Ghost‐Mirror Approach for Accurate and Efficient Kinetic Monte Carlo Simulation of Seeded Emulsion Polymerization

The kinetic Monte Carlo (kMC) method is well suited to the simulation of seeded emulsion polymerization reactions. Inadequate simulation volume results in an incorrect radical entry rate, and as such that inaccuracy propagates into the particle phase simulation. A novel kMC method is described here that has coined the Ghost‐Mirror approach (GM‐kMC) to guarantee sufficient aqueous phase simulation volume while minimizing the number of dispersed phase environments, and while maintaining accuracy and consistency with results produced by kMC simulations. To do so, a subset of a kMC method is replicated where only the aqueous phase reactions are treated in that extended volume; particle phases in those replicated volumes are untreated, as “ghosts”. In doing so, a critical condition for aqueous phase simulation volume is calculated to yield accurate results in the overall system. Important to emphasize though is that one does not require the equivalent number of simulated particles in the GM‐kMC approaches. The required number of particles to simulate accurate results can be even orders of magnitude smaller than the kMC approach; inherently offering significant gains in computational efficiency. This is extended further, reducing the required simulation time, by a hybrid extension to this GM‐kMC method. A modification to the kinetic Monte Carlo algorithm is demonstrated to extend the aqueous phase simulation volume for seeded emulsion polymerization with deliberate neglect of “ghosted” dispersed phase particles. This ensures a minimum simulation volume required to match output of that or beyond a threshold of particle number whereby the results stabilize, with orders of magnitude shorter computational time.