Abstract
Chemistry in plasma is complicated because it has so many reactions in parallel and in series. A complex network is suitable for the visualization and the analysis of its complexity. A numerical calculation based on hundreds of rate equations is a typical tool for plasma chemistry, but such a computational process does not clarify the undergoing physical and chemical properties that stabilize many industrial plasma processes for a number of applications. In this study, we focus on low-temperature plasma in which high-energy electrons are activators for chemical reactions, and investigate the origin of the stability by examining the statistical properties of networks for silane (\(\mathrm {SiH}_4\)) plasma. There is only one seed species in the initial space, \(\mathrm {SiH}_4\), which is surrounded by high-energy electrons. \(\mathrm {SiH}_4\) is decomposed into several fragments composed of Si and/or H atoms with possible charges, and such radical and ion species are decomposed or synthesized into other species, leading to the formation of temporal reaction networks in chemistry. With the effects of rate constants that determine chemical reaction rates, we create temporal networks and observe preferential attachments that induce a new reaction in a transient state. The centrality indices for participant species and degree distributions reveal what is occurring in this complex system, and during the sequential process we observe an exponential-tail degree distribution, which is a significant source of reaction stability.
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Acknowledgements
One of the authors (OS) thanks Prof. T. Murakami at Seikei University, Prof. M. J. Kushner at the University of Michigan, and Dr. S. Nunomura at National Institute of Advanced Industrial Science and Technology for their useful comments on this study. This work was partly supported by JSPS KAKENHI Grant Numbers JP18H03690 and JP18K18756.
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Mizui, Y., Miyagi, S., Sakai, O. (2021). Statistics of Growing Chemical Network Originating from One Molecule Species and Activated by Low-Temperature Plasma. In: Benito, R.M., Cherifi, C., Cherifi, H., Moro, E., Rocha, L.M., Sales-Pardo, M. (eds) Complex Networks & Their Applications IX. COMPLEX NETWORKS 2020 2020. Studies in Computational Intelligence, vol 944. Springer, Cham. https://doi.org/10.1007/978-3-030-65351-4_32
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