nickel [Ni(100)] surface, following intense laser optical pumping at 400 nm. We observe ultrafast (~100 fs) changes in both XAS and XES showing clear signatures of the formation of a hot electron-hole pair distribution on the adsorbate. This is followed by slower changes on a few picoseconds timescale, shown to be consistent with thermalization of the complete C/Ni system. Density functional theory spectrum simulations support this interpretation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Study of light nuclei by polarization observables in electron scattering

Electron-induced proton, neutron and deuteron knock-out remains the most versatile probe of the electro-magnetic properties and spin structure of light nuclei. The advent of highly polarized beams and targets and improvements in recoil polarization methods, as well as analysis and simulation techniques, have enabled us to study the static and dynamical properties of few-body systems with unprecedented precision. Recent experiments at Jefferson Lab and MAMI are presented and put into perspective of state-of-the art Faddeev calculations, with focus on the ^\mathbf{3}\mathbf{He} 3 𝐇 𝐞 nucleus.

Sirca, Simon↗
DOE OSTI2022

Hybrid Solid Oxide Fuel Cell/Gas Turbine Model Development for Electric Aviation

A thermodynamic model was developed and validated to analyze a high-performance solid oxide fuel cell and gas turbine (SOFC-GT) hybrid power system for electric aviation. This study used a process simulation software package (ProMax) to study the role of SOFC design and operation on the feasibility and performance of the hybrid system. Standard modules, including compressor, turbine, heat exchanger, reforming reactor, and combustor were used from the ProMax tool suite while a custom module was created to simulate the SOFC stack. The model used an SOFC test data set as an input. Additional SOFC stack performance effects, such as pressure, temperature, and utilization of air and fuel, were added from open source data. System performance predictors were SOFC specific power, fuel-to-electricity conversion efficiency, and hybrid system efficiency. Using these input data and predictors, a static thermodynamic performance model was created that can be modified for different system configurations and operating conditions. Prior to creating the final aircraft performance model, initial demonstration models were developed to validate output results. We used the NASA SOFC model as a benchmark, which was created with their Numerical Propulsion System Simulator (NPSS) software framework. Our output results matched within 1% of both the NASA model and open source SOFC performance data. With confidence gained in the accuracy of this model, a 1-MW SOFC-GT hybrid power system was constructed for an aircraft propulsion concept. Overall hybrid system efficiencies of > 75% FTE were observed during standard 36,000 feet cruise flight conditions.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Hector V3.2.0: functionality and performance of a reduced-complexity climate model

Abstract. Hector is an open-source reduced-complexity climate–carbon cycle model that models critical Earth system processes on a global and annual basis. Here, we present an updated version of the model, Hector V3.2.0 (hereafter Hector V3), and document its new features, implementation of new science, and performance. Significant new features include permafrost thaw, a reworked energy balance submodel, and updated parameterizations throughout. Hector V3 results are in good general agreement with historical observations of atmospheric CO2 concentrations and global mean surface temperature, and the future temperature projections from Hector V3 are consistent with more complex Earth system model output data from the sixth phase of the Coupled Model Intercomparison Project. We show that Hector V3 is a flexible, performant, robust, and fully open-source simulator of global climate changes. We also note its limitations and discuss future areas for improvement and research with respect to the model's scientific, stakeholder, and educational priorities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Scientific machine learning for modeling and simulating complex fluids

The formulation of rheological constitutive equations—models that relate internal stresses and deformations in complex fluids—is a critical step in the engineering of systems involving soft materials. While data-driven models provide accessible alternatives to expensive first-principles models and less accurate empirical models in many engineering disciplines, the development of similar models for complex fluids has lagged. The diversity of techniques for characterizing non-Newtonian fluid dynamics creates a challenge for classical machine learning approaches, which require uniformly structured training data. Consequently, early machine-learning based constitutive equations have not been portable between different deformation protocols or mechanical observables. Here, we present a data-driven framework that resolves such issues, allowing rheologists to construct learnable models that incorporate essential physical information, while remaining agnostic to details regarding particular experimental protocols or flow kinematics. These scientific machine learning models incorporate a universal approximator within a materially objective tensorial constitutive framework. By construction, these models respect physical constraints, such as frame-invariance and tensor symmetry, required by continuum mechanics. We demonstrate that this framework facilitates the rapid discovery of accurate constitutive equations from limited data and that the learned models may be used to describe more kinematically complex flows. This inherent flexibility admits the application of these “digital fluid twins” to a range of material systems and engineering problems. We illustrate this flexibility by deploying a trained model within a multidimensional computational fluid dynamics simulation—a task that is not achievable using any previously developed data-driven rheological equation of state.

