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A High-Throughput Screening toward Efficient Nitrogen Fixation: Transition Metal Single-Atom Catalysts Anchored on an Emerging π-π Conjugated Graphitic Carbon Nitride (g-C 10 N 3 ) Substrate with Dirac Dispersion.

Qiang ZhangXian WangFuchun ZhangChunyao FangDi LiuQingjun Zhou
Published in: ACS applied materials & interfaces (2023)
TM-N x is becoming a comforting catalytic center for sustainable and green ammonia synthesis under ambient conditions, resulting in increasing interest in single-atom catalysts (SACs) for the electrochemical nitrogen reduction reaction (NRR). However, given the poor activity and unsatisfactory selectivity of existing catalysts, it remains a long-standing challenge to design efficient catalysts for nitrogen fixation. Currently, the two-dimensional (2D) graphitic carbon-nitride substrate provides abundant and evenly distributed holes for stably supporting transition-metal atoms, which presents a fascinating prospect for overcoming this challenge and promoting single-atom NRR. An emerging holey graphitic carbon-nitride skeleton with a C 10 N 3 stoichiometric ratio (g-C 10 N 3 ) from a supercell of graphene is constructed, which provides outstanding electric conductivity for achieving high-efficiency NRR due to the Dirac band dispersion. Herein, a high-throughput first-principles calculation is carried out to evaluate the feasibility of π-d conjugated SACs resulting from a single TM atom anchored on g-C 10 N 3 (TM = Sc-Au) for NRR. We find that W metal embedded in g-C 10 N 3 (W@g-C 10 N 3 ) can compromise the ability to adsorb the key target reaction species (N 2 H and NH 2 ), hence acquiring an optimal NRR behavior among 27 TM-candidates. Our calculations demonstrate that W@g-C 10 N 3 shows a well-suppressed HER ability and, impressively, a low energy cost of -0.46 V. Additionally, all-around descriptors are proposed to uncover the fundamental mechanism of NRR activity, among which a 3D volcano plot (limiting potential, screening strategy, and electron origin) uncovers the NRR activity trend, achieving a quick and high-efficiency prescreening for numerous candidates. Overall, the strategy of the structure- and activity-based TM-N x -containing unit design will offer useful insight for further theoretical and experimental attempts.
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