Building Up a Picture of the Electrocatalytic Nitrogen Reduction Activity of Transition Metal Single-Atom Catalysts

化学 反键分子轨道 催化作用 过渡金属 吸附 掺杂剂 氮气 无机化学 密度泛函理论 纳米技术 计算化学 组合化学 兴奋剂 原子轨道 有机化学 材料科学 电子 物理 量子力学 光电子学
作者
Xin Liu,Yan Jiao,Yao Zheng,Mietek Jaroniec,Shi Zhang Qiao
出处
期刊:Journal of the American Chemical Society [American Chemical Society]
卷期号:141 (24): 9664-9672 被引量:787
标识
DOI:10.1021/jacs.9b03811
摘要

The lack of chemical understanding and efficient catalysts impedes the development of electrocatalytic nitrogen reduction reaction (eNRR) for ammonia production. In this work, we employed density functional theory calculations to build up a picture (activity trends, electronic origins, and design strategies) of single-atom catalysts (SACs) supported on nitrogen-doped carbons as eNRR electrocatalysts. To construct such a picture, this work presents systematic studies of the eNRR activity of SACs covering 20 different transition metal (TM) centers coordinated by nitrogen atoms contained in three types of nitrogen-doped carbon substrates, which gives 60 SACs. Our study shows that the intrinsic activity trends could be established on the basis of the nitrogen adatom adsorption energy (ΔEN*). Furthermore, the influence of metal and support (ligands) on ΔEN* proved to be related to the bonding/antibonding orbital population and regulating the scaling relations for adsorption of intermediates, respectively. Accordingly, a two-step strategy is proposed for improving the eNNR activity of TM-SACs, which involves the following: (i) selection of the most promising family of SACs (g-C3N4 supported SACs as predicted in this work) and (ii) further improvement of the activity of the best candidate in the aforementioned family via tuning the adsorption strength of the key intermediates. Also, the stability of N-doped carbon supports and their selectivity in comparison to the competing hydrogen evolution need to be taken into consideration for screening the durable and efficient candidates. Finally, an effective strategy for designing active, stable, and selective SACs based on the mechanistic insights is elaborated to guide future eNRR studies.
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