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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Three-dimensional hard X-ray ptychographic reflectometry imaging on extended mesoscopic surface structures

Many nanodevices and quantum devices, with their sizes often spanning from millimeters down to sub-nanometer, have intricate low-dimensional, non-uniform, or hierarchical structures on surfaces and interfaces. Since their functionalities are dependent on these structures, high-resolution surface-sensitive characterization becomes imperative to gain a comprehensive understanding of the function–structure relationship. We thus developed hard x-ray ptychographic reflectometry imaging, a new technique that merges the high-resolution two-dimensional imaging capabilities of hard x-ray ptychography for extended objects, with the high-resolution depth profiling capabilities of x-ray reflectivity for layered structures. The synergy of these two methods fully leverages both amplitude and phase information from ptychography reconstruction to not only reveal surface topography and localized structures, such as shapes and electron densities, but also yields statistical details, such as interfacial roughness that is not readily accessible through coherent imaging solely. The hard x-ray ptychographic reflectometry imaging is well-suited for three-dimensional imaging of mesoscopic samples, particularly those comprising planar or layered nanostructures on opaque supports, and could also offer a high-resolution surface metrology and defect analysis on semiconductor devices, such as integrated nanocircuits and lithographic photomasks for microchip fabrications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Virtual tower measurements during the American WAKE ExperimeNt (AWAKEN)

Dual-Doppler lidar measurements were made during the American WAKE ExperimeNt to provide height-resolved measurements of wind speed and direction at multiple locations immediately south of the leading row turbines in the King Plains wind farm in Oklahoma. These so-called virtual tower measurements were performed to characterize the inflow into the wind farm and to assess possible upwind blockage effects due to the collective action of the wind farm. The campaign was conducted from 12 November 2022 to 17 October 2023, during which time 14 unique virtual tower locations were sampled with heights ranging from 240 to 490 m AGL. The wind retrieval algorithm provided estimates of the horizontal winds and their uncertainties with a vertical resolution of about 10 m, while also accounting for the tilt of the lidar platform. The virtual tower results are compared to collocated lidar wind profiling data at the A1 site, which was located roughly 2.4 rotor diameters south of the nearest turbine. The wind speed difference between the wind profiler and the virtual tower was found to be quite sensitive to atmospheric stability and wind direction below 250 m AGL. The largest differences were observed for inflow under stable conditions, where the profiler wind speeds were observed to be about 22% lower than the virtual tower near hub height. These results suggest that there are persistent horizontal gradients in the flow upwind of the wind farm which result in biased estimates using standard ground-based lidar wind profiling methods.

17 WIND ENERGY↗
DOE OSTI2025

Efficient sampling of free energy landscapes with functions in Sobolev spaces

Molecular simulations of biological and physical phenomena generally involve sampling complicated, rough energy landscapes characterized by multiple local minima. In this work, we introduce a new family of methods for advanced sampling that draw inspiration from functional representations used in machine learning and approximation theory. As shown here, such representations are particularly well suited for learning free energies using artificial neural networks. As a system evolves through phase space, the proposed methods gradually build a model for the free energy as a function of one or more collective variables, from both the frequency of visits to distinct states and generalized force estimates corresponding to such states. Implementation of the methods is relatively simple and, more importantly, for the representative examples considered in this work, they provide computational efficiency gains of up to several orders of magnitude over other widely used simulation techniques.

Approximation theory↗
DOE OSTI2024

Ligand field exciton annihilation in bulk CrCl 3

The layered van der Waals material CrCl 3 exhibits very strongly bound ligand field excitons that control optoelectronic applications and are connected with magnetic ordering by virtue of their d-orbital origin. Time-resolved photoluminescence of these exciton populations at room temperature shows that their relaxation is dominated by exciton–exciton annihilation and that the spontaneous decay lifetime is very long. Furthermore, these observations allow the rough quantification of the exciton annihilation rate constant and contextualization in light of a recent theory of universal scaling behavior of the annihilation process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A review of fluids under nanoconfinement: Reactivity, geomechanics, phase transitions, and flow

Due to its many industrial applications, the physics associated with the nanoconfinement of fluids has garnered great attention from the scientific community in roughly the last fifteen years. One pioneer of that research has been the Multi-Scale Fluid-Solid Interactions in Architected and Natural Materials (MUSE) Energy Frontier Research Center, which produced more than 50 journal articles from 2018 to 2023. We structure the findings of MUSE into four categories and contextualize the work with the broader literature. Here, the four categories are (1) the dependence of chemical reactions on the degree of confinement, which given the lower freedom of motion of molecules yet improved availability of reaction sites generally lead to enhancement from bulk reactions; (2) the mechanical properties of the porous matrix, which are dependent on the heterogeneity of the system in terms of both composition and structure; (3) the phase transitions under nanoconfinement, which are influenced by the pore size and morphology, surface chemistry, and substrate composition; and (4) the physical controls of slip flow, which demonstrate the importance of several factors, such as wettability. These aspects of nanoconfinement are becoming clearer, but there are other elements such as mathematical theory that are still being developed.

