A new approach to understanding the interaction effect of salt and plasticizer on solid polymer electrolytes using statistical model and artificial intelligence algorithm

Adam, A.A. and Soleimani, H. and Shukur, M.F.B.A. and Dennis, J.O. and Abdulkadir, B.A. and Hassan, Y.M. and Yusuf, J.Y. and Shamsuri, N.A.B. (2022) A new approach to understanding the interaction effect of salt and plasticizer on solid polymer electrolytes using statistical model and artificial intelligence algorithm. Journal of Non-Crystalline Solids, 587.

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Abstract

Nowadays, solid polymer electrolytes (SPEs) based on natural biopolymeric macromolecules such as cellulose and its derivatives have demonstrated great potential over their synthetic counterparts due to their natural abundance, low cost of production, biocompatibility, and biodegradability. However, the low ionic conductivity of these polymers has been a serious challenge and needs to be optimized to meet demands for practical applications. Herein, the response surface methodology (RSM) and artificial neural network (ANN) were employed to predict and optimize the performance of pectin/methylcellulose (PC/MC) based SPE complexed with potassium phosphate (K3PO4) and glycerol. RSM analysis of variance (ANOVA) revealed that the interactive behaviour of both K3PO4 and glycerol, particularly at higher potassium salt content has an enormous influence on ionic conductivity and potential window of the SPE. After numerical optimization, an optimum interaction (�3 � 10�4 Scm�1, 4.19 V) was achieved at 60 wt. and 41.37 wt. of K3PO4 and glycerol respectively. © 2022

Item Type: Article
Impact Factor: cited By 1
Uncontrolled Keywords: Analysis of variance (ANOVA); Biocompatibility; Biodegradability; Biodegradable polymers; Biopolymers; Glycerol; Ionic conductivity; Neural networks; Optimization; Polyelectrolytes; Potassium compounds, Artificial intelligence algorithms; Cost of productions; Interaction effect; Low-costs; MC; Natural abundance; New approaches; Response-surface methodology; Solid polymer electrolytes; Statistic modeling, Solid electrolytes, Biodegradability; Glycerol; Neural Networks; Optimization; Polyelectrolytes; Potassium Compounds
Depositing User: Ms Sharifah Fahimah Saiyed Yeop
Date Deposited: 09 Jun 2022 07:47
Last Modified: 09 Jun 2022 07:47
URI: http://scholars.utp.edu.my/id/eprint/33037

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