Boron-doped sucrose carbons for supercapacitor electrode: artificial neural network-based modelling approach

Abstract

Here, a simple yet efficient and economic strategy were demonstrated for the production of multiporous boric acid-doped sucrose carbon (B-x-pC) for supercapacitor application. The electrochemical performance was established through cyclic voltammetry and galvanostatic charge/discharge tests. B-x-pC samples were characterized by X-ray diffraction, scanning electron microscope, Raman spectroscopy and nitrogen adsorption/desorption at - 196 degrees C. The results reveal that the optimum boron dopant is 2 at %; and B-2-pC containing 2 at.% boron exhibited honeycomb-like porous structure (2.88 nm) and a high specific surface area of 1298.9 m(2) g(-1). The B-2-pC-based symmetric supercapacitor delivered a remarkable energy density of similar to 56 Wh kg(-1), a high power density of 1300 W kg(-1) and superior capacitance of 239 F g(-1) t 1 A g(-1) in 1 M H2SO4 lectrolyte. To establish the complex relationships between the electrode structure, active operating conditions and electrochemical performance of the supercapacitor, an artificial neural network (ANN) methodology was utilized herein. After several random runs, the ANN maintained satisfactory predictive performance with an average error rate of similar to 1.06% and desirability function of 0.93 which is closer to 1.0.