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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Investigation of heat transport using directly driven gold spheres

Recently, heat transport was investigated using a directly driven beryllium sphere [Farmer et al., Phys. Plasmas 27, 082701 (2020)]. Models that overly restrict heat transport were rejected. This paper extends work to directly driven gold spheres where radiation loss is more important. Here, gold coated spheres are directly driven at the OMEGA laser facility at intensities of 5×10 14 W/cm 2 . Plasma conditions, laser coupling, and x-ray flux are all measured. Additionally, comparisons to 2D radiation-hydrodynamic simulations are performed. Simulations use three common heat transport models: local transport with flux limiters of f = 0.15 and f = 0.03, and the nonlocal Schurtz–Nicolai–Busquet (SNB) model. It is shown that both the SNB model and f = 0.15 match the measured plasma conditions with the SNB model better capturing the temporal evolution of electron temperature. The f = 0.03 model predicts too low of an electron density and too hot of a temperature. The measured scattered light is roughly 6% of the incident energy, the f = 0.15 and SNB models predict 0.5% uncoupled light, and f = 0.03, 38% uncoupled light. The x-ray fluxes in the f = 0.15 and SNB simulations rise too quickly and are just outside the measurement's error, while the x-ray flux in the f = 0.03 simulation is low by a factor of two-three. For these reasons, the f = 0.03 model is rejected.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Particle-in-cell Monte Carlo-collision modeling of non-ideal effects in wave-heated dense microplasmas

A computational model for non-ideal plasma effects during the time evolution of a second-stage laser-heated discharge at high pressures is presented. The model extends a classical one-dimensional particle-in-cell Monte Carlo-collision (PIC-MCC) approach coupled with Maxwell's equations for the laser-heating process of a xenon plasma at 300 K temperature and 10–100 bar pressure. Plasma non-ideality resulting from Coulomb coupling at high plasma densities is manifested as a depression in the effective ionization potential of atoms and enhanced collision cross sections. These non-ideal effects are represented using the Ecker–Kröll model in the context of the PIC-MCC approach. We find that full ionization of the plasma is obtained on the picosecond timescale, starting from the skin layer and quickly expanding throughout the domain through an anomalous extension of the skin depth. More critically, we show that the inclusion of the non-ideal plasma effects results in more rapid ionization compared to an ideal plasma, especially at higher pressures. The ionization delay reduction is of the order of a fraction of a picosecond, corresponding to a 16% decrease at 100 bar. As the amplitude of the wave field is lowered, the ionization rate is lowered, making the plasma non-ideality effects more prominent.

Solmaz, Evrim (ORCID:0000000211830881)↗
DOE OSTI2021

Comparing plasma conditions in short-pulse-heated foils via fine-structure x-ray emission

Fine-structure x-ray spectra have been measured from foils with embedded tracer layers at two laser facilities. In this work, a suite of layered foils with thin Ti tracers under varied tamper layers was studied at both the Titan and the ALEPH 400 nm laser facilities, where Ti Heα emission was recorded using a high-resolution Bragg crystal spectrometer. Several indicators of plasma parameters are examined in the spectra, including temperature- and density-dependent line ratios and line broadening from Stark and opacity effects. Spectra indicate that (1) the plasma density at ALEPH is significantly higher than at Titan and (2) the electron temperature is high for near-surface layers at both facilities but drops more quickly with depth at ALEPH. These inferences of plasma conditions are consistent with differing levels of temporal contrast at each laser facility.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Structural transitions of 4:1 methanol–ethanol mixture and silicone oil under high pressure

A 4:1 (volume ratio) methanol–ethanol (ME) mixture and silicone oil are two of the most widely used liquid pressure-transmitting media (PTM) in high-pressure studies. Their hydrostatic limits have been extensively studied using various methods; however, the evolution of the atomic structures associated with their emerging nonhydrostaticity remains unclear. Here, we monitor their structures as functions of pressure up to ∼30 GPa at room temperature using in situ high-pressure synchrotron x-ray diffraction (XRD), optical micro-Raman spectroscopy, and ruby fluorescence spectroscopy in a diamond anvil cell. No crystallization is observed for either PTM. The pressure dependence of the principal diffraction peak position and width indicates the existence of a glass transition in the 4:1 ME mixture at ∼12 GPa and in the silicone oil at ∼3 GPa, beyond which a pressure gradient emerges and grows quickly with pressure. There may be another liquid-to-liquid transition in the 4:1 ME mixture at ∼5 GPa and two more glass-to-glass transitions in the silicone oil at ∼10 GPa and ∼16 GPa. By contrast, Raman signals only show peak weakening and broadening for typical structural disordering, and Raman spectroscopy seems to be less sensitive than XRD in catching these structural transitions related to hydrostaticity variations in both PTM. These results uncover rich pressure-induced transitions in the two PTM and clarify their effects on hydrostaticity with direct structural evidence. The high-pressure XRD and Raman data on the two PTM obtained in this work could also be helpful in distinguishing between signals from samples and those from PTM in future high-pressure experiments.

