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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Ten-moment fluid model for low-temperature magnetized plasmas

In this paper, a one-dimensional 10-moment multi-fluid plasma model is developed and applied to low-temperature magnetized plasmas. The 10-moment model solves for six anisotropic pressure terms, in addition to density and three components of fluid momentum, which allows the model to capture finite kinetic effects. The results are benchmarked against a 5-moment model, which assumes that the gas constituents follow a Maxwellian velocity distribution function (VDF), and a particle-in-cell Monte Carlo collision model that allows for arbitrary non-Maxwellian VDFs. The models are compared in a one-dimensional, low-temperature, partially magnetized plasma test case. The 10-moment results accurately reproduce the anisotropic temperature profile in low-temperature magnetized plasmas, where shear gradients exist due to the E×B drift. We discuss the mechanisms by which the anisotropic pressure can be generated in low-temperature magnetized plasmas. In addition, the importance of a self-consistent heat flux closure to the 10-moment model is studied, showing consistency with other models only when the assumptions of the underlying model are met. The 10-moment model allows for study of electron inertia effects and non-Maxwellian VDFs without the need for kinetic methods that are more computationally expensive.

Kuldinow, Derek Amur (ORCID:0000000319730196)↗
DOE OSTI2020

Kinetic effects of self-organization in low-temperature magnetized plasmas (Final Report for DE-SC0019045: 9/1/2018-8/31/2019)

The research goal of this Early Career Research Program project is to advance the science of low temperature magnetized plasmas using first-principles kinetic, e.g., solving the Boltzmann equation, models. A better understanding of the plasma transport properties, such as electrical resistivity and thermal conductivity must be obtained to better control and design magnetized plasma sources. A key physical phenomenon in low-temperature magnetized plasmas is the self-organization of plasma flows, e.g., coherent plasma structures and transition between different discharge modes. Understanding the physics of coherent plasma structures has been identified as one of the four important frontier topics in a recent workshop by the Office of Fusion Energy Science. These self-emerging plasma patterns results from the nonlinear coupling between plasma constituents (ions, electrons, and neutral atoms), electromagnetic fields, and materials. The physics of low-temperature magnetized plasmas is particularly complex because (i) the collisionless instabilities affect collisional phenomena (ionization, transport, etc.) and vice versa and (ii) the presence of materials (sheath, electron injection, etc.) influences the bulk plasma properties in low-temperature plasma (LTP) devices. Computational models of these plasma flows remain challenging because the plasma density can vary several orders of magnitudes, a wide range of temporal and spatial scales must be resolved, the phenomena are inherently three-dimensional, and various physical processes, such as wall interaction, instabilities, inelastic collisions, etc., must be simultaneously and self-consistently taken into account. Understanding the fundamental transport mechanisms in cross-field configurations enables additional controllability of plasma properties and electron energy distribution functions (EEDFs).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Nitridation of atomically smooth (111) diamond surfaces using a low temperature Penning plasma discharge

Diamond is a material with a wide band gap that can host a variety of isolated paramagnetic defects, called “color centers”1. These color centers have attractive optical and magnetic properties suitable for quantum applications including quantum computing, nanophotonics and quantum sensing. The most common one is the negatively charged nitrogen vacancy (NV) color center. For quantum sensing, it is desirable to reduce the distance between the NV center and the analyte by using shallow color centers in order to increase sensitivity. In this context, the diamond surface termination is especially critical. The appropriate surface termination is required to stabilize the color centers and mitigate surface magnetic noise. The nitrogen termination of diamond has been postulated as highly desirable for the NV color center. The goal of this project is to take advantage of an electron beam-generated ExB low temperature plasma developed by the Princeton Collaborative Low Temperature Plasma Research Facility (PCRF) at the Princeton Plasma Physics Laboratory (PPPL) to nitridate the surface of (100) diamond single crystals with minimal surface damage. In this reactor, the use of a magnetized plasma enables gentle processing of materials sensitive to ion damage. This is in strong contrast to radiofrequency plasma processing reactors which are known to etch and sputter the surface. XPS measurements indicate the incorporation of nitrogen and oxygen atoms at the surface in similar amounts. XAS measurements confirm the nitridation and indicate that the nitrogen termination is different from the nitrogen termination obtained using radiofrequency plasma treatment4. The combination of these results indicates the formation of amid species at the (100) diamond surface that are promising for the stabilization of NV centers for quantum sensing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Non-equilibrium low-temperature plasma-assisted combustion of iso-octane: Perturbing pyrolysis and oxidation kinetics