Science & Technology - Other Topics↗
DOE OSTI2025

Electrochemical Characterization of Dissolved Oxides in Molten FLiNaK

Molten fluoride salts have long been the subject of investigation given their application in a variety of industrial processes. Oxides are a common exogeneous impurity within these systems, and can lead to many operational and regulatory concerns. In recent studies, the electro-oxidation of dissolved metallic oxides has been attributed to a single step oxygen evolution reaction despite voltametric evidence suggesting otherwise. Here, we first use square wave voltammetry to confirm that the oxidation of dissolved oxides in fluorides proceeds via a two-electron transfer reaction and then demonstrate that the presence of a peroxide-mediated redox reaction better explains the electrochemical data. Numerical simulations were then used to support the determination of improved diffusion coefficients to enable electroanalytical measurements of the oxide concentration across at a variety of temperatures. A linear Arrhenius relationship was observed when the experimental data was corrected for ohmic resistance effects. Concentration measurements using the corrected square wave voltammetry data demonstrated high accuracy across a large range of concentrations, while the uncorrected data showed plateauing and high errors. In total, this work serves to rectify previously misconstrued electrochemical data of oxides in molten salts and demonstrate how accurate, in situ concentration measurements can be achieved in real-world systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Machine Learning Driven Sensitivity Analysis of E3SM Land Model Parameters for Wetland Methane Emissions

Methane (CH 4 ) is globally the second most critical greenhouse gas after carbon dioxide, contributing to 16%–25% of the observed atmospheric warming. Wetlands are the primary natural source of methane emissions globally. However, wetland methane emission estimates from biogeochemistry models contain considerable uncertainty. One of the main sources of this uncertainty arises from the numerous uncertain model parameters within various physical, biological, and chemical processes that influence methane production, oxidation, and transport. Sensitivity Analysis (SA) can help identify critical parameters for methane emission and achieve reduced biases and uncertainties in future projections. This study performs SA for 19 selected parameters responsible for critical biogeochemical processes in the methane module of the Energy Exascale Earth System Model (E3SM) land model (ELM). The impact of these parameters on various CH 4 fluxes is examined at 14 FLUXNET- CH 4 sites with diverse vegetation types. Given the extensive number of model simulations needed for global variance-based SA, we employ a machine learning (ML) algorithm to emulate the complex behavior of ELM methane biogeochemistry. We found that parameters linked to CH 4 production and diffusion generally present the highest sensitivities despite apparent seasonal variation. Comparing simulated emissions from perturbed parameter sets against FLUXNET-CH 4 observations revealed that better performances can be achieved at each site compared to the default parameter values. This presents a scope for further improving simulated emissions using parameter calibration with advanced optimization techniques.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Sensitivity of Precipitation Displacement of a Simulated MCS to Changes in Land Surface Conditions

Abstract This study investigates the role of the land surface on the precipitation produced by an elevated mesoscale convective system (MCS) in Iowa between 24–25 June 2015 during the Plains Elevated Convection at Night (PECAN) field campaign. Previous studies have shown a strong effect of low‐level atmospheric moisture on the location of this MCS. A series of semi‐idealized and realistic simulations with irrigation are conducted to understand the effect of moisture perturbations on the MCS precipitation displacement. In general, numerical simulations place the MCS east of the observed location. Adding moisture directly in the low‐level atmosphere in the semi‐idealized experiments reduces this displacement error. However, experiments with perturbed soil moisture result in drying over Iowa induced by moisture flux divergence from cooler low‐level temperatures and higher surface pressure, causing the MCS to move further to the east. The irrigation impact on low‐level moisture is highly dependent on the length of simulation period. Shorter simulations on the order of days generate similar drying over Iowa but the opposite is found for month‐long simulations. Despite the lack of low‐level moistening in the perturbed soil moisture and short‐term irrigation experiments, the sensitivity to low‐level moisture is similar in all runs. More low‐level moisture generates a more convectively unstable environment with less inhibition and a lower level of free convection that leads to more rapid MCS development and a change in MCS location.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Combined molecular and spin dynamics simulation of BCC iron with vacancy defects

