Synergetic Experimental and ANN- Based Modeling of Cyclic Voltammetry Behavior in NH 4 F-Assisted MnCo 2 O 4 Nanosheet for High-Performance Supercapacitors

MnCo ₂ O ₄ nanostructures were chemically deposed on stainless steel flexible substrate with the assistance of NH ₄ F for their excellent supercapacitor electrodes properties. MnCO ₂ O ₄ nanowires and nanosheet were grown on the stainless steel mech through a one-step hydrothermal process using NH ₄ F. The as prepared nanowires and nanosheet MnCo ₂ O ₄ was characterized by XRD, FTIR, SEM-EDX. The XRD spectra of the sample exhibited a face centered cubic phase structure. SEM observations showed that the addition of NH ₄ F transformed the MnCo ₂ O ₄ morphology from nanowires to arrays of nanosheets, anchored onto stainless steel mesh. The electrochemical performance of MnCo ₂ O ₄ nanowires and nanosheets was evaluated using EIS, CV and GCD. The associated morphological modification plays a crucial role in enhancing the electrochemical charge storage capability of the supercapacitor electrodes. According to EIS studies, incorporating NH ₄ F enhances capacitance and charge distribution while reducing charge transfer resistance. The CV and GCD tests confirmed that MnCo ₂ O ₄ nanosheet arrays demonstrated improved highest CV-specific capacitance of 318.7 F g ^-1 at 5 mV s ^-1 , aligned with GCD- specific capacitance reaching 769.3 at 1 A g ^-1 . Furthermore, the cyclic voltammetry of the prepared electrodes was successfully predicted using an intelligent artificial neural network (ANN) implemented in Python environment. The proposed ANN model exhibits strong learning capability and high predictive accuracy demonstrating a satisfactory predictive performance with an error below 0.05%. Overall, these results indicate that the developed ANN model, combined with the superior electrochemical performance of the synthesized electrode, holds strong potential for supercapacitor application.