Dendritic NiS2@Co-N-C nanoarchitectures as bifunctional electrocatalysts for long-life Zn-air batteries

INORGANIC CHEMISTRY FRONTIERS(2023)

Cited 2|Views7
No score
Abstract
Zn-air batteries (ZABs) have been widely studied due to their high theoretical energy density, low cost, and high safety. However, the lack of efficient bifunctional electrocatalysts toward both the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) hinders their large-scale application. Herein, a dendritic NiS2@Co-N-C/CNF nanoarchitecture is proposed, which was fabricated by high-temperature carbonization of Co-MOFs and a subsequent simple hydrothermal composite method using NiS2 nanosheets. The catalyst is reasonably designed to integrate the oxygen reduction reaction (ORR)/oxygen evolution reaction (OER) active sites on the surface of carbon nanofibers. Through the synergy between NiS2 and Co-N-C/CNF and the unique branch-leaf porous structure, the catalyst showed excellent catalytic activity and stability. In an alkaline electrolyte, the OER overpotential of NiS2@Co-N-C/CNF is 300 mV at 10 mA cm(-2). The ORR half-wave potential (E-1/2) of NiS2@Co-N-C/CNF is 0.8 V. In addition, the superior catalytic activity of NiS2@Co-N-C/CNF could be transferred to a ZAB, which exhibits a maximum peak power density of 181 mW cm(-2) along with an ultra-long cycling stability for 1050 and 600 h at discharging current densities of 5 and 10 mA cm(-2), respectively. The performance is significantly higher than that of commercial precious metal Pt/C + IrO2 mixed catalysts. The peak power density of solid state ZAB (SSZAB) integrated with NiS2@Co-N-C/CNF is 76 mW cm(-2), and it can still maintain excellent cycling stability under different bending states. More impressively, four in-series SSZABs (NiS2@Co-N-C/CNFs) can charge smartphones, indicating their potential feasibility in the field of wearable electronics.
More
Translated text
Key words
bifunctional electrocatalysts,dendritic nis<sub>2</sub>@co–n–c,zn–air,long-life
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined