Journal
MATERIALS SCIENCE IN SEMICONDUCTOR PROCESSING
Volume 36, Issue -, Pages 43-48Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.mssp.2015.02.084
Keywords
MnO2; Supercapacitor; Artificial neural network (ANN); Thin films
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Funding
- CSIR, New Delhi [03 (1240)/12/EMR-II]
- Human Resource Development of the Korea Institute of Energy technology Evaluation and Planning (KETEP) - Korea Government Ministry of Knowledge Economy [20124010203180]
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This paper deals with the fabrication of MnO2 supercapacitor and modeling of cyclic voltammetery using Artificial Neural Network (ANN). Nano fiber MnO2 (NF-MnO2) films synthesized on stainless steel substrate by adopting potentiodynamic technique from an aqueous manganous sulfate monohydrate (MnSO4 center dot H2O) and surface morphology have characterized using field emission scanning electron microscope (FE-SEM). The electrochemical characterizations have studied with the help of cyclic voltammogram, from which the maximum specific capacitance was estimated to be 392 F g(-1). The present investigation further involves modeling of supercapacitor performance using artificial neural network (ANN) approach. The said ANN model based on the multilayer perceptron concept and model is scripted in MATLAB. The Levenberg-Marquart back propagation algorithm (BP) and the sigmoid activation function are used to improve the performance of ANNs. The intelligent model shows the satisfactory performance with the error rate 1.24%, 1.03%, 0.87%, 1.17%, and 1.28% for electrodeposited MnO2 samples. (c) 2015 Elsevier Ltd. All rights reserved.
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