[2C01-08] Surface Analysis/Applied Surface Science/Evaluation Technique (ASS)

10:15 AM - 10:30 AM JST(1:15 AM - 1:30 AM UTC)

[2C05] Exploration of potential reaction pathways of Rochow-Müller process using Machine-Learning-based potential

*Tanudji Jeffrey¹, Michio Okada^1,2, Tomohiko Nakamura³, Yuji Kobayashi³, Tetsuya Inukai³ (1. Institute of Radiation Sciences, The University of Osaka (Japan), 2. Graduate School of Science, The University of Osaka (Japan), 3. Shin-Etsu Chemical Co. Ltd. (Japan))

The Rochow-Müller process, also known as the direct synthesis, is an important method for producing silicone. However, the complex reaction processes mean the pathway is still not fully understood. Using machine-learning based (ML) potential derived from density functional theory (DFT), we attempt to explore the reaction pathways in order to understand any possible branching as well as the energy required for the reaction processes. These configurations will then be calculated independently with DFT to find out the differences between the ML model and DFT calculations.

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