The Effects of Geometry on the Corona-to-Streamer Discharge Transition

The electric spark discharge has been studied for hundreds of years, yet many details of the phenomenon remain elusive. One particular area in the field of spark discharges that has yet to be explored in depth is the transition region between the corona and the streamer discharge. The parameters that characterize the transition region are purely geometric for a given potential difference applied between two electrodes. For the case of a point-to-plane electrode geometry, the transition between the oscillating corona discharge and the rapidly-growing streamer discharge is determined by the radius of curvature of the anode. In this contribution, the transition radius of curvature is found analytically using simplified models of each discharge and the principle of least action. For a sufficiently small anode, the corona discharge is also shown to be energetically more favorable at all radii of curvature, supporting the general claim that corona discharges are most readily produced on thin wires

The Effects of Geometry on the Corona-to-Streamer Discharge Transition

The electric spark discharge has been studied for hundreds of years, yet many details of the phenomenon remain elusive. One particular area in the field of spark discharges that has yet to be explored in depth is the transition region between the corona and the streamer discharge. The parameters that characterize the transition region are purely geometric for a given potential difference applied between two electrodes. For the case of a point-to-plane electrode geometry, the transition between the oscillating corona discharge and the rapidly-growing streamer discharge is determined by the radius of curvature of the anode. In this contribution, the transition radius of curvature is found analytically using simplified models of each discharge and the principle of least action. For a sufficiently small anode, the corona discharge is also shown to be energetically more favorable at all radii of curvature, supporting the general claim that corona discharges are most readily produced on thin wires

Molecular dynamics simulations of AR+ bombardment of Si with comparison to experiment

The authors present molecular dynamics (MD) simulations of energetic Ar+ ions (20–200 eV) interacting with initially crystalline silicon, with quantitative comparison to experiment. Ar+ bombardment creates a damaged or amorphous region at the surface, which reaches a steady-state thickness that is a function of the impacting ion energy. Real-time spectroscopic ellipsometry data of the same phenomenon match the MD simulation well, as do analogous SRIM simulations. They define positional order parameters that detect a sharp interface between the amorphous and crystalline regions. They discuss the formation of this interesting feature in the simulation, and show that it provides insight into some assumptions made in the analysis of experimental data obtained by interface-sensitive surface spectroscopy techniques

Molecular Dynamics for Low Temperature Plasma-Surface Interaction Studies

The mechanisms of physical and chemical interactions of low temperature plasmas with surfaces can be fruitfully explored using molecular dynamics (MD) simulations. MD simulations follow the detailed motion of sets of interacting atoms through integration of atomic equations of motion, using inter-atomic potentials that can account for bond breaking and formation that result when energetic species from the plasma impact surfaces. This article summarizes the current status of the technique for various applications of low temperature plasmas to material processing technologies. The method is reviewed, and commonly used inter-atomic potentials are described. Special attention is paid to the use of MD in understanding various representative applications, including tetrahedral amorphous carbon film deposition from energetic carbon ions; the interactions of radical species with amorphous hydrogenated silicon films; silicon nano-particles in plasmas; and plasma etching.Comment: Manuscript #271801, Accepted in J. Phys. D, November 10th, 200

Process Design and Economics for Biochemical Conversion of Lignocellulosic Biomass to Ethanol: Dilute-Acid Pretreatment and Enzymatic Hydrolysis of Corn Stover

This report describes one potential biochemical ethanol conversion process, conceptually based upon core conversion and process integration research at NREL. The overarching process design converts corn stover to ethanol by dilute-acid pretreatment, enzymatic saccharification, and co-fermentation. Building on design reports published in 2002 and 1999, NREL, together with the subcontractor Harris Group Inc., performed a complete review of the process design and economic model for the biomass-to-ethanol process. This update reflects NREL's current vision of the biochemical ethanol process and includes the latest research in the conversion areas (pretreatment, conditioning, saccharification, and fermentation), optimizations in product recovery, and our latest understanding of the ethanol plant's back end (wastewater and utilities). The conceptual design presented here reports ethanol production economics as determined by 2012 conversion targets and 'nth-plant' project costs and financing. For the biorefinery described here, processing 2,205 dry ton/day at 76% theoretical ethanol yield (79 gal/dry ton), the ethanol selling price is $2.15/gal in 2007$

Environmental and financial implications of ethanol as a bioethylene feedstock versus as a transportation fuel

Bulk chemicals production from biomass may compete with biofuels for low-cost and sustainable biomass sources. Understanding how alternative uses of biomass compare in terms of financial and environmental parameters is therefore necessary to help ensure that efficient uses of resources are encouraged by policy and undertaken by industry. In this paper, we compare the environmental and financial performance of using ethanol as a feedstock for bioethylene production or as a transport fuel in the US life cycle-based models are developed to isolate the relative impacts of these two ethanol uses and generate results that are applicable irrespective of ethanol production pathway. Ethanol use as a feedstock for bioethylene production or as a transport fuel leads to comparable greenhouse gas (GHG) emissions and fossil energy consumption reductions relative to their counterparts produced from fossil sources. By displacing gasoline use in vehicles, use of ethanol as a transport fuel is six times more effective in reducing petroleum energy use on a life cycle basis. In contrast, bioethylene predominately avoids consumption of natural gas. Considering 2013 US ethanol and ethylene market prices, our analysis shows that bioethylene is financially viable only if significant price premiums are realized over conventional ethylene, from 35% to 65% depending on the scale of bioethylene production considered (80 000 t yr−1 to 240 000 t yr−1). Ethanol use as a transportation fuel is therefore the preferred pathway considering financial,GHGemissions, and petroleum energy use metrics, although bioethylene production could have strategic value if demand-side limitations of ethanol transport fuel markets are reached

2022 Review of Data-Driven Plasma Science

Data-driven science and technology offer transformative tools and methods to science. This review article highlights the latest development and progress in the interdisciplinary field of data-driven plasma science (DDPS), i.e., plasma science whose progress is driven strongly by data and data analyses. Plasma is considered to be the most ubiquitous form of observable matter in the universe. Data associated with plasmas can, therefore, cover extremely large spatial and temporal scales, and often provide essential information for other scientific disciplines. Thanks to the latest technological developments, plasma experiments, observations, and computation now produce a large amount of data that can no longer be analyzed or interpreted manually. This trend now necessitates a highly sophisticated use of high-performance computers for data analyses, making artificial intelligence and machine learning vital components of DDPS. This article contains seven primary sections, in addition to the introduction and summary. Following an overview of fundamental data-driven science, five other sections cover widely studied topics of plasma science and technologies, i.e., basic plasma physics and laboratory experiments, magnetic confinement fusion, inertial confinement fusion and high-energy-density physics, space and astronomical plasmas, and plasma technologies for industrial and other applications. The final section before the summary discusses plasma-related databases that could significantly contribute to DDPS. Each primary section starts with a brief introduction to the topic, discusses the state-of-the-art developments in the use of data and/or data-scientific approaches, and presents the summary and outlook. Despite the recent impressive signs of progress, the DDPS is still in its infancy. This article attempts to offer a broad perspective on the development of this field and identify where further innovations are required