Designing Sequence-Specific Copolymer Compatibilizers Using a Molecular-Dynamics-Simulation-Based Genetic Algorithm

详细信息    查看全文

• 作者：Venkatesh Meenakshisundaram ; Jui-Hsiang Hung ; Tarak K. Patra ; David S. Simmons
• 刊名：Macromolecules
• 出版年：2017
• 出版时间：February 14, 2017
• 年：2017
• 卷：50
• 期：3
• 页码：1155-1166
• 全文大小：681K
• ISSN：1520-5835

文摘

Compatibilizers—surfactant molecules designed to improve the stability of an interface—are employed to enhance material properties in settings ranging from emulsions to polymer blends. A major compatibilization strategy employs block or random copolymers composed of distinct repeat units with preferential affinity for each of the two phases forming the interface. Here we pose the question of whether improved compatibilization could be achieved by employing new synthetic strategies to realize copolymer compatibilizers with specific monomeric sequence. We employ a novel molecular-dynamics-simulation-based genetic algorithm to design model sequence-specific copolymers that minimize energy of a polymer/polymer interface. Results indicate that sequence-specific copolymers offer the potential to yield larger reductions in interfacial energy than either block or random copolymers, with the preferred sequence being compatibilizer concentration dependent. By employing a simple thermodynamic scaling model for copolymer compatibilization, we pinpoint the origins of this sequence specificity and concentration dependence in the “loop entropy” of compatibilizer segments connecting interfacial bridge points. In addition to pointing toward a new strategy for improved interfacial compatibilization, this approach provides a conceptual basis for the computational design of a new generation of sequence-specific polymers leveraging recent and ongoing synthetic advances in this area.