• 文献标题:   Enhancement of CO adsorption energy on defective graphene-supported Cu13 cluster and prediction with an induction energy model
  • 文献类型:   Article
  • 作  者:   GAO DL, RAO SY, LI YR, LIU NG, WANG DY
  • 作者关键词:   co adsorption, adsorption enhancement, defective graphenesupported cu 13 cluster, ab initio molecular dynamic, induction energy model
  • 出版物名称:   APPLIED SURFACE SCIENCE
  • ISSN:   0169-4332 EI 1873-5584
  • 通讯作者地址:  
  • 被引频次:   0
  • DOI:   10.1016/j.apsusc.2023.156368 EA JAN 2023
  • 出版年:   2023

▎ 摘  要

The adsorption of CO on Cu13 and defective graphene-supported Cu13 clusters is investigated using ab initio molecular dynamics methods. The results show that the CO adsorption energies on the defective graphenesupported Cu13 cluster are substantially enhanced compared to those on the Cu13 cluster. Furthermore, the average adsorption energy on the defective graphene-supported Cu13 cluster is significantly increased by 155% compared with the experimental one on pristine Cu surfaces, indicating that the defective graphene-supported Cu13 cluster can be an excellent catalyst for CO adsorption. The enhancement of the adsorption energies can be qualitatively explained in terms of the crystal orbital Hamilton population, that is, as the bond interaction increases, the adsorption energy increases. We propose an induction energy model to calculate the amount of the adsorption energy enhancement. The predicted adsorption energies on the defective graphene-supported Cu13 clusters are in quantitative agreement with those obtained from ab initio molecular dynamics simulations. The current study provides insights into designing highly active catalysts for CO adsorption.