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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Electrical Resistivity Changes During Heating Experiments Unravel Heterogeneous Thermal‐Hydrological‐Mechanical Processes in Salt Formations

Abstract Rock salt is considered a suitable medium for the permanent disposal of heat‐generating radioactive waste due to its isolation properties. However, excavation damage and heating induce complex and heterogeneous thermal‐hydrological‐mechanical (THM) processes across different zones. Quantifying this heterogeneity is crucial for accurate long‐term performance assessment models, but traditional methods lack the necessary resolution. This study employs 4D electrical resistivity tomography (ERT) monitoring during controlled heating experiments in a salt formation to unravel the spatiotemporal dynamics of THM processes. Advanced time‐lapse inversion and clustering analysis quantify subsurface properties and map the heterogeneity of THM dynamics. The ERT results can estimate subsurface properties and delineate the damaged and intact zones, enabling appropriate parameterization and representation of processes for long‐term modeling. This approach may be used in further improving the predictive models and ensuring the safe long‐term disposal of radioactive waste in rock salt.

58 GEOSCIENCES↗
DOE OSTI2021

Nonequilibrium phonon tuning and mapping in few-layer graphene with infrared nanoscopy

Electron-phonon interactions are fundamentally important physical processes responsible for many key discoveries in condensed matter physics and material sciences. Herein, by exploiting the scattering-type scanning near-field optical microscope (s-SNOM) excited with a femtosecond infrared (IR) laser, we explored the strong coupling between IR phonons in few-layer graphene (FLG) with ultrahot electrons, which are heated up by the intense laser field enhanced by the s-SNOM tip. More specifically, we found that the intensity of the phonon resonance can be tuned systematically by varying the laser power that controls the electron temperature. Furthermore, the high spatial resolution of s-SNOM allows us to map the local phonon characteristics at sharp boundaries and nanostructures. Our results offer insights into the intriguing physics behind the electron-phonon interactions in nonequilibrium conditions and open a pathway for manipulating phonons with optical means.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Gravothermal evolution of dark matter halos with differential elastic scattering

Here, we study gravothermal evolution of dark matter halos in the presence of differential self-scattering that has strong velocity and angular dependencies. We design controlled N-body simulations to model Rutherford and Møller scatterings in the halo, and follow its evolution in both core-expansion and -collapse phases. The simulations show the commonly-used transfer cross section underestimates the effects of dark matter self-interactions, but the viscosity cross section provides an accurate approximation for modeling angular-dependent dark matter scattering. We investigate thermodynamic properties of the halo, and find that the three moments of the Boltzmann equation under the fluid approximation are satisfied. We further propose a constant effective cross section, which integrates over the halo's characteristic velocity dispersion with weighting kernels motivated by kinetic theory of heat conduction. The effective cross section provides a good approximation to differential self-scattering for most of the halo evolution. It indicates that we can map astrophysical constraints on a constant self-interacting cross section to an SIDM model with velocity- and angular-dependent scatterings.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Optimization of a High Pressure Turbine Blade and Sector-Based Annular Rig Design for Supercritical CO2 Power Cycle Representative Testing

Abstract As part of the ongoing research into the design of hardware for zero emission cycles, a first-stage high-pressure turbine (HPT) blade is optimized for a 300 MWe supercritical CO2 (sCO2) power cycle using the surrogate-assisted genetic algorithm optimizer in Numeca FINE/Design three-dimensional with objectives of increasing efficiency and decreasing heat load to the blade. Supercritical CO2 property tables are constructed from NIST REFPROP data for the condensable gas simulation in FINE/Turbo. A detailed mesh sensitivity study is performed for a baseline design to identify the proper-grid refinement and efficiently allocate resources for the optimization. Seventy design variables are selected for the initial population generation. Self-organizing maps are then used to focus the design variables on the most important ones affecting the objective functions. The optimization results in approximately 3000 three-dimensional Reynolds Averaged Navier Stokes simulations of different blade shapes with increases in efficiency of up to 0.85% and decreases in heat load of 14%. Families of blade shapes are identified for experimental testing in an annular rig at the Purdue Experimental Turbine Aerothermal Laboratory. A design to adapt the annular cascade for testing optimized geometries is introduced, which features eccentric radius sectors allowing for scaled-up geometries of sCO2 optimized blade profiles to be tested at design cycle representative conditions at high Reynolds numbers in dry air. Analysis into the effects of Reynolds number, working fluid, and geometric relations are presented to prove the efficacy of the test method.

