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Mesoscale simulations of controlled degradation of tetra-PEG hydrogels demonstrate that dynamic heterogeneity in these systems depends on relative extent of reaction and solvent quality. 

Abstract Polyolefins account for more than half of global primary polymer production, however only a small fraction of these polymers are currently being recycled. Fragmentation of polymer chains into shorter chains with a targeted molecular weight distribution with the goal of reusing these fragments in subsequent chemical synthesis can potentially introduce an alternative approach to polyolefins recycling. Herein we develop a mesoscale framework to model degradation of polyethylene melts at a range of high temperatures. We use the dissipative particle dynamics approach with modified segmental repulsive potential to model the process of random scission in melts of linear polymer chains. We characterize the fragmentation process by tracking the time evolution of the distribution of degrees of polymerization of chain fragments. Specifically, we track the weight average and the number average degrees of polymerization and dispersity of polymer fragments as a function of the fraction of bonds broken. Furthermore, we track the number fraction distribution and the weight fraction distribution of polymer fragments with various degrees of polymerization as functions of the fraction of bonds broken for a range of high temperatures. Our results allow one to quantify to what extent the distribution of polymer chain fragments during random scission can be captured by the respective analytical distributions for the range of conversions considered. Understanding the thermal degradation of polyolefins on the mesoscale can result in the development of alternative strategies for recycling a range of thermoplastics. 

Controlling morphology of polysiloxane blends crosslinked by the hydrosilylation reaction followed by pyrolysis constitutes a robust strategy to fabricate polymer-derived ceramics (PDCs) for a number of applications, from water purification to hydrogen storage. Herein, we introduce a dissipative particle dynamics (DPD) approach that captures the phase separation in binary and ternary polymer blends undergoing hydrosilylation. Linear polyhydromethylsiloxane (PHMS) chains are chosen as preceramic precursors and linear vinyl-terminated polydimethylsiloxane (v-PDMS) chains constitute the reactive sacrificial component. Hydrosilylation of carbon–carbon unsaturated double bonds results in the formation of carbon–silicon bonds and is widely utilized in the synthesis of organosilicons. We characterize the dynamics of binary PHMS/v-PDMS blends undergoing hydrosilylation and ternary blends in which a fraction of the reactive sacrificial component (v-PDMS) is replaced with the non-reactive sacrificial component (methyl-terminated PDMS (m-PDMS), polyacrylonitrile (PAN), or poly(methyl methacrylate) (PMMA)). Our results clearly demonstrate that the morphology of the sacrificial domains in the nanostructured polymer network formed can be tailored by tunning the composition, chemical nature, and the degree of polymerization of the sacrificial component. We also show that the addition of a non-reactive sacrificial component introduces facile means to control the self-assembly and morphology of these nanostructured materials by varying the fraction, degree of polymerization, or the chemical nature of this component. 

Abstract Controlled degradation of hydrogels enables several applications of these materials, including controlled drug and cell release applications and directed growth of neural networks. These applications motivate the need of a simulation framework for modeling controlled degradation in hydrogels. We develop a Dissipative Particle Dynamics (DPD) framework for hydrogel degradation. As a model hydrogel, we prepare a network formed by end-linking tetra-arm polyethylene glycol precursors. We model bond breaking during degradation of this hydrogel as a stochastic process. The fraction of degradable bonds follows first order degradation kinetics. We characterize the rate of mass loss during degradation process.