Chen, Xiehang (ORCID:0000000168541506)↗
DOE OSTI2021

Nonradiative relaxation dynamics in the [Au 25- n Ag n (SH) 18 ] -1 ( n = 1, 12, 25) thiolate-protected nanoclusters

Evaluation of the electron-nuclear dynamics and relaxation mechanisms of gold and silver nanoclusters and their alloys is important for future photocatalytic, light harvesting, and photoluminescence applications of these systems. In this work, the effect of silver doping on the nonradiative excited state relaxation dynamics of the atomically precise thiolate-protected gold nanocluster [Au 25- n Ag n (SH) 18 ] –1 ( n = 1, 12, 25) is studied theoretically. Time-dependent density functional theory is used to study excited states lying in the energy range 0.0–2.5 eV. The fewest switches surface hopping method with decoherence correction was used to investigate the dynamics of these states. The HOMO–LUMO gap increases significantly upon doping of 12 silver atoms but decreases for the pure silver nanocluster. Doped clusters show a different response for ground state population increase lifetimes and excited state population decay times in comparison to the undoped system. The ground state recovery times of the S 1 –S 6 states in the first excited peak were found to be longer for [Au 13 Ag 12 (SH) 18 ] –1 than the corresponding recovery times of other studied nanoclusters, suggesting that this partially doped nanocluster is best for preserving electrons in an excited state. The decay time constants were in the range of 2.0–20 ps for the six lowest energy excited states. Among the higher excited states, S 7 has the slowest decay time constant although it occurs more quickly than S 1 decay. Overall, these clusters follow common decay time constant trends and relaxation mechanisms due to the similarities in their electronic structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Estimate of pre-thermal quench non-thermal electron density profile during Ar pellet shutdowns of low-density target plasmas in DIII-D

The radial density profile of pre-thermal quench (pre-TQ) early-time runaway electrons (REs) is estimated by combining electron cyclotron emission (ECE) and soft x-ray (SXR) data during rapid shutdown of low-density (n e ≲ 10 13 cm -3 ) DIII-D target plasmas with cryogenic argon pellet injection. This technique is limited in these experiments to the pre-TQ phase and quickly loses validity during the TQ. Two different cases are studied: a high (10 keV) temperature target and a lower (4 keV) temperature target. The results indicate that early-time, low-energy (~10 keV) REs form ahead of the argon pellet as it enters the plasma, affecting the pellet ablation rate; it is hypothesized that this may be caused by rapid cross-field transport of argon ions ahead of the pellet. Fokker-Planck modeling of the two shots suggests that the RE current is quite significant during the pre-TQ phase (up to 50% of the total current). Comparison between modeled pre-TQ RE current and post-TQ RE current inferred from avalanche theory suggests that RE current increases during the high temperature target TQ but decreases during the low temperature target TQ. Here, the uncertainties in this estimate are large; but, if true, this suggests that TQ loss of REs can be larger than previously estimated in DIII-D.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Effect of surface properties and polymer chain length on polymer adsorption in solution