Engineering↗
DOE OSTI2022

Thermodynamic insights into the intricate magnetic phase diagram of EuAl 4

The tetragonal intermetallic compound EuAl 4 hosts an exciting variety of low-temperature phases. In addition to a charge density wave below 140 K, four ordered magnetic phases are observed below 15.4 K. Recently, a skyrmion phase was proposed based on Hall effect measurements under a c-axis magnetic field. Here, we present a detailed investigation of the phase transitions in EuAl 4 under c-axis magnetic field. Our dilatometry, heat-capacity, DC magnetometry, AC magnetic susceptibility, and resonant ultrasound spectroscopy measurements reveal three magnetic phase transitions not previously reported. The first key result is a detailed H ∥ [001] magnetic phase diagram mapping the seven phases we observe. Second, we identify a high-field phase, phase VII, which directly corresponds to the region were skyrmions have been previously suggested. Our results provide guidance for future studies exploring the complex magnetic interactions and spin structures in EuAl 4 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Benefits of using multiple Raman laser wavelengths for characterizing defects in a UO 2 matrix

Abstract Raman spectroscopy is one of the most useful techniques for studying the structure of UO 2 and changes due to specific defects caused by doping, changes in stoichiometry, irradiation, or heating under oxidizing conditions. In this paper, we illustrate several aspects of the application of Raman techniques to the study of UO 2 , including the use of wavelength‐dependent excitation (455, 532, and 785 nm) to assess the effects of doping (Nd, Th, and Zr), ion irradiation, and in situ heating and oxidation (UO 2 to U 3 O 8 ). Additionally, we show examples of how correlative microscopy is possible using electron backscatter diffraction combined with Raman maps of specific vibration bands or of laser‐induced luminescence generated by rare‐earth dopants in the matrix. For each of these applications, we suggest optimal excitation wavelengths that vary depending on the desired data. Blue (455 nm) excitation tends to promote oxidation even at low powers, but because Raman spectra change little with doping, irradiation‐induced changes are easier to observe. Green (532 nm) excitation is optimal for observing electron–phonon resonance effects in UO 2 and offers a good compromise for high‐temperature oxidation experiments, delivering high‐quality spectra for both UO 2 and U 3 O 8 . Infrared (785 nm) excitation is best for observing “defect” bands associated with doping in UO 2 , as changes with irradiation are small. Raman spectroscopy is particularly suited for studying the stability of UO 2 towards oxidation in the presence of dopants simulating fission products, where electron–phonon resonant effects, dopant ion luminescence, and mapping can be used together to investigate structural rearrangement as a function of temperature. These techniques can offer insight into microstructural changes in UO 2 fuels at higher burnups envisioned in future reactors.

42 ENGINEERING↗
DOE OSTI2026

Gas-driven short disconnection mitigates thermal runaway in Li-ion batteries under mechanical abuse

Mechanical abuse poses a critical safety risk to Li-ion batteries by inducing internal short circuits that initiate thermal runaway. Remarkably, voltage recovery frequently emerges during thermal runaway initiation, a phenomenon that conventional theories fail to explain. Here, our study develops a new multiphysics mechanism to explain voltage recovery, termed gas-driven short disconnection, whereby internal gas pressure mechanically disengages short-circuit contacts and causes the cell voltage to rebound. This mechanism incorporates gas generation and its structural impact on the short circuit. Real-time optical and thermal imaging and X-ray computed tomography reveal fluid-structure interaction between internal gas flow and adjacent shorting contacts. We establish a mechanistic framework linking gas-driven short disconnection to cell-level voltage and temperature responses, elucidating the extension–truncation pattern of voltage recovery. Furthermore, thermal regime maps show that a voltage recovery duration exceeding 5 s correlates with limited temperature rise below 150 °C, indicating that sustained short-circuit disconnection suppresses Joule heating. Additionally, a dimensionless criterion is deduced from scaling analysis for physical plausibility of gas-driven short disconnection in mechanically abused cells. This finding inspires smart venting control, which regulates gas release to maintain the internal pressure while dissipating gas enthalpy, thereby providing a device-level strategy for thermal runaway mitigation.

