Simplification of plasma chemistry by means of vital nodes identification

等离子体化学 等离子体 钥匙(锁) 鉴定(生物学) 化学 化学反应 反应中间体 化学种类 生产(经济) 生化工程 纳米技术 计算机科学 材料科学 物理 有机化学 生态学 生物 计算机安全 宏观经济学 量子力学 工程类 经济 催化作用
作者
Bowen Sun,Dingxin Liu,Yifan Liu,Santu Luo,Mingyan Zhang,Jishen Zhang,Aijun Yang,Xiaohua Wang,Mingzhe Rong
出处
期刊:Journal of Applied Physics [American Institute of Physics]
卷期号:130 (9) 被引量:3
标识
DOI:10.1063/5.0063068
摘要

Cold atmospheric plasmas have great application potential due to their production of diverse types of reactive species, so understanding the production mechanism and then improving the production efficiency of the key reactive species are very important. However, plasma chemistry typically comprises a complex network of chemical species and reactions, which greatly hinders identification of the main production/reduction reactions of the reactive species. Previous studies have identified the main reactions of some plasmas via human experience, but since plasma chemistry is sensitive to discharge conditions, which are much different for different plasmas, widespread application of the experience-dependent method is difficult. In this paper, a method based on graph theory, namely, vital nodes identification, is used for the simplification of plasma chemistry in two ways: (1) holistically identifying the main reactions for all the key reactive species and (2) extracting the main reactions relevant to one key reactive species of interest. This simplification is applied to He + air plasma as a representative, chemically complex plasma, which contains 59 species and 866 chemical reactions, as reported previously. Simplified global models are then developed with the key reactive species and main reactions, and the simulation results are compared with those of the full global model, in which all species and reactions are incorporated. It was found that this simplification reduces the number of reactions by a factor of 8–20 while providing simulation results of the simplified global models, i.e., densities of the key reactive species, which are within a factor of two of the full global model. This finding suggests that the vital nodes identification method can capture the main chemical profile from a chemically complex plasma while greatly reducing the computational load for simulation.
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