Utilizing an atomistic computational model, which handles both translational and spin degrees of freedom, combined molecular and spin dynamics simulations have been performed to investigate the effect of vacancy defects on spin wave excitations in ferromagnetic iron. Fourier transforms of space- and time-displaced correlation functions yield the dynamic structure factor, providing characteristic frequencies and lifetimes of the spin wave modes. A comparison of the system with a 5% vacancy concentration with pure lattice data shows a decrease in frequency and a decrease in lifetime for all transverse spin wave excitations observed. In addition, the clearly defined transverse spin wave excitations are distorted with the introduction of vacancy defects, and we observe reduced excitation lifetimes due to increased magnon–magnon scattering. We observe further evidence of increased magnon–magnon scattering, as the peaks in the longitudinal spin wave spectrum become less distinct. Finally, similar impacts are observed in the vibrational subsystem, with a decrease in characteristic phonon frequency and flattening of lattice excitation signals due to vacancy defects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Dynamical Downscaling of Earth System Model Data for Energy System Analysis

Assessing energy resources (e.g., solar, wind, and hydro) under future scenarios requires datasets with sufficient spatial and temporal detail to capture variability and extreme events. While global-scale Earth System Model (ESM) projections are widely used, their coarse resolution limits direct application to regional energy system analyses. Dynamical downscaling offers a robust approach to generate physically consistent, fine-scale datasets that better represent local atmospheric processes impacting energy resources. In this work, we present a two-stage approach for producing high-resolution historical and future projections over the contiguous United States (CONUS). First, we optimize the Weather Research and Forecasting (WRF) model configuration for energy-relevant variables - solar irradiance, wind speed, and precipitation - by conducting ERA5-driven simulations at 8-km and 28-km resolution. Multiple physics schemes and model configurations within the WRF are evaluated against observational datasets including the National Solar Radiation Database (NSRDB), the Parameter-elevation Regressions on Independent Slopes Model (PRISM), and the Stage IV multi-radar/multi-sensor precipitation product for the CONUS domain. Using the best-performing configuration, we dynamically downscale MPI-ESM1-2-HR simulations for 2000-2060 under SSP2-4.5 and SSP5-8.5 scenarios at 4-km spatial and hourly temporal resolution. This presentation will provide a comprehensive analysis of the results from multiple numerical experiments and high-resolution ESM projections. In addition, we will discuss potential applications of our high-resolution datasets within the energy sector and outline future research avenues dedicated to evaluating how extreme weather events influence system performance and resilience.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Climate, Variability, and Climate Sensitivity of “Middle Atmosphere” Chemistry Configurations of the Community Earth System Model Version 2, Whole Atmosphere Community Climate Model Version 6 (CESM2(WACCM6))

Abstract Simulating whole atmosphere dynamics, chemistry, and physics is computationally expensive. It can require high vertical resolution throughout the middle and upper atmosphere, as well as a comprehensive chemistry and aerosol scheme coupled to radiation physics. An unintentional outcome of the development of one of the most sophisticated and hence computationally expensive model configurations is that it often excludes a broad community of users with limited computational resources. Here, we analyze two configurations of the Community Earth System Model Version 2, Whole Atmosphere Community Climate Model Version 6 (CESM2(WACCM6)) with simplified “middle atmosphere” chemistry at nominal 1 and 2° horizontal resolutions. Using observations, a reanalysis, and direct model comparisons, we find that these configurations generally reproduce the climate, variability, and climate sensitivity of the 1° nominal horizontal resolution configuration with comprehensive chemistry. While the background stratospheric aerosol optical depth is elevated in the middle atmosphere configurations as compared to the comprehensive chemistry configuration, it is comparable among all configurations during volcanic eruptions. For any purposes other than those needing an accurate representation of tropospheric organic chemistry and secondary organic aerosols, these simplified chemistry configurations deliver reliable simulations of the whole atmosphere that require 35% and 86% fewer computational resources at nominal 1 and 2° horizontal resolution, respectively.

54 ENVIRONMENTAL SCIENCES↗