Single-atom catalysts based on metal–N4 moieties and anchored on carbon supports (defined as M–N–C) are promising for oxygen reduction reaction (ORR). Among those, M–N–C catalysts with 4d and 5d transition metal (TM4d,5d) centers are much more durable and not susceptible to the undesirable Fenton reaction, especially compared with 3d transition metal based ones. However, the ORR activity of these TM4d,5d–N–C catalysts is still far from satisfactory; thus far, there are few discussions about how to accurately tune the ligand fields of single-atom TM4d,5d sites in order to improve their catalytic properties. Herein, we leverage single-atom Ru–N–C as a model system and report an S-anion coordination strategy to modulate the catalyst’s structure and ORR performance. The S anions are identified to bond with N atoms in the second coordination shell of Ru centers, which allows us to manipulate the electronic configuration of central Ru sites. The S-anion-coordinated Ru–N–C catalyst delivers not only promising ORR activity but also outstanding long-term durability, superior to those of commercial Pt/C and most of the near-term single-atom catalysts. DFT calculations reveal that the high ORR activity is attributed to the lower adsorption energy of ORR intermediates at Ru sites. Metal–air batteries using this catalyst in the cathode side also exhibit fast kinetics and excellent stability.
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Understanding activity origin for the oxygen reduction reaction on bi-atom catalysts by DFT studies and machine-learning
Bi-atom catalysts (BACs) have attracted increasing attention in important electrocatalytic reactions such as the oxygen reduction reaction (ORR). Here, by means of density functional theory simulations coupled with machine-learning technology, we explored the structure–property correlation and catalytic activity origin of BACs, where metal dimers are coordinated by N-doped graphene (NC). We first sampled 26 homonuclear (M 2 /NC) BACs and constructed the activity volcano curve. Disappointingly, only one BAC, namely Co 2 /NC, exhibits promising ORR activity, leaving considerable room for enhancement in ORR performance. Then, we extended our study to 55 heteronuclear BACs (M 1 M 2 /NC) and found that 8 BACs possess competitive or superior ORR activity compared with the Pt(111) benchmark catalyst. Specifically, CoNi/NC shows the most optimal activity with a very high limiting potential of 0.88 V. The linear scaling relationships among the adsorption free energy of *OOH, *O and *OH species are significantly weakened on BACs as compared to a transition metal surface, indicating that it is difficult to precisely describe the catalytic activity with only one descriptor. Thus, we adopted machine-learning techniques to identify the activity origin for the ORR on BACs, which is mainly governed by simple geometric parameters. Our work not only identifies promising BACs yet unexplored in the experiment, but also provides useful guidelines for the development of novel and highly efficient ORR catalysts.
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- Award ID(s):
- 1849243
- PAR ID:
- 10221171
- Date Published:
- Journal Name:
- Journal of Materials Chemistry A
- Volume:
- 8
- Issue:
- 46
- ISSN:
- 2050-7488
- Page Range / eLocation ID:
- 24563 to 24571
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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