Abstract
Molecular recognition is essential for the advancement of functional supramolecular natural polymer-based hydrogels. First, a series of carboxymethyl cellulose (CMC)-chitosan (CSN) hydrogels crosslinked with fumaric acid are studied, where the influence of composition on microstructure and swelling is investigated using mathematical modelling and experiment and the hydrolytic properties, microstructure parameters and physicochemical properties are examined. Second, best fit values for the responses are obtained using multiple linear regression and MATLAB R2020a curve fitting and predictive models are generated. Third, the optimum microstructure is loaded with polyethylene glycol (PEG) and bismuth telluride (Bi2Te3) and coated on fabric for imparting thermal sensitivity. The results show that (1) optimum microstructure (25.65 ± 1.86 nm mesh size, 116.25 ± 0.00 μmol/cm3 effective crosslinking-density, 348.03 ± 10.81% swelling, and 62.86 ± 1.11% gel fraction) is found at CMC:CSN = 1:3 for G3; (2) the model shows good agreement with experimental data demonstrating potential for estimating hydrogel swelling and microstructure; and (3) G3/PEG and G3/PEG/Bi2Te3 enhance thermal conductivity of fabric at ambient, body, and elevated temperatures. The study demonstrates the potential of the generated model in predicting CMC-CSN swelling and G3 as an ideal host matrix for wearable textiles/devices.
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