School of Energy and Environment, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong.
School of Energy and Environment, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong.
Int J Biol Macromol. 2021 Jun 30;181:1010-1022. doi: 10.1016/j.ijbiomac.2021.04.117. Epub 2021 Apr 20.
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 (BiTe) 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/cm 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/BiTe 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.
分子识别对于功能超分子天然聚合物水凝胶的发展至关重要。首先,研究了一系列用富马酸交联的羧甲基纤维素(CMC)-壳聚糖(CSN)水凝胶,通过数学建模和实验研究了组成对微观结构和溶胀的影响,并考察了水解性能、微观结构参数和物理化学性质。其次,使用多元线性回归和 MATLAB R2020a 曲线拟合获得了响应的最佳拟合值,并生成了预测模型。然后,将最佳微观结构与聚乙二醇(PEG)和碲化铋(BiTe)负载并涂覆在织物上,以赋予其热敏感性。结果表明:(1)在 CMC:CSN = 1:3 时,G3 的最佳微观结构(25.65 ± 1.86nm 网格尺寸、116.25 ± 0.00μmol/cm 的有效交联密度、348.03 ± 10.81%的溶胀率和 62.86 ± 1.11%的凝胶分数);(2)模型与实验数据吻合较好,表明其具有估计水凝胶溶胀和微观结构的潜力;(3)G3/PEG 和 G3/PEG/BiTe 提高了织物在环境、人体和升高温度下的导热性。该研究表明,所生成模型在预测 CMC-CSN 溶胀和 G3 作为可穿戴纺织品/器件的理想宿主基质方面具有潜力。