Your browser doesn't support javascript.
loading
Programmable kernel structures of atomically precise metal nanoclusters for tailoring catalytic properties.
Li, Ya-Hui; Zhao, Shu-Na; Zang, Shuang-Quan.
Afiliação
  • Li YH; Henan Key Laboratory of Crystalline Molecular Functional Material, Henan International Joint Laboratory of Tumor Theranostical Cluster Materials, Green Catalysis Center and College of Chemistry Zhengzhou University Zhengzhou P. R. China.
  • Zhao SN; Henan Key Laboratory of Crystalline Molecular Functional Material, Henan International Joint Laboratory of Tumor Theranostical Cluster Materials, Green Catalysis Center and College of Chemistry Zhengzhou University Zhengzhou P. R. China.
  • Zang SQ; Henan Key Laboratory of Crystalline Molecular Functional Material, Henan International Joint Laboratory of Tumor Theranostical Cluster Materials, Green Catalysis Center and College of Chemistry Zhengzhou University Zhengzhou P. R. China.
Exploration (Beijing) ; 3(3): 20220005, 2023 Jun.
Article em En | MEDLINE | ID: mdl-37933377
The unclear structures and polydispersity of metal nanoparticles (NPs) seriously hamper the identification of the active sites and the construction of structure-reactivity relationships. Fortunately, ligand-protected metal nanoclusters (NCs) with atomically precise structures and monodispersity have become an ideal candidate for understanding the well-defined correlations between structure and catalytic property at an atomic level. The programmable kernel structures of atomically precise metal NCs provide a fantastic chance to modulate their size, shape, atomic arrangement, and electron state by the precise modulating of the number, type, and location of metal atoms. Thus, the special focus of this review highlights the most recent process in tailoring the catalytic activity and selectivity over metal NCs by precisely controlling their kernel structures. This review is expected to shed light on the in-depth understanding of metal NCs' kernel structures and reactivity relationships.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article