Abstract
Graphyne materials have shown promising advantages for fabrication of carbon-based, metal-free catalysts (CMFCs) in the electrocatalytic field. Herein, we report functionalized γ-graphdiyne nanoribbons (γGDyNRs) by edge termination or N doping as potential bifunctional CMFCs for oxygen reduction reaction (ORR) and hydrogen evolution reaction (HER) via intensive density functional theory (DFT) simulations. It is revealed that sp-N doping (sandwiched by two sp-C) at the inner location and sp2-N doping near the edge can effectively boost the ORR and HER performance of inert γGDyNRs. Our results further demonstrate that sp2-N can play a principal role, especially when at the edge of γGDY; this effect was not addressed in earlier experimental and theoretical work. We also built a machine learning model for predicting bifunctional activities using a light gradient boosting machine. Feature importance analysis shows that the distance between adsorption site and the closest atom to it and the atomic charge of adsorption site are the most important features in determining the activities. Our work not only identifies γGDyNRs as promising alternative catalysts to Pt, but also benefits the rational design of novel CMFCs with high efficiency.
| Original language | English |
|---|---|
| Article number | 156084 |
| Journal | Applied Surface Science |
| Volume | 613 |
| DOIs | |
| State | Published - 15 Mar 2023 |
Keywords
- Bifunctional activity
- Density functional theory
- Graphyne materials
- Machine learning