58 GEOSCIENCES↗
DOE OSTI2025

Comparison of tungsten versus molybdenum for double shell capsules using machine learning design optimization

Double shell targets are an alternative ignition platform for inertial confinement fusion. One design consideration for double shell targets is the choice of inner shell material to help trap radiation emitted by the hot fuel to aid ignition. Materials such as molybdenum and tungsten are of interest for the inner shell layer of the targets. While molybdenum has a lower density that could inhibit instability growth and allow for radiography and code benchmarking, tungsten has a higher density that could provide more compression and confinement. These tradeoffs have been explored using optimized designs for each material. Our previous work [Vazirani et al., “Coupling 1D xRAGE simulations with machine learning for graded inner shell design optimization in double shell capsules,” Phys. Plasmas 28, 122709 (2021); Vazirani et al., “Coupling multi-fidelity xRAGE with machine learning for graded inner shell design optimization in double shell capsules,” Phys. Plasmas 30, 062704 (2023); and Vazirani et al., “Bayesian batch optimization for molybdenum versus tungsten inertial confinement fusion double shell target design,” Stat. Anal. Data Min. 17, e11698 (2024)] resulted in a multi-fidelity Bayesian optimization framework to find yield-optimized double shell target geometries. By leveraging simulations of varying fidelities (one-dimensional and two-dimensional) to inform one another, the multi-fidelity optimization was able to optimize a design in the highest fidelity with significantly fewer simulations than would be used in a systematic parameter scan. In this work, we apply the multi-fidelity Bayesian optimization to explore the optimized designs of double shell targets with molybdenum and tungsten inner shells as well as the physics producing the high performing implosions. A physics exploration of all the simulations used in this study shows trends in designs that contribute to high yields, ion temperatures, and fuel areal densities. Comparison of molybdenum and tungsten simulations shows that they can produce similar implosion conditions with different geometries, which would be important to study in experiments. Graded density layers produce varying performances with the two materials but continue to be of interest for future studies along with studies of doped inner shell materials and applied surface roughness.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Shock-driven three-fluid mixing with various chevron interface configurations

When a shock wave crosses a density interface, the Richtmyer–Meshkov instability causes perturbations to grow. Richtmyer–Meshkov instabilities arise from the deposition of vorticity from the misaligned density and pressure gradients at the shock front. In many engineering applications, microscopic surface roughness will grow into multi-mode perturbations, inducing mixing between the fluid on either side of an initial interface. Applications often have multiple interfaces, some of which are close enough to interact in the later stages of instability growth. In this study, we numerically investigate the mixing of a three-layer system with periodic zigzag (or chevron) interfaces, calculating the dependence of the width and mass of mixed material on properties such as the shock timing, chevron amplitude, multi-mode perturbation spectrum, density ratio, and shock mach number. The multi-mode case is also compared with a single-mode perturbation. The Flash hydrodynamic code is used to solve the Euler equations in three dimensions with adaptive grid refinement. Key results include a significant increase in mixed mass when changing from a single-mode to a multi-mode perturbation on one of the interfaces. The mixed width is mainly sensitive to the density ratio and chevron amplitude, whereas the mixed mass also depends on the multi-mode spectrum. In conclusion, steeper initial perturbation spectra have lower mixed mass at early times but a greater mixed mass after the reflected shock transits back across the layer.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Magnetic metamaterials by ion-implantation

We present a method for the additive fabrication of planar magnetic nanoarrays with minimal surface roughness. Synthesis is accomplished by combining electron-beam lithography, used to generate nanometric patterned masks, with ion implantation in thin films. By implanting 56 Fe + ions, we are able to introduce magnetic functionality in a controlled manner into continuous Pd thin films, achieving 3D spatial resolution down to a few tens of nanometers. Our results demonstrate the application of this technique in fabricating square artificial spin ice lattices, which exhibit well-defined magnetization textures and interactions among the patterned magnetic elements.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A multi-scale cognitive interaction model of instrument operations at the Linac Coherent Light Source

