Application and comparison of derivative-free optimization algorithms to control and optimize free radical polymerization simulated using the kinetic Monte Carlo method

•Developed a derivative-free optimization framework coupled with KMC simulations.•Compared different methods to evaluate efficiency.•Achieved multi-objective optimization for polymerization including sequence.

The diversity of the potential arrangements of multiple monomers along the length of polymer chains and their impact on polymer properties spark interest in the design of polymer sequence characteristics for particular applications. Kinetic Monte Carlo (KMC) is a technique that can track the explicit arrangement of monomers in the polymer chains, yet it is difficult to integrate with conventional gradient-based optimization algorithms that are typically invoked to design polymer properties. In this work, we applied and compared derivative-free optimization algorithms to incorporate KMC simulations and find synthesis conditions for achieving property targets and minimizing reaction time, advancing our ability to carry out the design of polymer microstructures and control polymerization processes.