Hybrid deterministic and stochastic approach for dynamic simulation of photoinduced atom-transfer radical polymerization processes with microscopic resolution

Abstract

Among the various polymerization mechanisms available for producing polymers, photoinduced atom-transfer radical polymerization (photoATRP) stands out as a promising technique. By utilizing light as an external stimulus, photoATRP facilitates the production of well-defined polymers with precise distributions. The demand for advanced polymeric materials synthesis necessitates a deep understanding of polymer chains at the molecular level. As molecular weight distribution (MWD) is a key quality index of polymers, developing models with embedded MWD information holds significance for process design and optimization tasks. In this work, an accelerated hybrid deterministic and stochastic approach is proposed for simulating dynamic photoATRP processes. The proposed approach demonstrates computational efficiency and flexibility, enabling precise predictions for the evolution of both macroscopic and microscopic properties of polymers. An application to a batch photoATRP system model is presented to illustrate the validity and performance of the proposed hybrid approach.