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理论预测促使合成用于CO还原的GDY负载InO量子点。

Theoretical Prediction Leads to Synthesize GDY Supported InO Quantum Dots for CO Reduction.

作者信息

He Feng, Chen Xi, Xue Yurui, Li Yuliang

机构信息

CAS Key Laboratory of Organic Solids, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, P. R. China.

University of Chinese Academy of Sciences, Beijing, 100190, P. R. China.

出版信息

Angew Chem Int Ed Engl. 2024 May 21;63(21):e202318080. doi: 10.1002/anie.202318080. Epub 2024 Apr 18.

DOI:10.1002/anie.202318080
PMID:38548702
Abstract

The preparation of formic acid by direct reduction of carbon dioxide is an important basis for the future chemical industry and is of great significance. Due to the serious shortage of highly active and selective electrocatalysts leading to the development of direct reduction of carbon dioxide is limited. Herein the target catalysts with high CORR activity and selectivity were identified by integrating DFT calculations and high-throughput screening and by using graphdiyne (GDY) supported metal oxides quantum dots (QDs) as the ideal model. It is theoretically predicted that GDY supported indium oxide QDs (i.e., InO/GDY) is a new heterostructure electrocatalyst candidate with optimal CORR performance. The interfacial electronic strong interactions effectively regulate the surface charge distribution of QDs and affect the adsorption/desorption behavior of HCOO* intermediate during CORR to achieve highly efficient CO conversion. Based on the predicted composition and structure, we synthesized the advanced catalytic system, and demonstrates superior CO-to-HCOOH conversion performance. The study presents an effective strategy for rational design of highly efficient heterostructure electrocatalysts to promote green chemical production.

摘要

通过二氧化碳直接还原制备甲酸是未来化学工业的重要基础,具有重要意义。由于高活性和选择性的电催化剂严重短缺,导致二氧化碳直接还原的发展受到限制。在此,通过结合密度泛函理论(DFT)计算和高通量筛选,并使用石墨炔(GDY)负载的金属氧化物量子点(QDs)作为理想模型,确定了具有高二氧化碳还原反应(CORR)活性和选择性的目标催化剂。理论预测表明,GDY负载的氧化铟量子点(即InO/GDY)是一种具有最佳CORR性能的新型异质结构电催化剂候选物。界面电子强相互作用有效地调节了量子点的表面电荷分布,并影响了CORR过程中HCOO*中间体的吸附/解吸行为,以实现高效的CO转化。基于预测的组成和结构,我们合成了先进的催化体系,并展示出优异的CO到HCOOH的转化性能。该研究为合理设计高效异质结构电催化剂以促进绿色化学生产提供了一种有效策略。

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