Trade-off between quantum capacitance and thermodynamic stability of defected graphene: an implication for supercapacitor electrodes

Binder-Free Supercapacitors Based on Thin Films of MWCNT/GO Nanohybrids: Computational and Experimental Analysis

This work reports an innovative approach to the fabrication of free-standing thin films of multiwalled carbon nanotubes (MWCNTs)/graphene oxide (GO) nanohybrids by using dimethyl formamide (DMF) and n-hexane as a solvent–antisolvent system for the growth of thin films of MWCNTs/GO nanohybrids. The synthesis of the GO was carried out by using the modified Hummers method, while the synthesis of MWCNTs/GO nanohybrids was done by the intermixing of the carboxylic acid functionalized MWCNT and GO using the solution-mixing method. The growth of the thin film of MWCNTs/GO nanohybrids was done by obeying the surface-tension-driven phenomena which occur mainly due to the coalescence of bubbles due to the solvent–antisolvent interfacial tension. Furthermore, density functional theory (DFT)-based first-principles simulations were performed to understand the structural, electronic, and capacitive aspects of MWCNT/GO nanohybrids. The computational results demonstrated excellent quantum capacitance in the MWCNT/GO nanohybrid electrodes. Inspired by the computational results, the same process elaborated above has also been employed to develop binder-free supercapacitor devices utilizing the MWCNT/GO nanohybrid as an electrode material. The electrochemical performance of this electrode in 1 M aqueous H2SO4 demonstrates a good energy density of 21.63 WhKg−1 at a current density of 0.5 Ag−1, with a high specific capacitance of 369.01 F/g at the scan rate of 2 mVs−1 and excellent cyclic stability of 97% for 5000 charge–discharge cycles.

A first-principles roadmap and limits to design efficient supercapacitor electrode materials

A road map to guide researchers to predict the desired properties is presented based on the DFT calculations to allow researchers decide which property of the material they wish to predict or develop and how to choose the proper DFT route to do so.