Lv Yisheng, Wang Liquan, Liu Fan, Feng Weisheng, Wei Jie, Lin Shaoliang
Shanghai Key Laboratory of Advanced Polymeric Materials, State Key Laboratory of Bioreactor Engineering, Key Laboratory for Ultrafine Materials of Ministry of Education, School of Materials Science and Engineering, East China University of Science and Technology, Shanghai 200237, China.
Soft Matter. 2020 Apr 8;16(14):3466-3475. doi: 10.1039/d0sm00244e.
Polymerization-induced self-assembly (PISA), incorporating the polymerization with in situ self-assembly, can achieve nano-objects efficiently. However, the cooperative polymerization and self-assembly lead to unclear polymerization kinetics and aggregation behavior, especially for the systems forming rigid chains. Here, we used dissipative particle dynamics simulations with a probability-based reaction model to explore the PISA behavior of rod-coil block copolymer systems. The impact of the length of macromolecular initiators, the targeted length of rigid chains, and the reaction probability on the PISA behavior, including polymerization kinetics and self-assembly, were examined. The difference between PISA and traditional self-assembly was revealed. A comparison with experimental observations shows that the simulation can capture the essential feature of the PISA. The present work provides a comprehensive understanding of rod-coil PISA systems and may provide meaningful information for future experimental research.
聚合诱导自组装（PISA）将聚合反应与原位自组装相结合，能够高效地制备纳米物体。然而，协同聚合和自组装导致聚合动力学和聚集行为不明确，尤其是对于形成刚性链的体系。在此，我们使用基于概率反应模型的耗散粒子动力学模拟来探究棒-线圈嵌段共聚物体系的PISA行为。研究了大分子引发剂长度、刚性链目标长度和反应概率对PISA行为（包括聚合动力学和自组装）的影响。揭示了PISA与传统自组装之间的差异。与实验观察结果的比较表明，该模拟能够捕捉PISA的基本特征。本工作提供了对棒-线圈PISA体系的全面理解，并可能为未来的实验研究提供有意义的信息。
