Chain‐by‐Chain Monte Carlo Simulation: A Novel Hybrid Method for Modeling Polymerization. Part I. Linear Controlled Radical Polymerization Systems

Kinetic Monte Carlo (kMC) simulation is available for simulating microstructure of polymer chains with as much detail as one seeks at the expense of convergence tests and computational costs. A new hybrid deterministic–probabilistic method is developed as an alternative to kMC that builds chains one‐by‐one or chain‐by‐chain and it is named “Chain‐by‐Chain Monte Carlo” method (CBC‐MC). The CBC‐MC algorithm is tested on the synthesis of styrene/methyl methacrylate linear gradient copolymers via nitroxide‐mediated polymerization and methyl methacrylate/methyl acrylate linear hyperbolic gradient copolymers via atom transfer radical polymerization. Results are compared with kMC and method of moments and confirm that if applicable, full information regarding the microstructure of chains can be obtained using CBC‐MC method with reduced simulation times and smaller sample sizes. The Chain‐by‐Chain Monte Carlo simulation method (CBC‐MC) is introduced as a novel hybrid deterministic/probabilistic technique for polymerization systems. In CBC‐MC, nonspecific interactions are described through the use of deterministic equations, saving on ensemble size and computational time, and greatly enhancing convergence. In this article, CBC‐MC is successfully tested in two case studies involving the synthesis of linear gradient copolymers.