| jh260078 |
Machine Learning-Driven Multi-Scale Simulations for Green Catalysis Design |
| 課題代表者 |
Yoshitada Morikawa(The University of Osaka)
Yoshitada Morikawa
(Graduate School of Engineering)
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| 概要 |
This research aims to develop Machine Learning Interatomic Potentials (MLIPs) integrated with multi-scale simulations to optimally design the heterogeneous catalysts, focusing on CO2 hydrogenation to methanol. The advantage is manifold due to the utilization of CO2 as green-house gas as well as the production of methanol as green energy resource.
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| 関連Webページ |
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| 報告書等 |
研究紹介ポスター
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最終報告書
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| 業績一覧 |
(1) 学術論文 （査読あり） |
| 該当なし |
| (2) 国際会議プロシーディングス （査読あり） |
| 該当なし |
| (3) 国際会議発表（査読なし） |
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Halim, H.; Fitriah, W. O. N.; Ramadhani, S.; Yamada, Y.; Anshor, M. F.; Sitiputa, P.; Ueda, R.; Muttaqien, F.; Morikawa, Y. "Active Sites Evolution in Cu Catalysts: Insights from Machine Learning Molecular Dynamics." 20th International Conference on Theoretical Aspects of Catalysis (ICTAC-20), Delft, The Netherlands, July 6, 2026. (Oral presentation).
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Anshor, M. F.; Halim, H. H.; Morikawa, Y. "CO Coadsorption Effect on Water-Gas Shift Reaction over Cu Clusters on Cu(111): Insights from Machine Learning Force Field and Microkinetic Modeling." 20th International Conference on Theoretical Aspects of Catalysis (ICTAC-20), Delft, The Netherlands, July 6–10, 2026. (Poster presentation).
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Halim, H. H. "Active Sites Evolution in Cu Catalysts: Insights from Machine Learning Molecular Dynamics." ACS Fall 2026, American Chemical Society National Meeting, Chicago, IL, USA, August 23–27, 2026. (Oral presentation).
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| (4) 国内会議発表（査読なし） |
| 該当なし |
| (5) 公開したライブラリなど |
| 該当なし |
| (6) その他（特許，プレスリリース，著書等） |
| 該当なし |
