Issue 30, 2022

Nanocrystals of CuCoO2 derived from MOFs and their catalytic performance for the oxygen evolution reaction

Abstract

In this work, two different solvothermal synthesis routes were employed to prepare MOF-derived CuCoO2 (CCO) nanocrystals for electrocatalytic oxygen evolution reaction (OER) application. The effects of the reductants (ethylene glycol, methanol, ethanol, and isopropanol), NaOH addition, the reactants, and the reaction temperature on the structure and morphology of the reaction product were investigated. In the first route, Cu-BTC derived CCO (CCO1) nanocrystals with a size of ∼214 nm and a specific surface area of 4.93 m2 g−1 were prepared by using Cu-BTC and Co(NO3)2·6H2O as the Cu and Co source, respectively. In the second route, ZIF-67 derived CCO (CCO2) nanocrystals with a size of ∼146 nm and a specific surface area of 11.69 m2 g−1 were prepared by using ZIF-67 and Cu(NO3)2·3H2O as the Co and Cu source, respectively. Moreover, the OER performances of Ni foam supported CCO1 (Ni@CCO1) and CCO2 (Ni@CCO2) electrodes were evaluated in 1.0 M KOH solution. Ni@CCO2 demonstrates a better OER catalytic performance with a lower overpotential of 394.5 mV at 10 mA cm−2, a smaller Tafel slope of 82.6 mV dec−1, and long-term durability, which are superior to those of some previously reported delafossite oxide or perovskite oxide catalysts. This work reveals the preparation method and application potential of CCO electrocatalysts by using Cu-BTC/ZIF-67 as the precursor, providing a new approach for the preparation of delafossite oxide CCO and the enhancement of their OER performances.

Graphical abstract: Nanocrystals of CuCoO2 derived from MOFs and their catalytic performance for the oxygen evolution reaction

Supplementary files

Article information

Article type
Paper
Submitted
25 Apr 2022
Accepted
07 Jul 2022
First published
07 Jul 2022

Dalton Trans., 2022,51, 11536-11546

Nanocrystals of CuCoO2 derived from MOFs and their catalytic performance for the oxygen evolution reaction

H. Gao, X. Liu, N. Han, L. Shi, L. Wang, Y. Mi, X. Bao, J. Bai, H. Li and D. Xiong, Dalton Trans., 2022, 51, 11536 DOI: 10.1039/D2DT01281B

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