The stability of low-index platinum surfaces and their electronic properties is investigated with density functional theory, toward the goal of understanding the surface structure and electron emission, and identifying precursors to electrical breakdown, on nonideal platinum surfaces. Propensity for electron emission can be related to a local work function, which, in turn, is intimately dependent on the local surface structure. The (1×N) missing row reconstruction of the Pt(110) surface is systematically examined. The (1×3) missing row reconstruction is found to be the lowest in energy, with the (1×2) and (1×4) slightly less stable. In the limit of large (1×N) with wider (111) nanoterraces, the energy accurately approaches the asymptotic limit of the infinite Pt(111) surface. This suggests a local energetic stability of narrow (111) nanoterraces on free Pt surfaces that could be a common structural feature in the complex surface morphologies, leading to work functions consistent with those on thermally grown Pt substrates.
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.
Helium is frequently used as a working medium for the generation of plasmas and is capable of energetic photon emissions. These energetic photon emissions are often attributed to the formation of helium excimer and subsequent photon emission. When the plasma device is exposed to another gas, such as nitrogen, this energetic photon emission can cause photoionization and further ionization wave penetration into the additional gas. Often ignored are the helium resonance emissions that are assumed to be radiation trapped and therefore not pertinent to photoionization. Here, experimental evidence for the presence of helium atomic emission in a pulsed discharge at ten's of Torr is shown. Simulations of a discharge in similar conditions agree with the experimental measurements. In this context, the role of atomic and molecular helium light emission on photoionization of molecular nitrogen in an ionization wave is studied using a kinetic modeling approach that accounts for radiation dynamics in a developing low-temperature plasma. Three different mixtures of helium at a total pressure of 250 Torr are studied in simulation. Photoionization of the nitrogen molecule by vacuum ultraviolet helium emission is used as the only seed source ahead of the ionization front. It is found that even though radiation trapped, the atomic helium emission lines are the significant source of photoionization of nitrogen. The significant effect of radiation trapped photon emission on ionization wave dynamics demonstrates the need to consider these radiation dynamics in plasma reactors where self-absorbed radiation is ignored.
This paper presents a new method for modeling rarefied gas flows based on hybridization of direct simulation Monte Carlo (DSMC) and discrete velocity method (DVM)-based quasi-particle representations of the velocity distribution function. It is aimed at improving the resolution of the tails of the distribution function (compared with DSMC) and computational efficiency (compared with DVM). Details of the method, such as the collision algorithm and the particle merging scheme, are discussed. The hybrid approach is applied to the study of noise in a Maxwellian distribution, computation of electron-impact ionization rate coefficient, as well as numerical simulation of a supersonic Couette flow. The hybrid-based solver is compared with pure DSMC and DVM approaches in terms of accuracy, computational speed, and memory use. It is shown that such a hybrid approach can provide a lower computational cost than a pure DVM approach, while being able to retain accuracy in modeling high-velocity tails of the distribution function. For problems where trace species have a significant impact on the flow physics, the proposed method is shown to be capable of providing better computational efficiency and accuracy compared with standard fixed-weight DSMC.
A novel method based on combining Direct Simulation Monte Carlo (DSMC) and Discrete Velocity Method (DVM) representations of the velocity distribution functions in velocity space is applied to rarefied ionized gas flows in order to study its efficiency and accuracy. The objective is to improve the efficiency of modeling of flows where trace populations have a significant effect on the flow physics. Numerical results are obtained for a 0-dimensional flow of a Ar/Ar+ /e− mixture and compared with the BOLSIG+ solver.
For high voltage electrical devices, prevention of high voltage breakdown is critical for device function. Use of polymeric encapsulation such as epoxies is common, but these may include air bubbles or other voids of varying size. The present work aimed to model and experimentally determine the size dependence of breakdown voltage for voids in an epoxy matrix, as a step toward establishing size criteria for void screening. Effects were investigated experimentally for both one-dimensional metal/epoxy/air/epoxy/metal gap sizes from 50 μm to 10 mm, as well as spherical voids of 250 μm, 500 μm, 1 mm and 2 mm sizes. These experimental results were compared to modified Paschen curve and particle-in-cell discharge models; minimum breakdown voltages of 6 - 8.5 kV appeared to be predicted by 1D models and experiments, with minimum breakdown voltage for void sizes of 0.2 - 1 mm. In a limited set of 3D experiments on 250 μm, 500 μm, 1 mm and 2 mm voids within epoxy, the minimum breakdown voltages observed were 18.5 - 20 kV, for 500 μm void sizes. These experiments and models are aimed at providing initial size and voltage criteria for tolerable void sizes and expected discharge voltages to support design of encapsulated high voltage components.
In the present research, a new method for simulation of rarefied gas flows is proposed, a velocity-space hybrid of both a DSMC representation of particles and a discrete velocity quasi-particle representation of the distribution function. The hybridization scheme is discussed in detail, and is numerically verified for two test-cases: the BKW relaxation problem and a stationary Maxwellian distribution. It is demonstrated that such a velocity-space hybridization can provide computational benefits when compared to a pure discrete velocity method or pure DSMC approach, while retaining some of the more attractive properties of discrete velocity methods. Further possible improvements to the velocity-space hybrid approach are discussed.
3D Particle-In-Cell Direct Simulation Monte Carlo (PIC-DSMC) simulations of cm-sized devices cannot resolve atomic-scale (nm) surface features and thus one must generate micron-scale models for an effective “local” work function, field enhancement factor, and emission area. Here we report on development of a stochastic effective model based on atomic-scale characterization of as-built electrode surfaces. Representative probability density distributions of the work function and geometric field enhancement factor (beta) for a sputter-deposited Pt surface are generated from atomic-scale surface characterization using Scanning Tunneling Microscopy (STM), Atomic Force Microscopy (AFM), and Photoemission Electron Microscopy (PEEM). In the micron-scale model every simulated PIC-DSMC surface element draws work functions and betas for many independent “atomic emitters”. During the simulation the field emitted current from an element is computed by summing each “atomic emitter's” current. This model has reasonable agreement with measured micron-scale emitted currents across a range of electric field values.
The purpose of this paper is to characterize the need for improved predictive capabilities in low-temperature plasma (LTP) science, and to identify possible means of accomplishing this. While these means may constitute an initiative of their own, we consider these ideas to have widespread importance to discovery plasma science. Therefore, it is our hope that these ideas are more generally incorporated in future work.
