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Nitrogen Electroreduction Performance of Transition Metal Dimers Embedded into N-Doped Graphene: A Theoretical Prediction

Abstract

The electrocatalytic nitrogen reduction reaction (eNRR) at ambient conditions using sustainable energy sources is a fascinating approach for ammonia (NH3) production to replace the industrial Haber-Bosch process with enormous energy input and continuous CO2 emissions. However, the eNRR process remains a coveted goal due to the poor product selectivity, low activity, and stability of the traditional catalysts. Inspired by the recent experimental advances on dual-atom catalysts, herein, by means of comprehensive spin-polarized density functional theory (DFT) computations, the catalytic performance of various binary transition metals dispersed in nitrogen-doped porous graphene (NPG) for the eNRR was systematically evaluated. Our results revealed that the N atoms around vacancy in substrate can strongly stabilize these metal dimers by forming the metal-N bonds. Among FeFe, FeCo, FeNi, FeCu, FeRh, FeRu, FePd, MoFe, MoCo, MoCu, MoRu, and MoMo, the binary FeRh embedded in NPG was identified as the most active catalyst due to its lowest limiting potential (0.22 V) via the distal mechanism. Our results further suggested that the good eNRR catalytic activity of the dispersed FeRh mainly originates from its optimal adsorption/desorption features with the eNRR intermediates, obvious suppressing effect on the hydrogen evolution reaction, and great promise for synthesis. Our work not only opens a new door to advance sustainable NH3 production by tailoring the electronic structures of the binuclear metal atoms, but also provides deeper insight into the structure-performance relationships of dual sites for eNRR electrocatalysts.

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Supplementary files

Article information


Submitted
12 Dec 2019
Accepted
29 Jan 2020
First published
30 Jan 2020

J. Mater. Chem. A, 2020, Accepted Manuscript
Article type
Paper

Nitrogen Electroreduction Performance of Transition Metal Dimers Embedded into N-Doped Graphene: A Theoretical Prediction

J. Zhao, H. Li, L. Yin, Q. Cai and Z. Zhao, J. Mater. Chem. A, 2020, Accepted Manuscript , DOI: 10.1039/C9TA13599E

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