Guo Chao, Niu Yi
School of Materials Science and Engineering and Jiangsu Key Laboratory of Advanced Metallic Materials, Southeast University, Nanjing 211189, China.
ACS Biomater Sci Eng. 2019 Apr 8;5(4):1771-1783. doi: 10.1021/acsbiomaterials.9b00015. Epub 2019 Mar 20.
Biodegradability is a fundamental property of poly lactic acid (PLA). Numerous simulation algorithms based on reaction-diffusion model have been utilized to analyze the degradation behaviors of PLA. In the present work, a cellular automaton (CA) algorithm combined with an acceleratable reaction-diffusion model and coarse-grained kinetic Monte Carlo method is applied to simulate the degradation behaviors of PLA, such as random or end scission and crystallization of PLA chains, diffusion of soluble oligomers. The CA algorithm can reveal the global changes of molecular weight, mass, reaction number and soluble oligomer number generated by hydrolysis as well as the local distributions of molecular weight, soluble oligomer number and cellular state. The calculation result of experiment demonstrates that such a CA model can accurately simulate the change of molecular weight and mass loss simultaneously. The effects of hydrolysis mode, reaction rate constant, diffusion coefficient, device size and pore structure on the degradation behaviors of PLA especially the change in the molecular weight and the famous autocatalysis effect are comprehensively investigated. A novel classification method of molecular weight change curve is presented and the effects of various factors are concluded. In general, big reaction rate constant, small diffusion coefficient, big device size, solid or low porosity, and no or few initial soluble oligomers can more easily generate a type I curve, which corresponds to a strong autocatalysis hydrolysis.
生物降解性是聚乳酸(PLA)的一项基本特性。众多基于反应扩散模型的模拟算法已被用于分析PLA的降解行为。在当前工作中,一种结合了可加速反应扩散模型和粗粒度动力学蒙特卡洛方法的元胞自动机(CA)算法被应用于模拟PLA的降解行为,如PLA链的无规或端基断裂以及结晶、可溶性低聚物的扩散。CA算法能够揭示水解产生的分子量、质量、反应数和可溶性低聚物数的全局变化以及分子量、可溶性低聚物数和元胞状态的局部分布。实验计算结果表明,这样的CA模型能够同时准确模拟分子量变化和质量损失。全面研究了水解模式、反应速率常数、扩散系数、装置尺寸和孔结构对PLA降解行为的影响,尤其是分子量的变化以及著名的自催化效应。提出了一种新的分子量变化曲线分类方法并总结了各种因素的影响。一般来说,大的反应速率常数、小的扩散系数、大的装置尺寸、固体或低孔隙率以及无或少量初始可溶性低聚物更容易产生I型曲线,这对应于强自催化水解。