Response Surface Methodology Optimization in High-Performance Solid-State Supercapattery Cells Using NiCo2S4-Graphene Hybrids
MOLECULES(2022)
Abstract
In this work, NiCo2S4-graphene hybrids (NCS@G) with high electrochemical performance were prepared using a hydrothermal method. The response surface methodology (RSM), along with a central composite design (CCD), was used to investigate the effect of independent variables (G/NCS, hydrothermal time, and S/Ni) on the specific capacitances of the NCS@G/Ni composite electrodes. RSM analysis revealed that the developed quadratic model with regression coefficient values of more than 0.95 could be well adapted to represent experimental results. Optimized preparation conditions for NCS@G were G/NCS = 6.0%, hydrothermal time = 10.0, and S/Ni = 6.0 of NCS@G (111) sample. The maximum specific capacitance of NCS@G (111)/Ni fabricated at the optimal condition is about 216% higher than the best result obtained using the conventional experimental method. The enhanced capacitive performance of the NCS@G (111) sample can be attributed to the synergistic effect between NCS nanoparticles and graphene, which has the meso/macropores conductive network and low diffusion resistance. Notably, the NCS@G (111) could not only provide numerous reaction sites but also prevent the restacking of graphene layers. Furthermore, a supercapattery cell was fabricated with an (G + AC)/Ni anode, a NCS@G (111)/Ni cathode, and a carboxymethyl cellulose-potassium hydroxide (CMC-KOH) gel electrolyte. The NCS@G (111)//(G + AC) demonstrates an outstanding energy density of 80 Wh kg(-1) at a power density of 4 kW kg(-1), and a good cycling performance of 75% after 5000 cycles at 2 A g(-1). Applying the synthesis strategy of RSM endows remarkable capacitive performance of the hybrid materials, providing an economical pathway to design promising composite electrode material and fabricate high-performance energy storage devices.
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Key words
NiCo2S4,graphene,response surface methodology,optimization,supercapattery cell
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