Gas-driven short disconnection↗
DOE OSTI2022

Dissecting Nearby Galaxies with piXedfit. I. Spatially Resolved Properties of Stars, Dust, and Gas as Revealed by Panchromatic SED Fitting

We study spatially resolved properties (on spatial scales of ~1–2 kpc out to at least 3 effective radii) of the stars, dust, and gas in 10 nearby spiral galaxies. The properties of the stellar population and dust are derived by fitting the spatially resolved spectral energy distribution (SED) with more than 20 photometric bands ranging from far-ultraviolet to far-infrared. Our newly developed software piXedfit performs point-spread function matching of images, pixel binning, and models the stellar light, dust attenuation, dust emission, and emission from a dusty torus heated by an active galactic nucleus simultaneously through the energy-balance approach. With this self-consistent analysis, we present the spatially resolved version of the IRX–βrelation, finding that it is consistent with the relationship from the integrated photometry. We show that the old stellar populations contribute to the dust heating, which causes an overestimation of the star formation rate (SFR) derived from the total ultraviolet and infrared luminosities on kiloparsec scales. With archival high-resolution maps of atomic and molecular gas, we study the radial variation of the properties of the stellar populations (including stellar mass, age, metallicity, and SFR), dust (including dust mass, dust temperature, and abundance of polycyclic aromatic hydrocarbon), and gas, as well as dust-to-stellar mass and dust-to-gas mass ratios. We observe a depletion of the molecular gas mass fraction in the central region of the majority of the galaxies, suggesting that the lack of available fuel is an important factor in suppressing the specific SFR at the center.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Energy-Dispersive X-ray Spectroscopy and Atom-probe Tomography Data Quantifying Component-Ratios of Multicomponent Nano-Precipitates in Ion-Irradiated Ceria

Samples of ~1 µm films of CeO2 doped with 2 wt% Mo, 1.5 wt% Ru, 0.75 wt% Pd, 0.5 wt% Re and 0.25 wt% Rh grown with pulsed laser deposition were irradiated with I2+ ions (610°C and 730°C, 1016 and 5×1016 I2+/cm2). For selected samples post-irradiation heat treatment was conducted (900°C, 1100°C). The specimens were sectioned with focussed ion beam milling and characterized in a transmission electron microscope with energy dispesive x-ray spectroscopy, and with atom-probe tomography. Energy dispersive x-ray spectroscopy was used to obtain elemental maps showing the distribution of dopants in the specimen after exposure. Some of these maps are discussed in detail in our companion article “Formation of multicomponent alloy particles in doped ceria under I2+ ion irradiation and thermal annealing” in the Journal of Nuclear Materials [REF]. Advanced computational analysis could be used to more accurately quantify local compositions. Data is provided for additional regions of interest and one additional irradiation condition. The doped Ceria film that was heat treated at 1100 °C delaminated from the substrate in most places. Samples were extracted from the underside of a delaminated piece and analyzed with atom-probe tomography. The resulting data show Ceria and a Mo-rich particle and demonstrate that this approach is feasable in principle to study local compositions in a sample exposed to such extreme conditions.

multicomponent alloys, epsilon phase, EDS, atom pr↗
DOE OSTI2025

Thermal 𝑅⁢𝐶 circuit model for resolving the thermal paradox

Thermal measurements of heat capacity and thermal conductivity in a wide range of insulators and superconductors exhibit a “thermal paradox”: a large linear specific heat reminiscent of neutral Fermi surfaces (associated with fractionalized quasiparticles) in nonmetallic samples that exhibit no corresponding linear temperature coefficient to the thermal conductivity. At first sight, these observations appear to support the formation of a continuum of thermally localized many-body excitations, a form of many-body localization that would be fascinating in its own right. Here, in this work, by mapping thermal conductivity measurements onto thermal 𝑅⁢𝐶 circuits, we argue that the development of extremely long thermal relaxation times, a “thermal bottleneck,” is likely in systems with either many-body localization or neutral Fermi surfaces due to the large ratio between the electron and phonon specific heat capacities. We present a reevaluation of thermal conductivity measurements in materials exhibiting a thermal paradox that can be used in future experiments to deliberate between these two exciting alternatives.

