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Published April 2018 | Published + Supplemental Material
Journal Article Open

Oxygen-Vacancy Abundant Ultrafine Co₃O₄/Graphene Composites for High-Rate Supercapacitor Electrodes

Abstract

The metal oxides/graphene composites are one of the most promising supercapacitors (SCs) electrode materials. However, rational synthesis of such electrode materials with controllable conductivity and electrochemical activity is the topical challenge for high-performance SCs. Here, the Co₃O₄/graphene composite is taken as a typical example and develops a novel/universal one-step laser irradiation method that overcomes all these challenges and obtains the oxygen-vacancy abundant ultrafine Co₃O₄ nanoparticles/graphene (UCNG) composites with high SCs performance. First-principles calculations show that the surface oxygen vacancies can facilitate the electrochemical charge transfer by creating midgap electronic states. The specific capacitance of the UCNG electrode reaches 978.1 F g⁻¹ (135.8 mA h g⁻¹) at the current densities of 1 A g⁻¹ and retains a high capacitance retention of 916.5 F g⁻¹ (127.3 mA h g⁻¹) even at current density up to 10 A g⁻¹, showing remarkable rate capability (more than 93.7% capacitance retention). Additionally, 99.3% of the initial capacitance is maintained after consecutive 20 000 cycles, demonstrating enhanced cycling stability. Moreover, this proposed laser-assisted growth strategy is demonstrated to be universal for other metal oxide/graphene composites with tuned electrical conductivity and electrochemical activity.

Additional Information

© 2017 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Received: September 28, 2017; Revised: November 27, 2017; First published: 15 January 2018. This work is supported by NSFC (51702123, 51472110), Shandong Provincial Natural Science Foundation (ZR2016EMB05, ZR2017ZB0315), University of Jinan Science Foundation (No. XKY1630). S.Y. thanks the start-up research funding and B.C. thanks the Taishan Scholar Professorship both from University of Jinan. Y.L. thanks the startup support from UT Austin. This work used computational resources sponsored by the DOE's Office of Energy Efficiency and Renewable Energy and located at the National Renewable Energy Laboratory, and the Texas Advanced Computing Center (TACC) at UT Austin. The authors declare no conflict of interest.

Attached Files

Published - Yang_et_al-2018-Advanced_Science.pdf

Supplemental Material - advs535-sup-0001-S1.pdf

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Created:
August 19, 2023
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October 18, 2023