Artificial Intelligence-based Cyclic Voltammetry Behavior Model for Supercapacitance of Zinc oxide (ZnO) Nanocomposite

This paper presents the fabrication of binder-free nanostructured Zinc oxide (ZnO) electrode for supercapacitor by the chemical bath deposition method. Further, cyclic voltammetry was modeled using an artificial neural network. The prepared material resulted in increasing the capacitance value; acting as a binder-free electrode. Results of the electrochemical study revealed that the medium current is 1.335mA. Using artificial neural network modeling primarily based totally on the idea of multilayer Perception. The cyclic behavior of the organized fabric is examined. From the evaluation of the artificial neural network, the outcomes have been obtained to be much like the experimental values with an error rate of 0.1.