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Ghost‐Mirror Approach for Accurate and Efficient Kinetic Monte Carlo Simulation of Seeded Emulsion Polymerization
Author(s) -
Tripathi Amit K.,
Tsavalas John G.
Publication year - 2020
Publication title -
macromolecular theory and simulations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.37
H-Index - 56
eISSN - 1521-3919
pISSN - 1022-1344
DOI - 10.1002/mats.202070009
Subject(s) - emulsion polymerization , monte carlo method , polymerization , kinetic energy , seeding , phase (matter) , particle (ecology) , emulsion , kinetic monte carlo , excluded volume , statistical physics , aqueous solution , volume (thermodynamics) , materials science , chemistry , physics , thermodynamics , mathematics , classical mechanics , quantum mechanics , polymer , nuclear magnetic resonance , biochemistry , statistics , oceanography , geology
Front Cover : A modification to the kinetic Monte Carlo (kMC) algorithm is demonstrated, coined the Ghost‐Mirror ( GM‐kMC ) approach , to specifically extend the aqueous phase simulation volume for seeded emulsion polymerization with deliberate neglect of ‘ghosted’ dispersed phase particles in that extension. In the graphic, one zone is fully treated with Np = 3, where the aqueous phase simulation volume is extended to represent an effective Np = 27. The approach ensures a minimum simulation volume required to match kMC output of that or beyond a threshold of particle number whereby the results stabilize, with orders of magnitude shorter computational time. This is reported by Amit K. Tripathi, John G. Tsavalas in article 2000033.