Kinetic modeling of simultaneous polycondensation and free radical polymerization for polyurethane/poly(methyl methacrylate) interpenetrating polymer network

Abstract

A comprehensive kinetic Monte Carlo algorithm has been developed to investigate the formation process of a polyurethane/poly(methyl methacrylate) (PU/PMMA) interpenetrating polymer network (IPN), in which a component independent strategy is proposed to perform the simulation of simultaneous polycondensation and free radical polymerization. An empiric diffusion model based on the mass fraction of polymer is used to quantify the effect of diffusional limitations on MMA polymerization. Results show that the presence of acrylic monomers has little impact on the formation rate of PU, but the presence of the PU network can accelerate the polymerization of MMA. In addition, the effects of component mass ratio, acrylic cross-linker concentration, and [NCO]/[OH] ratio on the IPN formation kinetics are investigated based on the kinetic model. It is believed that the as-developed modeling strategy can be extended to other IPN systems and provide a better understanding of the interactions between chemically independent networks.

Toward an Automated Convergence Tool for Kinetic Monte Carlo Simulation of Conversion, Distributions, and Their Averages in Non-dispersed Phase Linear Chain-Growth Polymerization

“…Several PRE discriminants can be used to model the (reactive) macrospecies, namely, the chain length, the branch structure and location, or the chemical composition . Notorious examples of (non-dispersed) polymerization processes that can be simulated by k MC algorithms are free radical polymerization (FRP), − atom-transfer radical polymerization, − addition–fragmentation chain-transfer polymerization, , nitroxide-mediated polymerization (NMP), − and (pseudo-homogeneous) network polymer synthesis. ,, …”

“…7 Notorious examples of (non-dispersed) polymerization processes that can be simulated by kMC algorithms are free radical polymerization (FRP), 14−17 atom-transfer radical polymerization, 18−20 addition−fragmentation chaintransfer polymerization, 21,22 nitroxide-mediated polymerization (NMP), 23−26 and (pseudo-homogeneous) network polymer synthesis. 8,27,28 The main part of the algorithm for SSA-based kMC simulations includes a loop in which a stochastic time step is sampled, and the probabilities to select so-called reaction channels are calculated based on the number of molecules present in the (MC) control volume during each iteration of the loop. Additionally, if distributed species are involved, a weighted sampling must be executed to select the discriminator values.…”

Simulation time analysis of kinetic Monte Carlo algorithmic steps for basic radical (de)polymerization kinetics of linear polymers

“…[46][47][48] The field of polymer reaction engineering (PRE), being the application area in the present work, is a fertile ground to apply kMC algorithms as well, as polymerization kinetics are affected by variations in chain length, chemical composition, and branch location, and, hence, the polymeric macroscopic properties are affected by distributed macromolecular features. 15,[49][50][51] The kMC algorithm has been successfully applied, for instance for free radical polymerization (FRP), [52][53][54][55][56] reversible deactivation radical polymerization (RDRP), 57,58 including atom transfer radical polymerization (ATRP), [59][60][61][62] reversible addition-fragmentation chain transfer polymerization (RAFT), 4,63,64 and nitroxide mediated polymerization (NMP), 65,66 surface-initiated polymerization (SIP), 67 radical photopolymerization, 68,69 network polymer synthesis, 51,70,71 (radical) depolymerization, [72][73][74] and multi-compartment polymerization. [75][76][77] In general, kMC algorithms sample (reaction) events in (bio) chemical processes through three main steps: (i) the calculation of the probabilities of all these events at a given time, (ii) the sampling of the (reaction) event and its reactants or species involved, to be executed at a priorly sampled stochastic time step, and (iii) the updating of the state of the chemical system.…”

“…The field of polymer reaction engineering (PRE), being the application area in the present work, is a fertile ground to apply k MC algorithms as well, as polymerization kinetics are affected by variations in chain length, chemical composition, and branch location, and, hence, the polymeric macroscopic properties are affected by distributed macromolecular features. 15,49–51 The k MC algorithm has been successfully applied, for instance for free radical polymerization (FRP), 52–56 reversible deactivation radical polymerization (RDRP), 57,58 including atom transfer radical polymerization (ATRP), 59–62 reversible addition–fragmentation chain transfer polymerization (RAFT), 4,63,64 and nitroxide mediated polymerization (NMP), 65,66 surface-initiated polymerization (SIP), 67 radical photopolymerization, 68,69 network polymer synthesis, 51,70,71 (radical) depolymerization, 72–74 and multi-compartment polymerization. 75–77…”

Influencing Molecular Dynamics Simulations of Ion-Exchange Membranes by Considering Comonomer Propagation

“…The formation of cross-linked polymers fundamentally represents step-growth polymerization, in which multiple reactions between different types of monomers occur simultaneously, with some growing polymer chains capable of undergoing intramolecular transformations by bridging these chains via chemical bonding. , The step-growth process is very complex to study as one must account for every possible reaction in the system simultaneously. One of the most popular approaches to achieve this is via kinetic modeling that either considers polymerization via graph theory or relies on kinetic theory that describes the polymer growth via kinetic equations and accounts for diffusion control. , Many kinetic studies have been developed to analyze the extent of inter- and intramolecular reactions on the formation of cross-linked polymer networks and hence the influence of the kinetics of these complex reactions on the resulting bulk properties of such networks. − Graph theory has also been explored in identifying possible structures of polymer networks based on the topological information and atom connectivity of monomers and cross-linkers used. − Kinetic Monte Carlo simulations have been very popular in the last decade due to the rise of computer power. ,,− These simulations tend to be highly system-specific to tailor to a particular polymer chemistry, and due to the presence of multiple branches and functional groups, the complete relaxation of the polymer network may not be achieved during the simulation time, which relates to the ergodicity problem relevant to Monte Carlo simulations in general . Other methods to determine the polymer structure exist and should be noted.…”