Li Yinghao, Yin Hang, Situ Yi, Lyu Jing, Wang Wenxin
Charles Institute of Dermatology, School of Medicine, University College Dublin, Dublin 4, Ireland.
Sci Adv. 2025 May 9;11(19):eadu8884. doi: 10.1126/sciadv.adu8884.
Step-growth polymerization (SGP) products are ubiquitous, but the theoretical understanding of SGP reactions has stagnated since the introduction of Flory's classical theory. Flory's model based on two key assumptions-equal reactivity of functional groups and the absence of cyclization-falls short in guiding real-world polymerization processes. In this work, we extend Flory's model by accounting for individual reaction probabilities and cyclization tendencies, making it applicable to real SGP situations. Moreover, we have developed a top-down algorithm capable of extracting crucial information about polymer growth and cyclization from molecular weight data during the SGP process. By applying this expanded model to real SGP experiments, we reveal their kinetic mechanisms and demonstrate how concentration affects polymerization kinetics, offering valuable insights for predicting and controlling the polymer structure.
逐步增长聚合(SGP)产物无处不在,但自弗洛里经典理论提出以来,对SGP反应的理论理解一直停滞不前。弗洛里模型基于两个关键假设——官能团的等活性和无环化现象——在指导实际聚合过程方面存在不足。在这项工作中,我们通过考虑单个反应概率和环化趋势扩展了弗洛里模型,使其适用于实际的SGP情况。此外,我们开发了一种自上而下的算法,能够从SGP过程中的分子量数据中提取有关聚合物生长和环化的关键信息。通过将这个扩展模型应用于实际的SGP实验,我们揭示了它们的动力学机制,并展示了浓度如何影响聚合动力学,为预测和控制聚合物结构提供了有价值的见解。