The Linac Coherent Light Source (LCLS) is the world’s first x-ray free electron laser. It is a scientific user facility operated by the SLAC National Accelerator Laboratory, at Stanford, for the U.S. Department of Energy. As beam time at LCLS is extremely valuable and limited, experimental efficiency—getting the most high quality data in the least time—is critical. Our overall project employs cognitive engineering methodologies with the goal of improving experimental efficiency and increasing scientific productivity at LCLS by refining experimental interfaces and workflows, simplifying tasks, reducing errors, and improving operator safety and stress. Here, in this study, we describe a multi-agent, multi-scale computational cognitive interaction model of instrument operations at LCLS. Our model simulates the aspects of human cognition at multiple cognitive and temporal scales, ranging from seconds to hours, and among agents playing multiple roles, including instrument operator, real time data analyst, and experiment manager. The model can roughly predict impacts stemming from proposed changes to operational interfaces and workflows. Example results demonstrate the model’s potential in guiding modifications to improve operational efficiency. We discuss the implications of our effort for cognitive engineering in complex experimental settings and outline future directions for research. The model is open source, and the videos of the supplementary material provide extensive detail.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Exploring scenarios for enhanced fuel compression and performance on the National Ignition Facility with machine-learning-aided design techniques

Recent fusion experiments on the National Ignition Facility (NIF) have achieved ignition, producing multi-MJ fusion yields for input laser energies of roughly 2 MJ [Abu-Shawareb et al., Phys. Rev. Lett. 132, 065102 (2024)]. Building on the success of the target designs that have achieved ignition, we explore new implosion scenarios predicted to generate significantly more compression of the dense DT ice layer and correspondingly higher yields while preserving many of the key physics characteristics of present-day ignition designs. Our main result is a novel 3-shock implosion scheme that effectively minimizes the shock-induced entropy in the dense, accelerating DT shell and maximizes the resulting fuel compression subject to a fixed leading shock strength consistent with present-day ignition experiments, which is necessary to melt the crystalline high-density carbon ablator. Compared to the first NIF experiment to fulfill Lawson's ignition criterion, shot N210808 [Abu-Shawareb et al., Phys. Rev. Lett. 129, 075001 (2022)], our design exhibits a 40% increase in simulated peak areal density (ρR) and a 5× increase in 1D fusion yield using a 4% lighter ablator and identical DT payloads. We also present a complete integrated 2D hohlraum design and laser pulse specifications capable of generating the desired 3-shock drive and maintaining control of the low-mode capsule implosion symmetry, where the increase in simulated 2D yield relative to N210808 is > 10×. This new implosion regime was discovered with help from a machine-learning-enabled capsule design optimization framework. We outline the workflow this automated tool uses to identify improved design candidates by running several rounds of capsule simulations, constructing a surrogate model mapping input variations to key physics output quantities, and querying the resulting statistical model to propose adjustments to the x-ray drive and capsule to reach a set of physics objectives prescribed by the designer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Nonlinear evolution, propagation, electron-trapping, and damping effects of ion-acoustic solitons using fully kinetic PIC simulations

We investigate ion acoustic solitary waves (solitons) of varying amplitudes in a one-dimensional plasma using fully kinetic particle-in-cell simulations. The initial soliton conditions are based on the Korteweg–de Vries (KdV) equation, treating ions as a cold species and electrons with finite temperature. Our findings reveal that KdV solitons evolve nonlinearly to a saturated state at higher amplitude, deviating from KdV predictions for ion density and electric potential, and from the Boltzmann relation for electron density. At this saturated state, the KdV model cannot accurately describe the soliton behavior. For small amplitudes, Sagdeev's model describes the saturated state, but not the soliton width; for larger amplitudes, it models the width accurately, but not the amplitude. These discrepancies arise from assuming a Boltzmann relation for electron density, while electron trapping creates non-Boltzmann densities—a deviation that increases with soliton amplitude. Additionally, we observe that the soliton amplitude oscillates roughly at the electron bounce frequency. The soliton is better described by Schamel's electron density formulation and a modified KdV equation incorporating electron trapping. The soliton velocity matches best with predictions from Sagdeev's and Schamel's models. Moreover, the soliton speed–amplitude relationship differs from existing theoretical predictions. Finally, we find minimal ion and electron Landau damping effects.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

High temperature melting of dense molecular hydrogen from machine-learning interatomic potentials trained on quantum Monte Carlo

We present results and discuss methods for computing the melting temperature of dense molecular hydrogen using a machine learned model trained on quantum Monte Carlo data. In this newly trained model, we emphasize the importance of accurate total energies in the training. We integrate a two phase method for estimating the melting temperature with estimates from the Clausius–Clapeyron relation to provide a more accurate melting curve from the model. We make detailed predictions of the melting temperature, solid and liquid volumes, latent heat, and internal energy from 50 to 180 GPa for both classical hydrogen and quantum hydrogen. At pressures of roughly 173 GPa and 1635 K, we observe molecular dissociation in the liquid phase. Here, we compare with previous simulations and experimental measurements.