In polymer nanoparticle composites (PNCs) with attractive interactions between nanoparticles (NPs) and polymers, a bound layer of the polymer forms on the NP surface, with significant effects on the macroscopic properties of the PNCs. The adsorption and wetting behaviors of polymer solutions in the presence of a solid surface are critical to the fabrication process of PNCs. In this study, we use both classical density functional theory (cDFT) and molecular dynamics (MD) simulations to study dilute and semi-dilute solutions of short polymer chains near a solid surface. Using cDFT, we calculate the equilibrium properties of polymer solutions near a flat surface while varying the solvent quality, surface–fluid interactions, and the polymer chain lengths to investigate their effects on the polymer adsorption and wetting transitions. Using MD simulations, we simulate polymer solutions near solid surfaces with three different curvatures (a flat surface and NPs with two radii) to study the static conformation of the polymer bound layer near the surface and the dynamic chain adsorption process. Additionally, we find that the bulk polymer concentration at which the wetting transition in the poor solvent system occurs is not affected by the difference in surface–fluid interactions; however, a threshold value of surface–fluid interaction is needed to observe the wetting transition. We also find that with good solvent, increasing the chain length or the difference in the surface–polymer interaction relative to the surface–solvent interaction increases the surface coverage of polymer segments and independent chains for all surface curvatures. Finally, we demonstrate that the polymer segmental adsorption times are heavily influenced only by the surface–fluid interactions, although polymers desorb more quickly from highly curved surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Description of longitudinal space charge effects in beams and plasma through dielectric permittivity

We develop a universal framework which allows quickly solve a wide class of problems for longitudinal space charge effects in beams and plasmas in cylindrical geometry. We introduce the longitudinal dielectric permittivity for the beam of charged particles, which describes its collective space charge response. The analysis yields an effective plasma frequency, which depends on the transverse geometry of the system. This dielectric permittivity mirrors the dielectric permittivity of plasma and matches the one dimensional (1D) expression once the transverse size of the beam is large. Several particle species can be included as additive terms describing susceptibility of each specie. The developed approach allows to study stability criteria for collective beam-beam and beam-plasma instabilities for arbitrary transverse distributions in particle densities.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Transient mixing behavior of a supercritical fluid injected into supercritical and subcritical environments

Transient, near-field mixing of a supercritical fluid injected into supercritical and subcritical environments is investigated experimentally. Fuel (propane) from a 100 μm diameter Bosch diesel injector is injected into a high-pressure test rig with a steady flow of heated, low-velocity nitrogen to control the ambient pressure and temperature. The fuel supply pressure is approximately 190 bar, allowing short injections lasting 3–4 ms to be performed in quick succession to acquire statistically significant datasets to represent the unsteady fuel–air mixing. Two test cases with the same ambient density and injector inlet pressure and temperature were chosen in an attempt to isolate effects of mixture phase behavior. Microscopic rainbow Schlieren deflectometry (RSD) is used for visualization and quantitative data acquisition. In the case of the supercritical ambient, the injector inlet and exit and ambient conditions are all supercritical. The RSD analysis reveals a mixing process similar to the single phase fluid mixing, though condensation is also observed locally, and can be explained by the adiabatic mixing theory presented in the paper. For the subcritical ambient case, the injector inlet is supercritical, but the injector exit and ambient conditions are both subcritical. The results show a rapid expansion in the near-field promoting mixing between propane and nitrogen. At downstream locations, significant condensation is also observed as predicted by the adiabatic mixing theory. As a result, the supercritical ambient case exhibited longer and narrower jet penetration compared to the subcritical ambient case.

02 PETROLEUM↗
DOE OSTI2022

Active meta-learning for predicting and selecting perovskite crystallization experiments

Autonomous experimentation systems use algorithms and data from prior experiments to select and perform new experiments in order to meet a specified objective. In most experimental chemistry situations, there is a limited set of prior historical data available, and acquiring new data may be expensive and time consuming, which places constraints on machine learning methods. Active learning methods prioritize new experiment selection by using machine learning model uncertainty and predicted outcomes. Meta-learning methods attempt to construct models that can learn quickly with a limited set of data for a new task. Here in this paper, we applied the model-agnostic meta-learning (MAML) model and the Probabilistic LATent model for Incorporating Priors and Uncertainty in few-Shot learning (PLATIPUS) approach, which extends MAML to active learning, to the problem of halide perovskite growth by inverse temperature crystallization. Using a dataset of 1870 reactions conducted using 19 different organoammonium lead iodide systems, we determined the optimal strategies for incorporating historical data into active and meta-learning models to predict reaction compositions that result in crystals. We then evaluated the best three algorithms (PLATIPUS and active-learning k-nearest neighbor and decision tree algorithms) with four new chemical systems in experimental laboratory tests. With a fixed budget of 20 experiments, PLATIPUS makes superior predictions of reaction outcomes compared to other active-learning algorithms and a random baseline.

