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A universal descriptor based on pz-orbitals for the catalytic activity of multi-doped carbon bifunctional catalysts for oxygen reduction and evolution.
Nanoscale ( IF 5.8 ) Pub Date : 2020-08-21 , DOI: 10.1039/d0nr03521a
Jiameng Ma 1 , Qiuming Zhi , Lele Gong , Yang Shen , Defeng Sun , Yongjian Guo , Lipeng Zhang , Zhenhai Xia
Affiliation  

Dual-/multi-heteroatom-doped carbon nanomaterials have been demonstrated to be effective bi-/multi-functional catalysts for the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER), the critical reactions in fuel cells and metal–air batteries, respectively. However, trial-and-error routes are usually used to search for better catalysts from multi-doped complex material systems, and establishing design principles or intrinsic descriptors would accelerate the discovery of new efficient catalysts. Here, a descriptor based on pz-orbitals of active sites is proposed to describe the catalytic performance of dual-/tri-element-doped graphene catalysts for the ORR and the OER. In addition to multiple doping, the established descriptor is universal in nature and can also predict the contributions of defects and edges or their combinations. The prediction capacity of the descriptor is further enhanced by introducing a correction factor based on crystal orbital Hamilton population (COHP) analysis, which reveals the differences between the adsorption mechanism of edged C and graphitic C on graphene. The predictions are consistent with DFT calculations and experimental results. This work provides a powerful tool for rapidly screening multi-doped complex material systems for the desired ORR and OER bifunctional catalysts.

中文翻译:

基于pz轨道的通用描述符,用于多掺杂碳双功能催化剂的氧还原和放出催化活性。

掺杂双/多杂原子的碳纳米材料已被证明是有效的双/多功能催化剂,可用于氧还原反应(ORR)和氧释放反应(OER),燃料电池和金属-空气中的关键反应电池。然而,试错法通常用于从多掺杂复杂材料系统中寻找更好的催化剂,而建立设计原理或内在描述符将加速新型高效催化剂的发现。在此,基于p z的描述符提出了活性位点轨道来描述双/三元素掺杂石墨烯催化剂对ORR和OER的催化性能。除了多次掺杂之外,所建立的描述符本质上是通用的,并且还可以预测缺陷和边缘或其组合的影响。通过引入基于晶体轨道汉密尔顿人口(COHP)分析的校正因子,进一步增强了描述符的预测能力,该校正因子揭示了边缘碳和石墨碳在石墨烯上的吸附机理之间的差异。这些预测与DFT计算和实验结果一致。这项工作为快速筛选所需的ORR和OER双功能催化剂的多掺杂复杂材料系统提供了强大的工具。
更新日期:2020-10-02
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