Publications

Plasma etching of semiconductors is an essential process in the production of microchips which enable nearly every aspect of modern life. Two frequencies of applied voltage are often used to provide control of both the ion fluxes and energy distribution.

Structural disorder causes materials' surface electronic properties, e.g., work function (φ), to vary spatially, yet it is challenging to prove exact causal relationships to underlying ensemble disorder, e.g., roughness or granularity. For polycrystalline Pt, nanoscale resolution photoemission threshold mapping reveals a spatially varying φ = 5.70 ± 0.03 eV over a distribution of (111) vicinal grain surfaces prepared by sputter deposition and annealing. With regard to field emission and related phenomena, e.g., vacuum arc initiation, a salient feature of the φ distribution is that it is skewed with a long tail to values down to 5.4 eV, i.e., far below the mean, which is exponentially impactful to field emission via the Fowler-Nordheim relation. We show that the φ spatial variation and distribution can be explained by ensemble variations of granular tilts and surface slopes via a Smoluchowski smoothing model wherein local φ variations result from spatially varying densities of electric dipole moments, intrinsic to atomic steps, that locally modify φ. Atomic step-terrace structure is confirmed with scanning tunneling microscopy (STM) at several locations on our surfaces, and prior works showed STM evidence for atomic step dipoles at various metal surfaces. From our model, we find an atomic step edge dipole μ = 0.12 D/edge atom, which is comparable to values reported in studies that utilized other methods and materials. Our results elucidate a connection between macroscopic φ and the nanostructure that may contribute to the spread of reported φ for Pt and other surfaces and may be useful toward more complete descriptions of polycrystalline metals in the models of field emission and other related vacuum electronics phenomena, e.g., arc initiation.

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Plasma-based thermionic energy converters (TECs) feature non-equilibrium processes that are best modeled using fully kinetic simulations, and pose challenges in terms of length scales, time scales, and complex particle interactions. We present simulations of TECs using two particle-in-cell software packages which use modern high-performance computing to meet the simulation challenges. Using WarpX, we demonstrate the simulation of a triode plasma TEC. Using Aleph, we present simulations of an ignited cesium plasma TEC, including a large set of multi-step ionization processes. The Cs plasma simulations also demonstrate shortcomings of approximate models used historically.

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Particle-in-cell, direct simulation Monte Carlo simulations reveal that ion-acoustic instabilities excited in presheaths can cause significant ion heating. Ion-acoustic instabilities are excited by the ion flow toward a sheath when the neutral gas pressure is small enough and the electron temperature is large enough. A series of 1D simulations were conducted in which neutral plasma (electrons and ions) was uniformly sourced with an ion temperature of 0.026 eV and different electron temperatures (0.1 eV-50 eV). Ion heating was observed when the electron-to-ion temperature ratio exceeded the minimum value predicted by linear response theory to excite ion-acoustic instabilities at the sheath edge (T e / T i ≈ 28). When this threshold was exceeded, the temperature equilibration rate between ions and electrons rapidly increased near the sheath so that the local temperature ratio did not significantly exceed the threshold for instability. This resulted in significant ion heating near the sheath edge, which also extended back into the bulk plasma; presumably due to wave reflection from the sheath. This ion-acoustic wave heating mechanism was found to decrease for higher neutral pressures, where ion-neutral collisions damp the ion-acoustic waves and ion heating is instead dominated by inelastic collisions in the presheath.

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Understanding the role of physical processes contributing to breakdown is critical for many applications in which breakdown is undesirable, such as capacitors, and applications in which controlled breakdown is intended, such as plasma medicine, lightning protection, and materials processing. The electron emission from the cathode is a critical source of electrons which then undergo impact ionization to produce electrical breakdown. In this study, the role of secondary electron yields due to photons (γ ph) and ions (γ i) in direct current breakdown is investigated using a particle-in-cell direct simulation Monte Carlo model. The plasma studied is a one-dimensional discharge in 50 Torr of pure helium with a platinum cathode, gap size of 1.15 cm, and voltages of 1.2-1.8 kV. The current traces are compared with experimental measurements. Larger values of γ ph generally result in a faster breakdown, while larger values of γ i result in a larger maximum current. The 58.4 nm photons emitted from He(21P) are the primary source of electrons at the cathode before the cathode fall is developed. Of the values of γ ph and γ i investigated, those which provide the best agreement with the experimental current measurements are γ ph = 0.005 and γ i = 0.01. These values are significantly lower than those in the literature for pristine platinum or for a graphitic carbon film which we speculate may cover the platinum. This difference is in part due to the limitations of a one-dimensional model but may also indicate surface conditions and exposure to a plasma can have a significant effect on the secondary electron yields. The effects of applied voltage and the current produced by a UV diode which was used to initiate the discharge, are also discussed.

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This paper describes the verification and validation (V&V) framework developed for the stochastic Particle-in-Cell, Direct Simulation Monte Carlo code Aleph. An ideal framework for V&V from the viewpoint of the authors is described where a physics problem is defined, and relevant physics models and parameters to the defined problem are assessed and captured in a Phenomena Identification and Ranking Table (PIRT). Furthermore, numerous V&V examples guided by the PIRT for a simple gas discharge are shown to demonstrate the V&V process applied to a real-world simulation tool with the overall goal to demonstrably increase the confidence in the results for the simulation tool and its predictive capability. Although many examples are provided here to demonstrate elements of the framework, the primary goal of this work is to introduce this framework and not to provide a fully complete implementation, which would be a much longer document. Comparisons and contrasts are made to more usual approaches to V&V, and techniques new to the low-temperature plasma community are introduced. Specific challenges relating to the sufficiency of available data (e.g., cross sections), the limits of ad hoc validation approaches, the additional difficulty of utilizing a stochastic simulation tool, and the extreme cost of formal validation are discussed.

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Technologies based on non-equilibrium, low-temperature plasmas are ubiquitous in today’s society. Plasma modeling plays an essential role in their understanding, development and optimization. An accurate description of electron and ion collisions with neutrals and their transport is required to correctly describe plasma properties as a function of external parameters. LXCat is an open-access, web-based platform for storing, exchangig and manipulating data needed for modeling the electron and ion components of non-equilibrium, low-temperature plasmas. The data types supported by LXCat are electron- and ion-scattering cross-sections with neutrals (total and differential), interaction potentials, oscillator strengths, and electron- and ion-swarm/transport parameters. Online tools allow users to identify and compare the data through plotting routines, and use the data to generate swarm parameters and reaction rates with the integrated electron Boltzmann solver. In this review, the historical evolution of the project and some perspectives on its future are discussed together with a tutorial review for using data from LXCat.