Suppr超能文献

调控锚定在超薄g-CN@碳球上的高度分散钴原子的化学键合以增强析氧反应的电催化活性

Controlling the Chemical Bonding of Highly Dispersed Co Atoms Anchored on an Ultrathin g-CN@Carbon Sphere for Enhanced Electrocatalytic Activity of the Oxygen Evolution Reaction.

作者信息

Song Qianqian, Li Junqi, Wang Lei, Pang Lingyan, Liu Hui

机构信息

School of Materials Science and Engineering, Shaanxi Key Laboratory of Green Preparation and Functionalization for Inorganic Materials , Shaanxi University of Science and Technology , Xi'an 710021 , P. R. China.

出版信息

Inorg Chem. 2019 Aug 19;58(16):10802-10811. doi: 10.1021/acs.inorgchem.9b01089. Epub 2019 Jul 30.

Abstract

Controlling the chemical bonding of an active atom and carbon support is an effective strategy for enhancing the electrocatalytic activity of a metal-nitrogen/carbon catalyst. Herein, highly dispersed Co atoms are successfully prepared by using an ultrathin g-CN@carbon sphere as the support, and subsequently the well-defined Co-N and Co-O bonds on the atomic level are controllably constructed by adjusting the calcination atmosphere. Results show that highly dispersed Co with Co-O and Co-N bonds exhibits excellent oxygen evolution reaction performance in alkaline media at low and high overpotentials, respectively, and outperform most single-atom catalysts reported to date. DFT calculation, coupled with high-angle annular dark-field scanning transmission electron microscopy and X-ray photoelectron spectrometry techniques, reveals that the high activities mainly originate from the precise O-Co-N and N-Co-N coordination in the ultrathin g-CN@carbon sphere support. The enhancement mechanism of chemical bonding provides guidance for the atomic exploration and design of electrocatalysts.

摘要

控制活性原子与碳载体之间的化学键合是提高金属-氮/碳催化剂电催化活性的有效策略。在此,以超薄g-CN@碳球为载体成功制备了高度分散的Co原子,随后通过调节煅烧气氛在原子水平上可控地构建了明确的Co-N和Co-O键。结果表明,具有Co-O和Co-N键的高度分散Co分别在碱性介质中低过电位和高过电位下表现出优异的析氧反应性能,优于迄今为止报道的大多数单原子催化剂。密度泛函理论计算结合高角度环形暗场扫描透射电子显微镜和X射线光电子能谱技术表明,高活性主要源于超薄g-CN@碳球载体中精确的O-Co-N和N-Co-N配位。化学键合的增强机制为电催化剂的原子探索和设计提供了指导。

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