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Updated: Sep 9, 2025

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機械学習されたMACE-MPの原子間電位を用いたシリカのモデリング

Jamal Abdul Nasir1, Jingcheng Guan1, Woongkyu Jee1

  • 1Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, UK. c.r.a.catlow@ucl.ac.uk.

Physical chemistry chemical physics : PCCP
|September 2, 2025
PubMed
まとめ

機械学習のポテンシャルにより,シリカポリモルフとゼオライトを正確にモデル化し,相変化とフッ素イオンの振る舞いを予測します. これは,様々なシリカ材料のシミュレーションのためのMACEの機械学習の可能性の有効性を示しています.

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