TY - GEN
T1 - The modified logistic model for polymer-composites electrical conductivity prediction
AU - Folorunso, Oladipo
AU - Hamam, Yskandar
AU - Sadiku, Rotimi
AU - Ray, Suprakas Sinha
AU - Joseph, Adekoya Gbolahan
N1 - Publisher Copyright:
© 2020 American Institute of Physics Inc.. All rights reserved.
PY - 2020/11/26
Y1 - 2020/11/26
N2 - The discrepancies in the parameters that best predict the electrical conductivity of polymer-composite materials (PcM) are great challenges confronting the practical applications of some of these materials. Modeling approach, by using some set of mathematical equations, which incorporate various composite materials parameters, is a good step to predict the electrical conductivity of polymers and their composites. The synergetic loading effect of additives on polymers cannot be effectively predicted via experimentation. This is because the properties of materials change when they are subjected to temperature differential and some other mechanical factors. Consequently, this study further looks into the logistic model (MLM) for the prediction of electrical conductivity of PcM. The logistic model is an exponential function, which models the growth and decay of fillers, loaded on the polymers. The model is tested on various composites that are relevant for application in electrochemical energy storage. More so, the model considered the saturation point of the composites and the volume fraction of the inclusions in order to predict electrical conductivity of different polymer composites.
AB - The discrepancies in the parameters that best predict the electrical conductivity of polymer-composite materials (PcM) are great challenges confronting the practical applications of some of these materials. Modeling approach, by using some set of mathematical equations, which incorporate various composite materials parameters, is a good step to predict the electrical conductivity of polymers and their composites. The synergetic loading effect of additives on polymers cannot be effectively predicted via experimentation. This is because the properties of materials change when they are subjected to temperature differential and some other mechanical factors. Consequently, this study further looks into the logistic model (MLM) for the prediction of electrical conductivity of PcM. The logistic model is an exponential function, which models the growth and decay of fillers, loaded on the polymers. The model is tested on various composites that are relevant for application in electrochemical energy storage. More so, the model considered the saturation point of the composites and the volume fraction of the inclusions in order to predict electrical conductivity of different polymer composites.
UR - http://www.scopus.com/inward/record.url?scp=85098209646&partnerID=8YFLogxK
U2 - 10.1063/5.0028263
DO - 10.1063/5.0028263
M3 - Conference contribution
AN - SCOPUS:85098209646
T3 - AIP Conference Proceedings
BT - Proceedings of PPS2019, Europe-Africa Regional Conference of the Polymer Processing Society
A2 - Ray, Suprakas Sinha
PB - American Institute of Physics Inc.
T2 - PPS Europe-Africa 2019 Regional Conference, PPS 2019
Y2 - 18 November 2019 through 22 November 2019
ER -