Here, in this study, a plasma-coupled flow reactor facility is used to examine the effects of non-equilibrium low-temperature plasmas on perturbing the pyrolysis and oxidation kinetics of iso-octane. Experiments were performed in highly dilute reactive mixtures of nitrogen, at near isothermal conditions for temperatures ranging from 523 K to 1203 K. Experiments cumulatively demonstrated enhanced chemical reactivity with the plasma for temperatures below 900 K, and a lowering of the hot-ignition temperature. Detailed kinetic insight was derived from a 0D plasma-coupled kinetic model, utilizing a constructed mechanism that combined both plasma-specific chemistry and the neutral combustion chemistry. For pyrolysis conditions, the model displayed relatively good agreement with fuel consumption and the formation of most intermediates compared to the experimental data, demonstrating the model is able to accurately predict primary radical formation from the plasma directly interacting with the fuel. Enhanced reactivity was attributed to collisional quenching of excited-states of N 2 with fuel, which led to efficient fuel fragmentation and enhancement of the H-radical flux. For oxidation conditions, the model displayed satisfactory agreement with the experiments. Model predictions were able to accurately predict fuel consumption and most intermediate speciation data for T > 800 K, but most discrepancies were towards T < 800 K in particular with oxygenated intermediates. In the presence of oxygen, plasma effects were predominantly spent on efficient enhancement of O- and H-radical fluxes, leading to further fuel fragmentation and initiation of both the OH- and HO 2 -radical pools. Subsequent reactivity of iso-octane was then dictated by the response of the temperature-dependent neutral chemistry. At low-temperatures (T = 643 K), enhanced fuel radicals and O 2 -additon chemistry lead to the formation of oxygenated species, while at intermediate temperatures (T = 843 K) net decrease in OH-radical reactivity led to an increase in hydrocarbon speciation. Near the self-ignition threshold (T = 1163 K), radicals generated by high-temperature branching reactions dominate the oxidation process and effectively ignition. This study ultimately demonstrated that the enhancement of radicals afforded by the plasma causes a deviation in known understanding of iso-octane kinetics in some regards and warrants future studies to reconcile these discrepancies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Deep potential molecular dynamics simulations of low-temperature plasma-surface interactions

Machine learning approaches to potential generation for molecular dynamics (MD) simulations of low-temperature plasma-surface interactions could greatly extend the range of chemical systems that can be modeled. Empirical potentials are difficult to generalize to complex combinations of multiple elements with interactions that might include covalent, ionic, and metallic bonds. This work demonstrates that a specific machine learning approach, Deep Potential Molecular Dynamics (DeepMD), can generate potentials that provide a good model of plasma etching in the Si-Cl-Ar system. Comparisons are made between MD results using DeepMD models and empirical potentials, as well as experimental measurements. Pure Si properties predicted by the DeepMD model are in reasonable agreement with experimental results. Simulations of Si bombardment by Ar + ions demonstrate the ability of the DeepMD method to predict sputtering yields as well as the depth of the amorphous-crystalline interface. Etch yields as a function of flux ratio and ion energy for simultaneous Cl 2 and Ar + impacts are in good agreement with previous simulation results and experiment. Predictions of etch yields and etch products during plasma-assisted atomic layer etching of Si-Cl 2 -Ar are shown to be in good agreement with MD predictions using empirical potentials and with experiment. Finally, good agreement was also seen with measurements for the spontaneous etching of Si by Cl atoms at 300 K. Further, the demonstration that DeepMD can reproduce results from MD simulations using empirical potentials is a necessary condition to future efforts to extend the method to a much wider range of systems for which empirical potentials may be difficult or impossible to obtain.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Data from "Deep Potential Molecular Dynamics Simulations of Low-Temperature Plasma-Surface Interactions"

Data and input files related to the paper "Deep Potential Molecular Dynamics Simulations of Low-Temperature Plasma-Surface Interactions" (https://doi.org/10.1116/6.0004027). This includes the final DP model used in all simulations, training data set, example input files to run DeepMD (with LAMMPS), and data tables summarizing the results obtained from the simulations.

machine learning models↗
DOE OSTI2024

Plasma-assisted surface modification of biopolymers

The interaction of non-thermal plasmas with surfaces is an important problem of interest in various applications. This work focuses on two main aspects of the problem - simulation and experiments. The development of a low-temperature plasma modeling is described along with experiments focusing on the interaction of a low-temperature plasma with liquid water. The simulation framework is capable of handling arbitrary geometries, chemistry and a fully-coupled boundary condition for plasma-dielectric interface. Representative examples for the verification and validation of the framework are provided. The experimental work deals with the study of low-temperature plasmas with water with the nitrate injection rate compared for three different configurations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Low-Temperature Plasma-Based Metrology of Lithium-Ion Battery Electrode Materials (CRADA Final Report)

As part of the Cyclotron Road program, SirenOpt Inc. evaluated its low-temperature plasma-based metrology sensor prototype for measuring multiple critical properties of lithium-ion battery electrode materials in parallel and in real-time. Cost-effective, minimal-waste manufacturing of high-performance battery electrode materials will be vital for achieving society’s net-zero carbon emission goals. Because existing electrode metrology sensors cannot operate within most sections of manufacturing lines, manufacturers often complete hundreds of processing steps before they can test their products and detect problems. When manufacturers perform these offline tests, they typically only test a small portion of the manufactured products. Current electrode manufacturing thus often yields many low-quality products, or off-spec products that must be thrown away all together. For example, at least 6% of the total lithium-ion battery manufacturing cost (i.e., over $250 million/year for the average gigafactory) is devoted to processing defective electrodes that are not scrapped until performance tests are failed during late-stage quality control checks. Electrode variability also leads manufacturers to build extra cells into battery packs to reduce the risk of poor performance. For example, many electric vehicle (EV) manufacturers include up to 10% more cells than needed, which substantially increases the cost and weight of the final EV product. The SirenOpt sensor can potentially enable early detection of poorly manufactured electrodes and allow them to be removed earlier from manufacturing lines, which can save battery manufacturers (hundreds of) millions of dollars per year. The sensor can further be used to improve product quality by accelerating R&D and process optimization, improving quality control, and enabling real-time process control. Overall, a real-time, in-situ metrology strategy can create unprecedented opportunities for implementation of smart manufacturing practices and advanced quality and process control solutions to realize higher battery electrode throughput and performance.

25 ENERGY STORAGE↗