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

Deterministic modeling of hybrid nonlinear effects in epsilon-near-zero thin films

In nonlinear optics, significant effort is concentrated on improving the strength and efficiency of interactions; however, experimentally investigating nonlinear materials is a complex, time-consuming, and costly investment. Moreover, it is often challenging to isolate, study, and optimize material parameters in an experiment due to complexities in the growth process. Recently, epsilon-near-zero materials have received a great deal of attention as promising nonlinear optical materials, but like many up-and-coming materials, the ability to explore and optimize their properties has been challenging. Here, we establish a framework to rapidly evaluate the performance of nonlinear epsilon-near-zero materials for both inter- and intraband effects in silico, requiring only an energy-momentum (E-k) diagram, linear optical properties, and experimental conditions. Measured nonlinear reflection and transmission in gallium-doped zinc oxide films are compared to the numerical framework for both intra- and interband excitation to verify accuracy across wavelength and irradiance while two figures of merit (FoMs) are introduced to quickly evaluate the performance of films without a full numerical framework. This capability is used to predict the performance of highly doped gallium nitride, cadmium oxide, zinc oxide, and indium tin oxide films, and efficient intra- and interband operation conditions are identified. Through this numerical framework and the FoMs, the exploration of unstudied epsilon-near-zero materials is enabled without the need for a nonlinear experiment, thereby accelerating the search for more efficient nonlinear materials and excitation conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Faster ablative Kelvin–Helmholtz instability growth in a magnetic field

Shear flows along a plasma interface will quickly grow unstable due to the Kelvin–Helmholtz instability. If there is a concurrent temperature gradient across the interface, higher modes are stabilized by the thermal diffusion. These ablative effects must be considered in, for example, jet features in inertial confinement fusion hot-spots, or plasma plumes in young supernovae. We show that magnetization of the plasma can greatly affect the instability, even if magnetic pressure is small. This is because electrons are localized by their gyromotion, reducing the heat flux and material ablation. We use a two-dimensional numerical extended-magnetohydrodynamics approach to assess this effect for dense fusion conditions. In comparison with the unmagnetized case, self-generated Biermann fields make only a minor difference to growth rates. However, simulations with a large 50 kT external field found that the growth rate of the least stable mode increased by 40%. In conclusion, this has implications for mix processes in Z-pinches and magnetized inertial confinement fusion concepts.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Kinetic simulations verifying reconnection rates measured in the laboratory, spanning the ion-coupled to near electron-only regimes

The rate of reconnection characterizes how quickly flux and mass can move into and out of the reconnection region. In the Terrestrial Reconnection EXperiment (TREX), the rate at which the antiparallel asymmetric reconnection occurs is modulated by the presence of a shock and a region of flux pileup in the high-density inflow. Simulations utilizing a generalized Harris-sheet geometry have tentatively shown agreement with TREX's measured reconnection rate scaling relative to system size, which is indicative of the transition from ion-coupled toward electron-only reconnection. Here, in this study, we present simulations tailored to reproduce the specific TREX geometry, which confirm both the reconnection rate scale and the shock jump conditions previously characterized experimentally in TREX. The simulations also establish an interplay between the reconnection layer and the Alfvénic expansions of the background plasma associated with the energization of the TREX drive coils; this interplay has not yet been experimentally observed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

A physics-constrained neural network for multiphase flows

The present study develops a physics-constrained neural network (PCNN) to predict sequential patterns and motions of multiphase flows (MPFs), which includes strong interactions among various fluid phases. To predict the order parameters, which locate individual phases in the future time, a neural network (NN) is applied to quickly infer the dynamics of the phases by encoding observations. The multiphase consistent and conservative boundedness mapping algorithm (MCBOM) is next implemented to correct the predicted order parameters. This enforces the predicted order parameters to strictly satisfy the mass conservation, the summation of the volume fractions of the phases to be unity, the consistency of reduction, and the boundedness of the order parameters. Then, the density of the fluid mixture is updated from the corrected order parameters. Finally, the velocity in the future time is predicted by another NN with the same network structure, but the conservation of momentum is included in the loss function to shrink the parameter space. The proposed PCNN for MPFs sequentially performs (NN)-(MCBOM)-(NN), which avoids nonphysical behaviors of the order parameters, accelerates the convergence, and requires fewer data to make predictions. Numerical experiments demonstrate that the proposed PCNN is capable of predicting MPFs effectively.