heat transfer↗
DOE OSTI2024

Unraveling Interdiffusion Phenomena and the Role of Nanoscale Diffusion Barriers in the Copper–Gold System

Diffusion is one of the most fundamental concepts in materials science, playing a pivotal role in materials synthesis, forming, and degradation. Of particular importance is solid state interdiffusion of metals which defines the usable parameter space for material combinations in the form of alloys. This parameter space can be explored on the macroscopic scale by using diffusion couples. However, this method reaches its limit when going to low temperatures, small scales, and when testing ultrathin diffusion barriers. Therefore, this work transfers the principle of the diffusion couples to small scales by using core–shell nanowires and in situ heating. This allows us to delve into the interdiffusion dynamics of copper and gold, revealing the interplay between diffusion and the disorder–order phase transition. Our in situ TEM experiments in combination with chemical mapping reveal the interdiffusion coefficients of Cu and Au at low temperatures and highlight the impact of ordering processes on the diffusion behavior. The formation of ordered domains within the solid-solution is examined using high-resolution imaging and nanodiffraction including strain mapping. In addition, we examine the effectiveness of ultrathin Al 2 O 3 barrier layers to control interdiffusion of the diffusion couple. Our findings indicate that a 5 nm thick layer serves as an efficient diffusion barrier. Furthermore, this research provides valuable insights into the interdiffusion behavior of Cu and Au on the nanoscale, offering potential applications in the development of miniaturized integrated circuits and nanodevices.

alloys↗
DOE OSTI2025

Platinum liquid-vapor phase boundary mapped by fluid flyer experiments

We report a direct measurement of the temperature and density of a metal along its liquid-vapor coexistence (L-V) curve. By shocking platinum to a high-pressure liquid, we imparted sufficient heat for subsequent isentropic release to place it in a state on the boundary between the liquid and vapor phases. Released material in the liquid phase acted as a high velocity flyer pinned to the L-V curve. We measured velocity and radiant emission of the flyer as well as the interface motion and transiting shock states induced in a downstream window material by its impact. We used these measurements to calculate temperature and density of the L-V curve state which we compare to density functional theory predictions.

Equations of state↗
DOE OSTI2025

FY-25 Progress on Computational Modeling of the Water Based NSTF

This report summarizes the system level modeling using RELAP5-3D of the Natural Convection Shutdown Heat Removal Test Facility (NSTF) completed in FY25. This year’s work focuses on a new tank configuration where the inlet of the tank was lowered in elevation by 45”. The stability boundaries of the NSTF are thoroughly studied and stability maps are constructed based on the stability and the oscillation patterns of the system. Five distinct operational modes are identified, namely single-phase liquid, uniform double peak oscillations, uniform sinusoidal oscillations, stable two-phase flow, and non-uniform oscillations. Next, the riser inlet throttling case of experimental test Run-104 is simulated with the RELAP5 model where good agreement is obtained between the model and the experimental data. The simulation also highlights the effects of backflow of water from the tank to the upper region of the chimney. Additionally, the decay heat removal test of Run-99 is simulated with the RELAP5 model. Comparison is carried out between this run and a similar run with the mid-tank inlet of Run-74 performed in FY22. With the lower tank inlet, the RELAP5 model is able to predict the experimental data more accurately than the previous mid tank inlet configuration. The discrepancy in model prediction accuracy highlights the non-symmetrical spatial effects in the tank that would otherwise be more easily captured with higher fidelity models. Lastly, two exploratory studies are conducted to investigate the behaviors of the NSTF when 1) heating is provided to the downcomer and 2) a bypass channel is added between the horizontal chimney section to the downcomer.

