Wen Chengyuan, Odle Roy, Cheng Shengfeng
Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province, School of Information Engineering, Zhejiang Ocean University, Zhoushan 316022, China.
Department of Physics, Center for Soft Matter and Biological Physics, and Macromolecules Innovation Institute, Virginia Tech, Blacksburg, VA 24061, USA.
Polymers (Basel). 2023 Apr 4;15(7):1791. doi: 10.3390/polym15071791.
It is challenging to predict the molecular weight distribution (MWD) for a polymer with a branched architecture, though such information will significantly benefit the design and development of branched polymers with desired properties and functions. A Monte Carlo (MC) simulation method based on the Gillespie algorithm is developed to quickly compute the MWD of branched polymers formed through step-growth polymerization, with a branched polyetherimide from two backbone monomers (4,4'-bisphenol A dianhydride and m-phenylenediamine), a chain terminator (phthalic anhydride), and a branching agent (tris[4-(4-aminophenoxy)phenyl] ethane) as an example. This polymerization involves four reactions that can be all reduced to a condensation reaction between an amine group and a carboxylic anhydride group. A comparison between the MC simulation results and the predictions of the Flory-Stockmayer theory on MWD shows that the rates of the reactions are determined by the concentrations of the functional groups on the monomers involved in each reaction. It further shows that the Flory-Stockmayer theory predicts MWD well for systems below the gel point but starts to fail for systems around or above the gel point. However, for all the systems, the MC method can be used to reliably predict MWD no matter if they are below or above the gel point. Even for a macroscopic system, a converging distribution can be quickly obtained through MC simulations on a system of only a few hundred to a few thousand monomers that have the same molar ratios as in the macroscopic system.
预测具有支化结构的聚合物的分子量分布(MWD)具有挑战性,尽管此类信息将极大地有助于设计和开发具有所需性能和功能的支化聚合物。本文开发了一种基于 Gillespie 算法的蒙特卡罗(MC)模拟方法,用于快速计算通过逐步增长聚合形成的支化聚合物的 MWD,以由两种主链单体(4,4'-双酚 A 二酐和间苯二胺)、一种链终止剂(邻苯二甲酸酐)和一种支化剂(三[4-(4-氨基苯氧基)苯基]乙烷)形成的支化聚醚酰亚胺为例。该聚合反应涉及四个反应,这些反应均可简化为胺基与羧酸酐基之间的缩合反应。MC 模拟结果与 Flory-Stockmayer 理论对 MWD 的预测之间的比较表明,反应速率由每个反应中涉及的单体上的官能团浓度决定。进一步表明,Flory-Stockmayer 理论对于低于凝胶点的体系能很好地预测 MWD,但对于接近或高于凝胶点的体系开始失效。然而,对于所有体系,无论其低于还是高于凝胶点,MC 方法都可用于可靠地预测 MWD。即使对于宏观体系,通过对仅几百到几千个具有与宏观体系相同摩尔比的单体组成的体系进行 MC 模拟,也能快速获得收敛分布。