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Search for adsorption geometry of precursor on surface using genetic algorithm: MoO2Cl2 on SiO2 surface

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Abstract

We searched for appropriate adsorption geometries of a MoO2Cl2 precursor on a -H terminated β-SiO2 surface using genetic algorithm (GA). The adsorption geometries were configured by translating and rotating the precursor located near the surface. Six parameters decided the translation and rotation of the precursor along and around X, Y, and Z axes, and the six parameters were optimized by using the GA to search for energetically favorable adsorption geometries. For accurate and fast convergence of the GA, a dataset of adsorption geometry and the adsorption energy pairs was collected by grid search. Using this dataset, the hyper-parameters for the GA were optimized to search for the energetically favorable adsorption geometries. The GA found more energetically favorable adsorption geometries than the grid search with less computation time. The GA would be applicable to finding appropriate adsorption geometries of other types of precursors and surfaces.

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Acknowledgements

This paper was supported by Education and Research Promotion Program of KOREATECH in 2019. This paper was also supported by Korea Institute for Advancement of Technology (KIAT) Grant funded by the Korea Government (MOTIE) (P0008458, The Competency Development Program for Industry Specialist).

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Authors and Affiliations

  1. Department of Creative IT Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Gyeongbuk, Republic of Korea

    Jason Kim

  2. School of Energy Materials and Chemical Engineering, Korea University of Technology and Education (KoreaTech), Cheonan, Chungnam, Republic of Korea

    Jun-Young Jo, In-Gyu Choi & Yeong-Cheol Kim

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  1. Jason Kim
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  4. Yeong-Cheol Kim
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Correspondence to Yeong-Cheol Kim.

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Kim, J., Jo, JY., Choi, IG. et al. Search for adsorption geometry of precursor on surface using genetic algorithm: MoO2Cl2 on SiO2 surface. J. Korean Ceram. Soc. 57, 669–675 (2020). https://doi.org/10.1007/s43207-020-00079-0

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  • DOI: https://doi.org/10.1007/s43207-020-00079-0

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