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Published in

MDPI, Materials, 3(14), p. 550, 2021

DOI: 10.3390/ma14030550

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Electrothermal Modeling and Analysis of Polypyrrole-Coated Wearable E-Textiles

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

The inhomogeneity of the resistance of conducting polypyrrole-coated nylon–Lycra and polyester (PET) fabrics and its effects on surface temperature were investigated through a systematic experimental and numerical work including the optimization of coating conditions to determine the lowest resistivity conductive fabrics and establish a correlation between the fabrication conditions and the efficiency and uniformity of Joule heating in conductive textiles. For this purpose, the effects of plasma pre-treatment and molar concentration analysis of the dopant anthraquinone sulfonic acid (AQSA), oxidant ferric chloride, and monomer pyrrole was carried out to establish the conditions to determine the sample with the lowest electrical resistance for generating heat and model the experiments using the finite element modeling (FEM). Both PET and nylon-Lycra underwent atmospheric plasma treatment to functionalize the fabric surface to improve the binding of the polymer and obtain coatings with reduced resistance. Both fabrics were compared in terms of average electrical resistance for both plasma treated and untreated samples. The plasma treatment induced deep black coatings with lower resistance. Then, heat-generating experiments were conducted on the polypyrrole (PPy) coated fabrics with the lowest resistance using a variable power supply to study the distribution and maximum value of the temperature. The joule heating model was developed to predict the heating of the conductive fabrics via finite element analysis. The model was based on the measured electrical resistance at different zones of the coated fabrics. It was shown that, when the fabric was backed with neoprene insulation, it would heat up quicker and more evenly. The average electrical resistance of the PPy-PET sample used was 190 Ω, and a maximum temperature reading of 43 °C was recorded. The model results exhibited good agreement with thermal camera data.