Structure formation in binary polymer systems: Short-time dynamics and dynamics of crosslinked systems

by Gaoyuan Wang
Doctoral thesis
Date of Examination:2021-09-22
Date of issue:2022-07-27
Advisor:Prof. Dr. Marcus Müller
Referee:Prof. Dr. Marcus Müller
Referee:Prof. Dr. Reiner Kree
Persistent Address: http://dx.doi.org/10.53846/goediss-9379

 

 

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Abstract

English

Structure evolution in multicomponent polymer melts and in their network equivalents is investigated. In the first part, particle-based simulations reveal that on short length and time scales, the collective kinetics of structure formation and relaxation of polymeric systems is influenced by the sub-diffusive single-chain dynamics. D-RPA and D-SCFT are employed to describe the collective behavior in the simulation. D-RPA successfully captures the observed time evolution of density fluctuations on short time scales, whereas D-SCFT fails to provide an appropriate description on time scales much shorter than the Rouse relaxation time. In addition, a modified D-SCFT that accounts for the non-locality of Onsager coefficient in time is developed. In the second part, the structure and structure formation in 2D networks with a fixed topology and in 3D randomly crosslinked networks made of symmetric diblock copolymers are studied combining analytical approaches and particle-based simulations. The phase behavior of 2D regular networks comprised of square-shaped unit cells is found to depend strongly on the side lengths of the unit cells measured in the unit of the end-to-end distance of the constituent polymer strands and the number of unit cells belonging to the network. In 3D random networks, the crosslinks stabilize and partially memorize the structure existing at the time of their formation. The phase behavior of random networks is determined by the crosslink density and the strength of the repulsion between unlike species at crosslinking.
Keywords: self-consistent field theory; statistical physics; polymer networks; polymer physics; random phase approximation; coarse-grained particle simulation
 
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