Topics: Applied Physics, Chemistry, Physics, Plasma, Research
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 the 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.
Simplification of plasma chemistry by means of vital nodes identification
Bowen Sun, Dingxin Liu, Yifan Liu, Santu Luo, Mingyan Zhang, Jishen Zhang, Aijun Yang, Xiaohua Wang, and Mingzhe Rong, Journal of Applied Physics