(183g) The Stochastic Simulation of Isocyanate Amine Polymerization

The isocyanate amine reactions are used to produce various polyurea products which have important industrial uses. By varying isocyanate and amine types and ratios one could produce polyurea products which have range of functionalities. In this study, we developed a stochastic simulation algorithm to simulate isocynate amine polymerization reaction to predict molecular weight distribution of the final polyurea product. The developed algorithm accurately predicts the molecular weight distribution without requiring any experimental data and can help to synthesize new formulation by providing fast and accurate way of searching wide ranges of reactant ratios.  The algorithm uses exact kinetic Monte Carlo simulation method where the reaction and the time between reaction events are sampled explicitly from calculated reaction probabilities. This method consider the time evalution of the species concentration as a random Markov Chain process where the propabilities of the reaction depends only the current state of the system. The new molecules are created and used-up molecules are destroyed dynamically so that large polymerization reaction network can be simulated efficiently both in terms of memory and computational time. We used the developed algorithm to simulate diamine/diisocyanate/monoamine polymerization. The linear polymerization, termination and cycle formation of dual functional molecules are included in the reaction network. The result of the algorithm showed good agreement with the matrix-assisted laser desorption/ionization (MALDI) measurements.