Porous nitrogen-doped graphdiyne templated from zinc acetylacetonate for enhanced oxygen reduction reaction

Wenyan Si , Meiping Li , Xingru Yan , Qing Lv , Changshui Huang

ChemPhysMater ›› 2025, Vol. 4 ›› Issue (3) : 274 -279.

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ChemPhysMater ›› 2025, Vol. 4 ›› Issue (3) :274 -279. DOI: 10.1016/j.chphma.2025.01.003
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Porous nitrogen-doped graphdiyne templated from zinc acetylacetonate for enhanced oxygen reduction reaction
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Abstract

Catalysts for the oxygen reduction reaction (ORR) are crucial for energy conversion and storage. Notably, the number of available active sites directly influences the catalyst activity. A large specific surface area is conducive to the creation of more active sites on a catalyst, thereby improving its performance. Zn precursors easily decompose or volatilize at high temperatures, forming a structure with abundant pores, thereby facilitating nitrogen doping. A method for enhancing the ORR activity of nitrogen-doped graphdiyne (GDY) was developed by employing zinc acetylacetonate as a pore-forming agent to increase the exposure of the active N sites. The as-prepared catalyst (denoted as ZnT-N-GDY, where T refers to the template) outperformed Pt/C in the ORR and maintained stable cycling over 2000 cycles in zinc-air batteries, facilitated by the increased exposure of the active N sites, especially pyridinic nitrogen.

Keywords

Oxygen reduction reaction / Graphdiyne / Metal-free catalyst / Zinc-air battery

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Wenyan Si, Meiping Li, Xingru Yan, Qing Lv, Changshui Huang. Porous nitrogen-doped graphdiyne templated from zinc acetylacetonate for enhanced oxygen reduction reaction. ChemPhysMater, 2025, 4 (3) : 274-279 DOI:10.1016/j.chphma.2025.01.003

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Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

CRediT authorship contribution statement

Wenyan Si: Writing – original draft, Investigation. Meiping Li: Writing – review & editing, Funding acquisition, Data curation. Xingru Yan: Validation, Formal analysis. Qing Lv: Data curation, Conceptualization. Changshui Huang: Supervision, Funding acquisition, Conceptualization.

Acknowledgements

This work was supported by the National Key Research and Development Project of China (2022YFA1204500 and 2022YFA1204501), National Natural Science Foundation of China (No. 22172090), Strategic Priority Research Program of the Chinese Academy of Sciences (XDB0520200), Postdoctoral Fellowship Program of CPSF (GZC20232733), and Beijing National Laboratory for Molecular Sciences (2023BMS20131).

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