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

delete2017-01-13
delete67
PRE
AI
V
V. Meenakshisundaram
J
Jui‐Hsiang Hung
T
Tarak K. Patra
D
David Simmons *
DOI:10.1021/acs.macromol.6b01747delete
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Abstract

Abstract

En 中文
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.
Keywords:
REACTIVE COMB POLYMERS
SELF-CONSISTENT-FIELD
NEURAL-NETWORKS
PATTERN-RECOGNITION
RANDOM HETEROPOLYMERS
SECONDARY STRUCTURE
BLOCK-COPOLYMERS
T-G
BLENDS
INTERFACES
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Macromolecules cover
Macromolecules
IF:
5.2
Papers:
3.7W
Citations:
9.4W

Organization

U
University System of Ohio
Scholars:
15.5W
Papers: 13.0W
Citations: 200
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