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| Modeling the morphology development in latex particles as well as the branching of polymers, are of great interest to practitioners, since they determine the resulting performance of synthetic latex polymers.
We present two novel modeling methodologies. While using different levels of detail, both of them are able to reproduce experimental observations.
Our high resolution approach for modeling the dynamics of particle morphology development in the composite waterborne systems is based on stochastic dynamics. It utilizes Langevin dynamics for predicting non-equilibrium morphologies for various technological conditions, and uses the generalized shadow hybrid Monte Carlo technique for faster identification of equilibrium morphologies. The model takes into account the effects of phase compatibility and internal viscosity of the particles, and provides a detailed description of the morphology of a single particle.
For modeling the branching mechanism in control radical polymerization, we developed the delayed stochastic simulation algorithm, which operates with molecular numbers rather than with individual molecules, as does the high resolution approach. The algorithm has been successfully tested on simple exactly solvable models.
The predictions obtained with both approaches closely reproduce experimental results.
The possibilities for combining two approaches in the multi-scale stochastic modeling method are discussed. |
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