Analysis of Visualized Complex Reaction Network in Low- Temperature Molecular Plasma

It is quite frequent that a factorial fabrication process includes very complex systems, leading to difficulties in its regulation, estimation and prediction. To overcome these difficulties, causality in the complex systems is a key issue, which has not been frequently stressed but is of importance for effective performance of machine learning. One of the examples with such complexity is plasma and its chemistry, where they are in processes of dry etching and plasma chemical vapor deposition. So far, we successfully visualized the complexities using graphs or networks, where nodes represent elements and edges imply interactions between them. In this study, focusing on silane (SiH4) and methane (CH4) low-temperature molecular plasma chemistry, we clarify roles of species in the chemical reaction network, like reactants, intermediates and products, where a species is a node in this species network and a reactant-product pair is an edge. This distinction is straightforward for selection of reactants as input and products as output variables. We also show and discuss another network, reaction network, in which a reactant-product pair is an edge and its size is so huge that its network statistics is categorized by complex network science. By visualizing and analyzing a complex chemical reaction network in molecular plasma, we obtain useful information for parameter regulation in real processes and also identification of input/output variables for machine learning of a given process.