<学術雑誌論文>
Exploring Metal Cluster Catalysts Using Swarm Intelligence: Start with Hydrogen Adsorption

作成者
本文言語
出版者
発行日
収録物名
開始ページ
終了ページ
出版タイプ
アクセス権
権利関係
関連DOI
関連HDL
概要 The catalytic function of metal nanoclusters has attracted much attention because of their specific activity and selectivity. The structures of metal clusters are very diverse, especially when adsorba...tes are adsorbed on them. This is an obstacle when approaching metal nanocluster catalysts with computational chemistry. In this manuscript, a prescription for this problem is presented. With metal nanoclusters catalyzing reactions involving hydrogen in mind, a comprehensive, systematic, and efficient search for stable structures of metal nanoclusters with an adsorbed hydrogen atom is presented. This can be achieved through a good use of a supercomputer while using the particle swarm optimization algorithm and density functional theory together. In this attempt, three metallic elements, Fe, Ni, and Cu, are selected. When clustered, what kind of structure these elements form and how their affinity for hydrogen changes are detailed. Eventually, a path is presented to explore clusters that are actually useful as catalysts, using surface calculations as a reference.続きを見る

本文ファイル

pdf 7437556 pdf なし 1.05 MB 6  

詳細

PISSN
EISSN
NCID
レコードID
主題
タイプ
助成情報
登録日 2026.08.04
更新日 2026.08.05