Zhang Xiangyu, Zong Jing, Meng Dong
The Swalm School of Chemical Engineering, Mississippi State University, Mississippi State, MS 39762, USA.
Soft Matter. 2020 Aug 26;16(33):7789-7796. doi: 10.1039/d0sm00811g.
The standard random phase approximation (RPA) model is applied to investigate the cononsolvency of polymers in mixtures of two good solvents. It is shown that in the RPA framework, the two types of cononsolvency behaviors reported in previous theoretical studies can be unified under the same concept of mean-field density correlations. The two types of cononsolvency are distinguished by the solvent composition at which maximum immiscibility is predicted to occur. The maximum immiscibility occurs with the cosolvent being the minor solvent if the driving mechanism is the preferential solvation of polymers. For the cononsolvency driven by the preferential mixing of solvents, the maximum immiscibility is predicted at a symmetric solvent composition. An interplay of the two driving forces gives rise to a reentrant behavior in which the cononsolvency of the two types switches from one to the other, through a "conventional" region where the overall solvent quality varies monotonically with the solvent composition. The RPA model developed in this work provides a unified analytical framework for understanding the conformational and solubility transition of polymers in multi-solvent mixtures. Such findings highlight the complex role played by the solvents in polymer solutions, a problem of fundamental and practical interest in diverse applications of materials science.
应用标准随机相位近似（RPA）模型研究聚合物在两种良溶剂混合物中的共溶现象。结果表明，在RPA框架下，先前理论研究中报道的两种共溶行为可以在平均场密度关联的相同概念下统一起来。这两种共溶类型的区别在于预测发生最大不混溶性时的溶剂组成。如果驱动机制是聚合物的优先溶剂化，则当共溶剂为次要溶剂时会出现最大不混溶性。对于由溶剂的优先混合驱动的共溶现象，预测在对称溶剂组成下会出现最大不混溶性。两种驱动力的相互作用导致一种折返行为，即两种类型的共溶现象通过一个“常规”区域从一种转变为另一种，在该区域中整体溶剂质量随溶剂组成单调变化。本文开发的RPA模型为理解聚合物在多溶剂混合物中的构象和溶解度转变提供了一个统一的分析框架。这些发现突出了溶剂在聚合物溶液中所起的复杂作用，这是材料科学各种应用中一个具有根本和实际意义的问题。
