Suppr超能文献

单原子催化剂用于CO电化学和光化学转化的理论研究进展

Recent progress of theoretical studies on electro- and photo-chemical conversion of CO with single-atom catalysts.

作者信息

Jiang Liyun, Yang Qingqing, Xia Zhaoming, Yu Xiaohu, Zhao Mengdie, Shi Qiping, Yu Qi

机构信息

School of Physics and Telecommunication Engineering, School of Materials Science and Engineering, Shaanxi Laboratory of Catalysis, Shaanxi University of Technology Hanzhong 723001 China

Department of Chemistry and Key Laboratory of Organic Optoelectronics & Molecular Engineering of Ministry of Education, Tsinghua University Beijing China.

出版信息

RSC Adv. 2023 Feb 16;13(9):5833-5850. doi: 10.1039/d2ra08021d. eCollection 2023 Feb 14.

Abstract

The CO reduction reaction (CORR) into chemical products is a promising and efficient way to combat the global warming issue and greenhouse effect. The viability of the CORR critically rests with finding highly active and selective catalysts that can accomplish the desired chemical transformation. Single-atom catalysts (SACs) are ideal in fulfilling this goal due to the well-defined active sites and support-tunable electronic structure, and exhibit enhanced activity and high selectivity for the CORR. In this review, we present the recent progress of quantum-theoretical studies on electro- and photo-chemical conversion of CO with SACs and frameworks. Various calculated products of CORR with SACs have been discussed, including CO, acids, alcohols, hydrocarbons and other organics. Meanwhile, the critical challenges and the pathway towards improving the efficiency of the CORR have also been discussed.

摘要

将一氧化碳还原反应(CORR)转化为化学产品是应对全球变暖和温室效应的一种有前景且高效的方法。CORR的可行性关键在于找到能够实现所需化学转化的高活性和高选择性催化剂。单原子催化剂(SACs)由于其明确的活性位点和可通过载体调节的电子结构,是实现这一目标的理想选择,并且对CORR表现出增强的活性和高选择性。在这篇综述中,我们展示了关于SACs和框架对CO进行电化学和光化学转化的量子理论研究的最新进展。已经讨论了使用SACs进行CORR的各种计算产物,包括CO、酸、醇、烃类和其他有机物。同时,也讨论了CORR提高效率面临的关键挑战和途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf5a/9932639/cbb1af1a0f0e/d2ra08021d-f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验