Yi Xiong, Li Shengfang, Wen Pin, Yan Shilin
Hubei Key Laboratory of Theory and Application of Advanced Materials Mechanics, Wuhan University of Technology, Wuhan 430070, China.
School of Chemistry and Chemical Engineering, Hubei Polytechnic University, Huangshi 435003, China.
Polymers (Basel). 2024 Mar 22;16(7):873. doi: 10.3390/polym16070873.
Traditional polymer curing techniques present challenges such as a slow processing speed, high energy consumption, and considerable initial investment. Frontal polymerization (FP), a novel approach, transforms monomers into fully cured polymers through a self-sustaining exothermic reaction, which enhances speed, efficiency, and safety. This study focuses on acrylamide hydrogels, synthesized via FP, which hold significant potential for biomedical applications and 3D printing. Heat conduction is critical in FP, particularly due to its influence on the temperature distribution and reaction rate mechanisms, which affect the final properties of polymers. Therefore, a comprehensive analysis of heat conduction and chemical reactions during FP is presented through the establishment of mathematical models and numerical methods. Existing research on FP hydrogel synthesis primarily explores chemical modifications, with limited studies on numerical modeling. By utilizing Differential Scanning Calorimetry (DSC) data on the curing kinetics of polymerizable deep eutectic solvents (DES), this paper employs Malek's model selection method to establish an autocatalytic reaction model for FP synthesis. In addition, the finite element method is used to solve the reaction-diffusion model, examining the temperature evolution and curing degree during synthesis. The results affirm the nth-order autocatalytic model's accuracy in studying acrylamide monomer curing kinetics. Additionally, factors such as trigger temperature and solution initial temperature were found to influence the FP reaction's frontal propagation speed. The model's predictions on acrylamide hydrogel synthesis align with experimental data, filling the gap in numerical modeling for hydrogel FP synthesis and offering insights for future research on numerical models and temperature control in the FP synthesis of high-performance hydrogels.
传统的聚合物固化技术存在诸如加工速度慢、能源消耗高和初始投资大等挑战。前沿聚合(FP)是一种新颖的方法,它通过自维持放热反应将单体转化为完全固化的聚合物,从而提高了速度、效率和安全性。本研究聚焦于通过前沿聚合合成的丙烯酰胺水凝胶,其在生物医学应用和3D打印方面具有巨大潜力。热传导在前沿聚合中至关重要,特别是因为它对温度分布和反应速率机制有影响,而这些又会影响聚合物的最终性能。因此,通过建立数学模型和数值方法,对前沿聚合过程中的热传导和化学反应进行了全面分析。现有的关于前沿聚合水凝胶合成的研究主要探索化学改性,而对数值建模的研究有限。本文利用关于可聚合低共熔溶剂(DES)固化动力学的差示扫描量热法(DSC)数据,采用马利克的模型选择方法建立了前沿聚合合成的自催化反应模型。此外,使用有限元方法求解反应扩散模型,研究合成过程中的温度演变和固化程度。结果证实了n阶自催化模型在研究丙烯酰胺单体固化动力学方面的准确性。此外,发现引发温度和溶液初始温度等因素会影响前沿聚合反应的前沿传播速度。该模型对丙烯酰胺水凝胶合成的预测与实验数据相符,填补了水凝胶前沿聚合合成数值建模的空白,并为高性能水凝胶前沿聚合合成中数值模型和温度控制的未来研究提供了见解。