Computational Design of Photocured Polymers Using Stochastic Reaction–Diffusion Simulation. Issue 7 (11th May 2018)

• Record Type: Journal Article
• Authors: Sarkar, Swarnavo; Lin‐Gibson, Sheng
• Is Part Of: Advanced theory and simulations. Volume 1:Issue 7(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-05-11
• Subjects: disorder -- modeling -- phonons -- polymers -- reaction–diffusion; Science -- Simulation methods -- Periodicals; Science -- Methodology -- Periodicals; Engineering -- Simulation methods -- Periodicals; Engineering -- Methodology -- Periodicals; 507.21
• DOI: 10.1002/adts.201800028
• Languages: English
• ISSNs: 2513-0390

Abstract

Abstract: Photopolymerization is widely used for creating materials for biomedical applications, lithography, and fast 3D fabrication. The resin composition and curing protocol during polymerization define a high‐dimensional parameter space that dictates the reaction kinetics, network structures, and physical properties of polymerized materials. But a quantitative map from the input parameter space to the transient and final properties does not exist. Here, a computational method is presented to simulate network growth as a stochastic process using reaction‐diffusion master equations. The evolving diffusivity of reacting species during polymerization is modeled using effective medium method, thereby making the rates of reaction and fluctuation events sensitive to the spatial configuration of a growing network. The numerical studies show that this method can correlate fabrication parameters to polymer properties like crosslink heterogeneity, relaxation time, phonon density of states, and bulk modulus, in silico. Hence, stochastic simulation of polymerization is broadly applicable to accelerate the design of polymeric materials with targeted physical properties for specific applications. Abstract : Competition between network growth, crosslinking, and fluctuation determines the spatial configuration of a polymer network during polymerization. In this study, stochastic simulation is used to determine the kinetics of polymerization as a function of composition and curing protocol. This method enables mapping of fabrication parameters to a coarse‐grained network configuration, which is useful to determine polymer properties.