42 ENGINEERING↗
DOE OSTI2020

Improved Performance of Cu(InGa)(SeS) 2 PV Modules Using the Reaction of Metal Precursors. Final Report

This project “Improved Performance of Cu(InGa)(SeS) 2 PV Modules using the Reaction of Metal Precursors” was a partnership led by the Institute of Energy Conversion (IEC) at the University of Delaware with Columbia University and the Molecular Foundry at the Lawrence Berkeley National Laboratory. The aim was to develop pathways to improve Cu(InGa)(SeS) 2 (CIGSS) thin film photovoltaic modules using processes compatible with low manufacturing cost. The CIGSS approach investigated was a two-step process including deposition of metal precursor films following by reaction in hydride gases utilizing IEC’s novel reactor. The process was similar to that under commercial development by the project’s industry partner Stion. When Stion went out of business mid-project the focus changed to a rapid thermal process considered more commercially viable. Approaches to improve the performance of solar cells using the reacted films focused on two material innovations. First, the overall Ga content was increased to increase the operating voltage, which is desirable for scale-up to commercial modules. Second, the processing and performance advantages arising from Ag alloying were investigated. Advanced characterization guided process and material development including control of relative composition gradients. Research on the formation of Cu-Ga-In metal precursors utilized sputtering deposition which is normally used in commercial applications. The work resulted in processes for deposition of precursor stacks with increased relative Ga content and effects of deposition parameters on morphology and phase composition were established. It was shown that the metal precursor films have comparable phase composition and morphology so subsequent reaction follows from the same starting point. The addition of Ag to the metal precursors gave more uniform morphology and improved adhesion of reacted films which enable higher reaction temperature for faster processing. A novel outcome was the discovery of a previously undocumented material phase in sputter-deposited and evaporated Ag-Cu-In-Ga thin films. Hydride gas reaction processes including time-temperature-concentration profiles were developed for different precursor compositions. This enables control of composition profiles to engineer through-film gradients for solar cell optimization with characterization and simulations used to correlate measured film composition profiles to measurements of devices. In particular, the gradient of sulfur at the front of the CIGSS film was found to be critical. The simulations guided process development leading to improved reproducibility of devices improved performance with higher Ga content and higher voltage. With Ag-alloyed precursors, the reaction pathways leading were determined. A significant finding was that Ag-alloying increases the reaction rate to completely convert precursor films to the final chalcopyrite which could enable reduced reaction time to benefit manufacturability. To maintain potential commercial viability, the process under investigation was refocused to a rapid thermal process that could potentially be incorporated into an in-line process for manufacturing. Precursors with different composition were capped with an extra selenium layer and reacted in hydrogen sulfide 5-15 minutes, compared to typically 2 hours in the previous multi-step batch process. Critical RTP parameters were identified to control the reaction. Further optimization would be needed for high efficiency solar cells but pathways to high quality devices with further optimization and improved heating uniformity were developed. The project also developed new optoelectronic characterization approaches with a focus on development and application of spatial- and time-resolved photoluminescence and a custom mapping photoluminescence microscope built. It was shown how critical electronic transport properties strongly depend on the chemical composition of the material and that a wide range of samples show inhomogeneity on a length scale larger than the grains in the films. Additionally, two-photon excitation capability was developed to distinguish bulk vs surface losses. The project advances the state-of-the -art for precursor reaction processes in several ways that could impact manufacturing. This includes validation of approaches to increase voltage and establishment of model-guided control to form optimal composition profiles. The application of process control approaches with knowledge of phase formation and reaction pathways can be critically valuable in designing a large-scale process.

