Nanocomposites showed high specific capacitance of 1588.72 F/g, suggesting potential in supercapacitor applications.
In this paper, graphene oxide (GO), reduced graphene oxide (rGO), molybdenum disulfide (MoS 2 ), polythiophene (PTh), GO/MoS 2 /PTh, rGO/MoS 2 /PTh, and rGO/MoS 2 /PTh/carbon black (CB) nanocomposites were firstly synthesized to be used as a component of electrode material for supercapacitor devices. Thiophene monomer was chemically synthesized by an in‐situ oxidation polymerization method. The microwave‐irradiation method was used to form the reduction process of GO. The materials were characterized by scanning electron microscopy, energy dispersive x‐ray analysis, atomic force microscopy, thermogravimetric analysis (TGA) and, differential thermal analysis, Fourier transform infrared spectroscopy, and attenuated total reflectance analysis, Brunauer–Emmett–Teller analysis, four‐point probe conductivity, cyclic voltammetry, galvanostatic charge‐discharge and electrochemical impedance spectroscopy analysis. The TGA analysis shows that PTh has the most degradable material due to small polymer chains. However, the highest thermal stability (98.56%) was obtained for MoS 2 . The temperature raised up to 982°C. Moreover, the highest specific capacitance was calculated as C sp = 1588.72 F/g at 2 mV/s for the rGO/MoS 2 /PTh nanocomposite in a 6 M KOH electrolyte solution. In addition, the highest energy and power densities, specific capacitive retention, and the lowest equivalent series resistance (ESR) were presented for this nanocomposite as E = 3.20 Wh/kg at 10 mA, P = 1152.5 W/kg at 10 mA, 111.48% after 1000 charge–discharge cycles and ESR = 0.05 Ω at 10 mA, respectively. Equivalent ladder circuit model of R s ( C 1 ( R 1 ( R 2 C 2 ))) was also evaluated to interpret theoretical and experimental data using ZSimpWin 3.22 program. Results are compatible with each other. An easy preparation method and eco‐friendly synthesis were reported for rGO/MoS 2 /PTh/CB nanocomposite for next generation supercapacitor evaluations.
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Ateş et al. (2025) studied this question.
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