Statistical analysis of growing chemical reaction networks in low-temperature plasmas

Understanding the complex chemical reaction systems in low-temperature plasmas is important. Graph-theoretical network analysis is one of the most powerful tools to visualize the complexity of plasma chemistry [1]. We have visualized complex chemical reactions and reduced the dimensionality of reaction systems while maintaining the scale-free nature of the network topology. [2]. The growth mechanism of network may contain important features that stabilize the system. For example, the Barabási-Albert model [3] suggests two important factors: growth and preferential attachment (new nodes joining the network are more likely to attach to nodes with a higher number of link edges). In this study, we propose statistical analysis of the growing chemical reaction networks in low-temperature plasmas. The emphasis is on the statistical centrality of the network and the scale-free nature of the structure during the growth process. [1] T. Murakami and O. Sakai, Plasma Sources Sci. Technol. 29 (2020) 115018. [2] T. Minami, M. Tomita and T. Murakami, The 76^th Annual Gaseous Electronics Conference, Ann A rbor, USA, October, 2023. [3] A.- L. Barabási, R.Albert, and H. Jeong, Physica A, 272 (1999) 173