Abstract

Carbon-based metal free materials (CMFCs) as electrocatalysts have been a hot issue and are receiving growing attention. In this paper, we applied intensive density functional theory (DFT) calculations to study the electrocatalytic activities of γ-graphyne nanoribbons (γGyNRs) toward the oxygen reduction reaction (ORR) and hydrogen evolution reaction (HER). Our results revealed γGyNRs to be excellent bifunctional CMFCs after functionalization by termination or N-doping at the edge to introduce proper spin densities. The scaling relationship analysis enhanced our earlier understanding that the binding strength of H atom (ΔEH) is a general descriptor for designing bifunctional electrocatalysts for HER and ORR. Further study revealed that the light gradient boosting machine is a promising machine learning algorithm to accurately predict the electrocatalytic activities of γGyNRs. Feature importance analysis suggested that the surrounding environment of the active site plays a more significant role than we previously anticipated. Overall, we suggest promising γGyNRs as HER and ORR bifunctional electrocatalysts for the first time and provide deeper insight into the reaction mechanism, which is beneficial for the rational design of novel CMFCs.

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