Issue 20, 2020

Synthesis of Co2−xNixO2 (0 < x < 1.0) hexagonal nanostructures as efficient bifunctional electrocatalysts for overall water splitting

Abstract

Designing low-cost and high-performance bifunctional electrocatalysts towards hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) is vitally important for water splitting. Herein, we synthesize Co2−xNixO2 (0 < x < 1.0) hexagonal nanosheets with different Co/Ni molar ratios via a facile coprecipitation process followed by calcination under an Ar atmosphere. Changing the Co/Ni molar ratios of the Co2−xNixO2 products is found to have a momentous influence on the microstructures, specific surface areas and electrocatalytic performances. At a Co/Ni molar ratio of 0.6, the Co1.4Ni0.6O2 nanosheet exhibits the largest specific surface area of 60.63 m2 g−1, the best OER with an onset overpotential of 278.5 mV, and HER of 72.8 mV as a bifunctional electrocatalyst. Meanwhile, the minimum Tafel slope is 113.6 mV dec−1 for OER and 77.4 mV dec−1 for HER. The Co1.4Ni0.6O2 nanosheet has excellent OER and HER activity at 0.1 mg cm−2 trace loading. Moreover, we construct an overall water splitting cell using the Co1.4Ni0.6O2 bifunctional electrocatalyst in a two-electrode system to further demonstrate the practical application, which needs a cell voltage of 1.75 V at a current density of 10 mA cm−2 and exhibits great long-term stability. These results provide an efficient strategy for the rational design of Co-based oxides towards bifunctional overall water electrocatalysts.

Graphical abstract: Synthesis of Co2−xNixO2 (0 < x < 1.0) hexagonal nanostructures as efficient bifunctional electrocatalysts for overall water splitting

Supplementary files

Article information

Article type
Paper
Submitted
11 Mar 2020
Accepted
17 Apr 2020
First published
04 May 2020

Dalton Trans., 2020,49, 6587-6595

Synthesis of Co2−xNixO2 (0 < x < 1.0) hexagonal nanostructures as efficient bifunctional electrocatalysts for overall water splitting

H. Li, L. Chen, P. Jin, H. Lv, H. Fu, C. Fan, S. Peng, G. Wang, J. Hou, F. Yu and Y. Shi, Dalton Trans., 2020, 49, 6587 DOI: 10.1039/D0DT00925C

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