In Operando Identification of In Situ Formed Metalloid Zincδ+ Active Sites for Highly Efficient Electrocatalyzed Carbon Dioxide Reduction. (9th May 2022)

• Record Type: Journal Article
• Authors: Zhang, Xin Yu; Li, Wen Jing; Chen, Jiacheng; Wu, Xue Feng; Liu, Yuan Wei; Mao, Fangxin; Yuan, Hai Yang; Zhu, Minghui; Dai, Sheng; Wang, Hai Feng; Hu, P.; Sun, Chenghua; Liu, Peng Fei; Yang, Hua Gui
• Is Part Of: Angewandte Chemie. Volume 134:Number 28(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-05-09
• Subjects: CO2 Reduction Reaction -- EA Global Optimization Method -- Metalloid Znδ+ -- Operando EXAFS -- Zinc Pyrophosphate; Chemistry -- Periodicals; 540
• DOI: 10.1002/ange.202202298
• Languages: English
• ISSNs: 0044-8249

Abstract

Abstract: Electrochemical CO2 ‐to‐CO conversion provides a possible way to address problems associated with the greenhouse effect; however, developing low‐cost electrocatalysts to mediate high‐efficiency CO2 reduction remains a challenge on account of the limited understanding of the nature of the real active sites. Herein, we reveal the Zn δ+ metalloid sites as the real active sites of stable nonstoichiometric ZnO x structure derived from Zn2 P2 O7 through operando X‐ray absorption fine structure analysis in conjunction with evolutionary‐algorithm‐based global optimization. Furthermore, theoretical and experimental results demonstrated that Zn δ+ metalloid active sites could facilitate the activation of CO2 and the hydrogenation of *CO2, thus accelerating the CO2 ‐to‐CO conversion. Our work establishes a critical fundamental understanding of the origin of the real active center in the zinc‐based electrocatalysts for CO2 reduction reaction. Abstract : In a zinc‐based electrocatalyst for CO2 reduction reaction, the Zn δ+ metalloid hollow sites of stable, nonstoichiometric ZnO x, derived from Zn2 P2 O7, were shown to be the real active site structures for CO2 ‐to‐CO conversion, demonstrated by structure characterizations through operando X‐ray absorption fine structure analysis in conjunction with evolutionary‐algorithm‐based global optimization.