Lattice oxygen self-spillover on reducible oxide supported metal cluster: The water-gas shift reaction on Cu/CeO2catalyst

Ya Qiong Su, Guang Jie Xia, Yanyang Qin, Shujiang Ding, Yang Gang Wang (Corresponding author)

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Abstract

In this work we have tackled one of the most challenging problems in nanocatalysis namely understanding the role of reducible oxide supports in metal catalyzed reactions. As a prototypical example, the very well-studied water gas shift reaction catalyzed by CeO2supported Cu nanoclusters is chosen to probe how the reducible oxide support modifies the catalyst structures, catalytically active sites and even the reaction mechanisms. By employing density functional theory calculations in conjunction with a genetic algorithm andab initiomolecular dynamics simulations, we have identified an unprecedented spillover of the surface lattice oxygen from the ceria support to the Cu cluster, which is rarely considered previously but may widely exist in oxide supported metal catalysts under realistic conditions. The oxygen spillover causes a highly energetic preference of the monolayered configuration of the supported Cu nanocluster, compared to multilayered configurations. Due to the strong metal-oxide interaction, after the O spillover the monolayered cluster is highly oxidized by transferring electrons to the Ce 4f orbitals. The water-gas-shift reaction is further found to more favorably take place on the supported copper monolayer than the copper-ceria periphery, where the on-site oxygen and the adjacent oxidized Cu sites account for the catalytically active sites, synergistically facilitating the water dissociation and the carboxyl formation. The present work provides mechanistic insights into the strong metal-support interaction and its role in catalytic reactions, which may pave a way towards the rational design of metal-oxide catalysts with promising stability, dispersion and catalytic activity.

Original languageEnglish
Pages (from-to)8260-8267
Number of pages8
JournalChemical Science
Volume12
Issue number23
DOIs
Publication statusPublished - 21 Jun 2021

Bibliographical note

Funding Information:
This work was financially supported by the NSFC (no. 22022504), Guangdong “Pearl River” Talent Plan (no. 2019QN01L353), Higher Education Innovation Strong School Project of Guangdong Province of China (2020KTSCX122) and Guangdong Provincial Key Laboratory of Catalysis (no. 2020B121201002). Y. Q. Su acknowledges the “Young Talent Support Plan” of Xi'an Jiaotong University. We acknowledge supercomputing facilities provided by the HPC Platform, Xi'an Jiaotong University, the Netherlands Organization for Scientific Research (NWO), and the Center for Computational Science and Engineering (SUSTech).

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