Macroscopic visualization for statistics and microscopic identification of species roles in web-like plasma-enhanced chemical networks

Weakly-ionized plasma has multiple complexities in various phase spaces of parameters. One of the phase spaces it possesses is a chemical reaction network. To investigate its structure and functions, we proposed a visualization method for complex networks of chemical reactions enhanced by high-energy electrons, based on theories of complex networks; a graph with nodes and edges is efficient for this purpose, where nodes are species like atoms, molecules, radicals, ions and electrons with edges bridging chemical agents and products [1]. To identify roles of species in the network, centrality indices like betweenness and closeness are good measures as microscopic viewers [1,2]. To survey macroscopic and statistical properties of the network, we made a histogram of statistical counting of species for a centrality-index distribution, and plasma-enhanced chemical networks exhibit a wide broadening of the distributions in contrast to cases of random graphs [2]. These facts suggest that web-like plasma enhanced chemical networks are well organized and well balanced to preserve reaction-network stabilities. [1] O. Sakai, K. Nobuto, S. Miyagi and K. Tachibana, AIP Advances 5, 107140 (2015). [2] Y. Mizui, T. Kojima, S. Miyagi and O. Sakai, Symmetry 9, 309 (2017).