Identification of champion transition metals centers in metal and nitrogen-codoped carbon catalysts for CO2 reduction

By Fuping Pan, Wei Deng, C. Justiniano, Ying Li. Applied Catalysis B: Environmental, 2018

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Abstract Transition metal is known to influence electrochemical activities over transition metals (M) and nitrogen (N)-codoped carbon (M N C) catalysts. However, champion transition metals centers in M N C for catalyzing CO2 reduction reaction (CO2RR) remain unclear, hindering further catalyst development with enhanced performance. Herein, we report the investigation of effects of five transition metals (Cr, Mn, Fe, Co, Ni) on CO2RR activities and mechanisms using metal-doped nitrogenated carbon nanosheets as model catalysts fabricated via a novel space-confinement-assisted molecular-level complexing approach. Analyzing N 1s XPS spectra confirmed the formation of M−N complexes via the coordination of metals atoms with pyridinic N, which was identified as the active species in CO2RR. According to activity descriptors including overpotentials, Faradaic efficiency (FE) and Turnover Frequency (TOF) per metal site, we here established that Fe and Ni are more active than Co, Mn, and Cr in M N C for the reduction of CO2 to CO. The main role of Fe is to reduce overpotentials, exhibiting the lowest onset overpotential of 0.19 V to yield CO on Fe N C. Ni can drastically improve CO selectivity and reaction rates, yielding the highest CO Faradaic efficiency of 96%, partial current density of −8.2 mA cm−2, and TOF of 1060 h−1 at a moderate overpotential of 0.65 V. Mechanism explorations reveal that CO2RR on M N C (M = Fe, Cr, Mn) undergoes the formation of a *COOH intermediate as the rate-determining step, whereas M N C (M = Ni, Co) catalyzes CO2RR via the transfer of the first electron to form a *CO2 − species. On the basis of the findings, we suggest doping Fe and/or Ni to design advanced M N C for CO2 electroreduction.

Subfields: Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/e54a388f70332b79f7f6e06895b4e6e87cc4c2fd

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