| Search for adsorption geometry of precursor on surface using genetic algorithm: MoO2Cl2 on SiO2 surface |
| Jason Kim1, Jun-Young Jo2, In-Gyu Choi2, Yeong-Cheol Kim2 |
1Department of Creative IT Engineering , Pohang University of Science and Technology (POSTECH) , Pohang , Gyeongbuk , Republic of Korea
2School of Energy Materials and Chemical Engineering , Korea University of Technology and Education (KoreaTech) , Cheonan , Chungnam , Republic of Korea |
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Received: May 13, 2020; Revised: August 17, 2020 Accepted: August 20, 2020. Published online: November 30, 2020. |
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| ABSTRACT |
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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 confi gured 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 fi nding appropriate adsorption geometries of other types of precursors and surfaces. |
| Key words:
Atomic layer deposition · Precursor adsorption · Surface reaction · Genetic algorithm · Density functional theory |
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