08 HYDROGEN↗
DOE OSTI2025

Metal-organic chemical vapor deposition of MgGeN2 films on GaN and sapphire

MgGeN2 films were synthesized using metal-organic chemical vapor deposition on GaN/c-sapphire templates and c-plane sapphire substrates. Energy-dispersive x-ray spectroscopy was used to estimate the cation composition ratios. To mitigate magnesium evaporation, the films were grown at pyrometer temperature 745 °C with a wafer rotation speed of 1000 rpm. Growth rates were determined by fitting energy-dispersive x-ray spectroscopy spectra to film thicknesses using NIST DTSA-II software. The thickness estimates determined by this method were consistent with scanning transmission electron microscopy measurements done for selected samples. Scanning electron microscopy images revealed faceted surfaces indicative of a tendency toward three-dimensional growth. X-ray diffraction spectra confirmed that the films were highly crystalline and exhibited preferential orientation in alignment with the substrate. Atomic force microscopy measurements show that film thicknesses are consistent across samples grown on both GaN templates and sapphire substrates, with typical roughnesses around 10 nm. Transmittance spectra of films grown on double-side-polished sapphire substrates yielded band gaps of 4.28 ± 0.06 eV for samples exhibiting close-to-ideal stoichiometry. Comparison of the measured spectra with ab initio calculations are in good agreement both near the bandgap and at higher energies where excitation is into higher-lying bands. These findings provide insight into the growth and characterization of MgGeN2, contributing to the development of this material for potential applications in optoelectronics and power electronics.

Hu, Chenxi (ORCID:0000000236299660)↗
DOE OSTI2025

Nm-scale electrical resistance imaging on CdTe by scanning spreading resistance microscopy

Local resistance imaging can provide information on nm-scale carrier distribution in semiconductor devices. Scanning spreading resistance microscopy (SSRM), an atomic force microscopy-based nm-scale resistance mapping technique, has been developed for carrier delineation in Si microdevices. We report on the development and validation of SSRM on CdTe materials, by testing on molecular beam epitaxy (MBE) grown CdTe films. The probe/CdTe contact resistance was suppressed sufficiently below sample's spreading resistance by pressing the probe into the sample with ∼mN contact force and applying a large sample/probe forward bias voltage (V s ), which was understood by analyzing current-voltage (I-V) involving a serially connected insulating top layer with underlying spreading resistance. The carrier concentration as deduced from the resistance measurement, using a single mobility value, is consistent with Hall measurement with a standard deviation of 14% based on a set of MBE films with carrier concentrations in the range of 10 15 –10 16 /cm 3 . The doping polarity was readily identified by flipping V s polarity, where the resistance with reverse V s is orders of magnitude larger than forward V s . While focusing on the SSRM technique validation, we also show an example on an As-doped Cd(Se,Te) polycrystalline thin film of a high-performance CdTe solar cell, which illustrates the local resistance nonuniformity with up to two orders of magnitude differences, indicating if local mobility is roughly constant, local carrier concentration can have significant nonuniformity.

14 SOLAR ENERGY↗
DOE OSTI2025

First indirectly driven liquid-DT filled double shell implosions at the National Ignition Facility

Double shell implosions aim to explore material mixing under fusion conditions in a volume burn geometry using high-Z metal pushers. High-Z pushers are more compressible than low-Z pushers enabling high stagnation pressure which reduces the required implosion speed while maintaining a low pusher adiabat despite strong shock heating. Additionally, the use of a small fuel mass reduces the fuel internal energy required for ignition, thus achieving stable platforms with reasonable fusion output to conduct controlled experiments. These factors make volume burn in a double shell implosion highly promising. Recently, a series of liquid-DT filled, indirectly driven, double shell implosions were conducted at the National Ignition Facility with laser drives reaching up to 1.5 MJ. These experiments achieved a maximum DT neutron yield of 1.67 × 10 14 (yield—479 J), DT ion temperature of 2.6 keV, fuel areal density (ρR) of 0.15 g/cm 2 , and stagnation pressure of 79 Gbar. Over the course of these shots, the DT neutron yield has increased by an order of magnitude largely from improved mitigation of outer shell assembly joint driven instability growth using thicker gold plating at the assembly joint. Further performance improvements are expected by enhancing outer-to-inner shell kinetic energy transfer and refined mitigation of degradations from engineering features such as the outer shell joint, fill tube, and surface roughness.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Detailed characterization of runaway electron driven whistler waves in low-density DIII-D discharges