14 SOLAR ENERGY↗
DOE OSTI2022

Inverse Modeling of Hydrologic Parameters in CLM4 via Generalized Polynomial Chaos in the Bayesian Framework

In this work, generalized polynomial chaos (gPC) expansion for land surface model parameter estimation is evaluated. We perform inverse modeling and compute the posterior distribution of the critical hydrological parameters that are subject to great uncertainty in the Community Land Model (CLM) for a given value of the output LH. The unknown parameters include those that have been identified as the most influential factors on the simulations of surface and subsurface runoff, latent and sensible heat fluxes, and soil moisture in CLM4.0. We set up the inversion problem in the Bayesian framework in two steps: (i) building a surrogate model expressing the input–output mapping, and (ii) performing inverse modeling and computing the posterior distributions of the input parameters using observation data for a given value of the output LH. The development of the surrogate model is carried out with a Bayesian procedure based on the variable selection methods that use gPC expansions. Our approach accounts for bases selection uncertainty and quantifies the importance of the gPC terms, and, hence, all of the input parameters, via the associated posterior probabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Deconvoluting thermomechanical effects in X-ray diffraction data using machine learning

X-ray diffraction is ideal for probing the sub-surface state during complex or rapid thermomechanical loading of crystalline materials. However, challenges arise as the size of diffraction volumes increases due to spatial broadening and because of the inability to deconvolute the effects of different lattice deformation mechanisms. Here, we present a novel approach that uses combinations of physics-based modeling and machine learning to deconvolve thermal and mechanical elastic strains for diffraction data analysis. The method builds on a previous effort to extract thermal strain distribution information from diffraction data. The new approach is applied to extract the evolution of the thermomechanical state during laser melting of an Inconel 625 wall specimen which produces significant residual stress upon cooling. A combination of heat transfer and fluid flow, elasto-plasticity and X-ray diffraction simulations is used to generate training data for machine-learning (Gaussian process regression, GPR) models that map diffracted intensity distributions to underlying thermomechanical strain fields. First-principles density functional theory is used to determine accurate temperature-dependent thermal expansion and elastic stiffness used for elasto-plasticity modeling. The trained GPR models are found to be capable of deconvoluting the effects of thermal and mechanical strains, in addition to providing information about underlying strain distributions, even from complex diffraction patterns with irregularly shaped peaks.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Additive manufacturing of ceramic materials for energy applications: Road map and opportunities

Among engineering materials, ceramics are indispensable in energy applications such as batteries, capacitors, solar cells, smart glass, fuel cells and electrolyzers, nuclear power plants, thermoelectrics, thermoionics, carbon capture and storage, control of harmful emission from combustion engines, piezoelectrics, turbines and heat exchangers, among others. Advances in additive manufacturing (AM) offer new opportunities to fabricate these devices in geometries unachievable previously and may provide higher efficiencies and performance, all at lower costs. This article reviews the state of the art in ceramic materials for various energy applications. The focus of the review is on material selections, processing, and opportunities for AM technologies in energy related ceramic materials manufacturing. The aim of the article is to provide a roadmap for stakeholders such as industry, academia and funding agencies on research and development in additive manufacturing of ceramic materials toward more efficient, cost-effective, and reliable energy systems.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Inverse Mapping of the Collision Kernel and Wall Flux Scaling in a Tall Convection‐Cloud Chamber Using Local Sensors and Knowledge‐Informed Deep Learning

Droplet collision–coalescence is a crucial process in cloud physics, but accurately representing this process under different dynamical conditions remains challenging. A proposed future convective‐cloud chamber aims to investigate this key process, but the method for observing it remains unclear, even though it is theoretically established that collision‐coalescence will occur. This study serves as a proof‐of‐concept demonstration of how knowledge‐informed deep learning, combined with measurement data from local sensors in the chamber, can be used to estimate the collision kernels, which determine how the droplet size distribution evolves during collision‐coalescence. In addition to estimating the collision kernel, we also address wall fluxes, another uncertain but important process that acts as a source of heat and moisture in the chamber. Ensemble runs of large‐eddy simulations are conducted by scaling the wall fluxes and the collision kernel, while the measured flow and cloud properties are used as inputs for a neural network. Results indicate that this approach successfully maps the scaling of wall fluxes and the collision kernel with biases of approximately 1% or less relative to the range of the target data. This proof‐of‐concept lays the groundwork for future applications; when the real measurements are available, real sensor data combined with the trained model presented in this work will enable estimation of the actual wall fluxes and collision kernel.

cloud chamber↗