4.8 Article

Non-Noble Metal Incorporated Transition Metal Dichalcogenide Monolayers for Electrochemical CO2 Reduction: A First-Principles Study

期刊

ACS APPLIED MATERIALS & INTERFACES
卷 15, 期 50, 页码 58388-58396

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acsami.3c13240

关键词

CO2 reduction reaction; metalsingle atomcatalysts; vacancy; transition metal dichalcogenides; strain engineering

向作者/读者索取更多资源

Using a combination of non-noble metal atoms and defect-engineered transition metal dichalcogenide (TMD) monolayers, new types of single-atom catalysts for electrochemical CO2RR can be designed, exhibiting better catalytic performance and selectivity. Applying suitable biaxial tensile strains on defect-engineered TMDs can significantly reduce the overpotentials of non-noble metal atoms, with the vacancy defects and charge transfer playing a crucial role in improving catalytic activity.
Using non-noble metal atoms as catalysts is attractive for decreasing the cost of the CO2 reduction reaction (CO2RR). By screening first-row transition metals and noble metals through extensive first-principles calculations, non-noble Sc and Ti single atoms binding on vacancy-defected transition metal dichalcogenide (TMD) monolayers exhibit better catalytic performance and selectivity for electrochemical CO2RR than noble metal single atoms. The overpotentials of Sc and Ti atoms for the CO2RR can be reduced lower than 0.09 V after applying suitable biaxial tensile strains on vacancy-defected TMDs, which are approximately 1 order of magnitude lower than that of most reported metal atom catalysts. The vacancy defects of TMDs and charge transfer to metal atoms induced by tensile strain play a key role in improving the catalytic activity of non-noble metal single atoms. These results highlight a possible way to design new single atom catalysts for electrochemical CO2RR by utilizing the combination of non-noble metal atoms, defected TMDs, and strain engineering.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据