RE-driven whistler waves during quiescent DIII-D shots have been investigated further. The waves are confirmed to be mostly perpendicularly propagating and are observed for the first time with frequencies up to 700 MHz. Phase-spectral analysis has been used to infer their toroidal mode numbers, n, which are expected to scale with the wavenumber, k, of the mode. Though we derive a theoretical scaling of k ≈ 4n, the measured mode numbers are found to exhibit a very weak dependence on k. In addition, increases in synchrotron emission have been found to consistently lag whistler wave bursts by roughly 3–5 ms, suggesting the waves are causing pitch-angle scattering, since the emitted synchrotron radiation is a strong function of the REs' perpendicular energy. The stronger the wave bursts, the greater the subsequent increase in synchrotron emission. A predator-prey model is used to describe these nonlinear wave-particle interactions, from which the wave damping rates and the loss parameter can be inferred. The damping rates are found to be of the order of (1.6 ± 0.8) × 10 4 /s, and the unitless loss parameter is found to be approximately 2, suggesting that the loss mechanism is diffusive. These observations will serve to validate models of RE-driven waves in tokamak plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Rotation of electrothermal-instability-driven overheating structure due to helically oriented surface magnetic field on a high-current-density aluminum rod

Experiments on the 1-MA, 100-ns-rise-time Mykonos Facility demonstrate rotation of electrothermal instability (ETI)-driven overheating structure on 1.00-mm-diameter, 10-nm-surface roughness, 99.999%-pure aluminum rods, which are pulsed with helically polarized surface magnetic field. Rods are machined to include pairs of 10-micron-scale quasi-hemispherical voids or “engineered defects (ED)” which provide the dominant current density perturbation from which ETI grows most rapidly. Experiments include an axial magnetic field component through the addition of a helically wound return-current electrode or “helical return can (HRC).” For a given HRC design, azimuthal field (B ɵ ) and axial field (B z ) components rise at a prescribed and fixed ratio, driving an increasing magnetic field of constant polarization at the rod's surface; most experiments generated surface magnetic field at a 15-degree field polarization angle (from horizontal) defined as ɸ B = arctan(B z /B ɵ ). ETI-driven emission patterns from individual ED are observed to rotate along ɸ B , while emission patterns from dielectric-coated ED pairs are shown to elongate and preferentially merge along ɸ B , in qualitative agreement with 3D-magnetohydrodynamic simulations. These data strongly support that for a randomized distribution of current density perturbations on a high-current density conductor, nearby perturbations will favorably merge about ɸ B , with the degree of merging increasing with current. Such observations offer fundamental new understanding of the seeding mechanisms of the helical magneto-Rayleigh Taylor (MRT) instabilities observed from axially magnetized magnetically driven imploding liners.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Prediction of vacancy defect diffusion paths in high entropy alloys via machine learning on molecular dynamics data

Identifying the diffusion path of point defects is a critical step in understanding their evolution and the mechanisms of related phenomena. Defect diffusion occurs at small length and time scales, with impacts on material properties that may continue to evolve over ns to μs, ms, and the continuum scale (s, min, etc., and cm, m, etc.). The time scale accessible to molecular dynamics (MD) simulations is limited by small step sizes, typically in the fs range. Thus, surrogate models of MD simulations through machine learning (ML)-based algorithms are of great interest, especially for complex systems such as high entropy alloys (HEAs). In this work, dynamics governing vacancy migration in HEA were approximated with graph convolutional network (GCN) models as ansatzes for kinetic Monte Carlo (KMC) rate catalogs. Network design considered that diffusion in crystalline solids generally depends on interactions between defects and their immediate neighbor atoms. Graphs represented the vacancy surroundings, MD-generated trajectories provided training and comparison datasets, and unsupervised GCN models approximated interatomic dynamics governing vacancy migration in HEAs as ansatzes for KMC. A proof-of-concept model trained on MD data for the Fe, Ni, Cr, Co, and Cu HEA environment was used with two different neighbor interactions to assess the feasibility of training a GCN to predict vacancy defect transition rates in the HEA environment. The resulting setup rapidly generated MD-formatted synthetic trajectories based on dynamics learned from the MD training set, with a time acceleration of roughly two orders of magnitude and a similar diffusion coefficient to MD observations. Additionally, Nudged Elastic Band (NEB) calculations were performed on randomly generated FeNiCrCoCu HEA structures to determine vacancy migration barriers across nearest-neighbor sites. Transition probabilities for each jump, categorized by atomic type, were extracted from these calculations. NEB-based and GCN-based approaches led to similar outcomes.

Reimer, C↗