Practical Prediction of Heteropolymer Composition and Drift
Practical Prediction of Heteropolymer Composition and Drift
复制标题
杂聚物组成和漂移的实际预测
DOI：
10.1021/acsmacrolett.8b00813
复制
发表时间：
2018
影响因子：
7.015
通讯作者：
Xu, Ting
中科院分区：
文献类型：
--
作者：
Smith, Anton A.;Hall, Aaron;Wu, Vincent;Xu, Ting
在间歇聚合中，组分漂移是一种众所周知的现象，它会导致使用可控聚合方法合成的聚合物中的组分梯度。在已知单体反应性比的情况下，可以通过调整试剂比例和目标转化率来设计漂移和由此产生的梯度共聚物。虽然这样的预测是直接的，但很少有人这样做，可能是由于非专业人士认为困难和不熟悉。我们试图通过为使用共聚物的社区提供一个易于使用的程序来解决这个问题，该程序称为composition Drift，该程序基于Mayo-Lewis模型和第二个单体添加模型，使用蒙特卡罗方法。该工具也可用于预测非漂移聚合的组成。在此，我们向社区提供了这个工具，展示了两个最近使用的例子，以指导实验设计和理解杂多聚物（RHP）。
Composition drift in batch polymerizations is a well-known phenomenon and can lead to composition gradients in polymers synthesized using controlled polymerization methodologies. With known reactivity ratios of monomers, the drift, and thus resultant gradient copolymer, can be designed by adjusting reagent ratios and targeted conversions. Although such prediction is straightforward, it is seldom done, likely due to the perceived difficulty and unfamiliarity for nonspecialists. We seek to remedy this by providing the communities using copolymers with an easy-to-use program called Compositional Drift which is based on the Mayo–Lewis model and the penultimate model of monomer addition, using Monte Carlo methodology. This tool can also be applied to predict composition in nondrifting polymerizations. Herein we supply this tool to the community, showcasing two recent examples of use to guide experimental design and understanding of heteropolymers (RHP).