A Particle-Field Hybrid Simulation Method for Studying Strong Correlations In Polymeric Systems

Friday, August 25, 2017

Dr. Dong Meng

Department of Chemical Engineering

Mississippi State University

Hand Lab 1144, 3:30 P.M.dg

The presence of a small amount of strongly correlated interactions in polymeric materials, such as hydrogen bonding, ionomers, and coordinative bonds, can drastically alter materials’ mesoscale structural and dynamical properties. Examples include supramolecular polymeric assemblies and micro-phase separation of ion-containing block copolymers, etc. Understanding of such materials demands computational methods that can faithfully capture strongly correlated interactions, and have also access to materials’ mesoscopic behaviors. Among existing mesoscopic approaches, particle-based methods tend to be highly computationally demanding, while field-based methods do not explicitly describe pair level interactions and tend to undercount essential correlations and fluctuations. With these limitations in mind, here we propose a new simulation formalism that is based on expanding the single chain in mean field (SCMF) scheme [1]. As a hybrid particle-field method, the new formalism offers the degree of freedom of separating interactions into those to be treated using mean-field representations, and those to be preserved in particle-based representations. By doing so, the formalism combines the strength of both approaches in efficient calculation of interactions in dense systems, while being able to capture correlation and fluctuation effects due to interactions in particle-based representations. We illustrate the approach in the context of two examples, namely, gelation transition in a dilute polymer solution with explicit solvent, and network association in a dense polymer melt. The accuracy and computational advantage of the new formalism are assessed by direct comparisons with Monte Carlo simulations.


Dr. Meng joined the Swalm School of Chemical Engineering of Mississippi State University as an assistant professor at 2015. He received his PhD in Chemical Engineering from Colorado State University, with a research focused on studying micro-phase separation of block copolymers using self-consistent field theory. After graduation, Dr. Meng made a brief stop at University of California (at Riverside), developing classical density functional theories for modeling complexation of polyelectrolytes, before joining the department of chemical engineering of Columbia University as a post doc researcher with a research focus on simulating structural and mechanical properties of polymer nanocomposite materials. At Mississippi State University Dr. Meng’s research focuses on developing molecular theories and theory-informed simulation methods for studying structural and dynamical properties of supramolecular polymer networks.



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