Mechanics↗
DOE OSTI2022

Strain- and thickness-dependent magnetic properties of epitaxial La 0.67 Sr 0.33 CoO 3 /La 0.67 Sr 0.33 MnO 3 bilayers

Magnetic properties and interfacial phenomena of epitaxial perovskite oxides depend sensitively on parameters such as film thickness and strain state. In this work, epitaxial La0 .67 Sr 0.33 CoO 3 (LSCO)/La 0.67 Sr 0.33 MnO 3 (LSMO) bilayers were grown on NdGaO 3 (NGO) and LaAlO 3 (LAO) substrates with a fixed LSMO thickness of 6 nm, and LSCO thickness (t LSCO ) varying from 2 to 10 nm. Soft x-ray magnetic spectroscopy revealed that magnetically active Co 2+ ions that strongly coupled to the LSMO layer were observed below a critical t LSCO for bilayers grown on both substrates. On LAO substrates, this critical thickness was 2 nm, above which the formation of Co 2+ ions was quickly suppressed leaving only a soft LSCO layer with mixed valence Co 3+ /Co 4+ ions. The magnetic properties of both LSCO and LSMO layers displayed strong t LSCO dependence. This critical t LSCO increased to 4 nm on NGO substrates, and the magnetic properties of only the LSCO layer displayed t LSCO dependence. A non-magnetic layer characterized by Co 3+ ions and with a thickness below 2 nm exists at the LSCO/substrate interface for both substrates. Therefore, the results contribute to the understanding of interfacial exchange spring behavior needed for applications in next generation spintronic and magnetic memory devices.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Can a deep-learning model make fast predictions of vacancy formation in diverse materials?

The presence of point defects, such as vacancies, plays an important role in materials design. Here, we explore the extrapolative power of a graph neural network (GNN) to predict vacancy formation energies. We show that a model trained only on perfect materials can also be used to predict vacancy formation energies (E vac ) of defect structures without the need for additional training data. Such GNN-based predictions are considerably faster than density functional theory (DFT) calculations and show potential as a quick pre-screening tool for defect systems. To test this strategy, we developed a DFT dataset of 530 E vac consisting of 3D elemental solids, alloys, oxides, semiconductors, and 2D monolayer materials. We analyzed and discussed the applicability of such direct and fast predictions. We applied the model to predict 192 494 E vac for 55 723 materials in the JARVIS-DFT database. Our work demonstrates how a GNN-model performs on unseen data.

2D materials↗
DOE OSTI2023

Optimization of transformer ratio and beam loading in a plasma wakefield accelerator with a structure-exploiting algorithm

Plasma-based acceleration has emerged as a promising candidate as an accelerator technology for a future linear collider or a next-generation light source. We consider the plasma wakefield accelerator (PWFA) concept where a plasma wave wake is excited by a particle beam and a trailing beam surfs on the wake. For a linear collider, the energy transfer efficiency from the drive beam to the wake and from the wake to the trailing beam must be large, while the emittance and energy spread of the trailing bunch must be preserved. One way to simultaneously achieve this when accelerating electrons is to use longitudinally shaped bunches and nonlinear wakes. In the linear regime, there is an analytical formalism to obtain the optimal shapes. In the nonlinear regime, however, the optimal shape of the driver to maximize the energy transfer efficiency cannot be precisely obtained because currently no theory describes the wake structure and excitation process for all degrees of nonlinearity. In addition, the ion channel radius is not well defined at the front of the wake where the plasma electrons are not fully blown out by the drive beam. We present results using a novel optimization method to effectively determine a current profile for the drive and trailing beam in PWFA that provides low energy spread, low emittance, and high acceleration efficiency. We parameterize the longitudinal beam current profile as a piecewise-linear function and define optimization objectives. For the trailing beam, the algorithm converges quickly to a nearly inverse trapezoidal trailing beam current profile similar to that predicted by the ultrarelativistic limit of the nonlinear wakefield theory. For the drive beam, the beam profile found by the optimization in the nonlinear regime that maximizes the transformer ratio also resembles that predicted by linear theory. Furthermore, the current profiles found from the optimization method provide higher transformer ratios compared with the linear ramp predicted by the relativistic limit of the nonlinear theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