Model‐Assisted Optimization of RAFT Polymerization in Micro‐Scale Reactors—A Fast Screening Approach

Abstract

AbstractIn this work, the combination of different modeling approaches with in‐line proton nuclear magnetic resonance (1H‐NMR) spectroscopy is used to assist the transfer of a reversible addition‐fragmentation chain transfer (RAFT) polymerization of methyl methacrylate to a micro‐scale reactor. This approach is then applied to find the optimal process parameters like temperature or residence time as well as the best composition of the reaction mixture in order to optimize the conversion and molecular characteristics of the synthesized polymer. A kinetic model based on ordinary differential equations implemented in the program Predici is first validated based on experimental data of reactions performed at various temperatures. Further on, two glass chip reactors and a coil reactor are used and combined in different ways to investigate the influence of the reactor geometry on the polymerization process. This optimization step is assisted by multiphysics modeling that focuses on the heat transfer properties of specific areas inside the reactors. This experimental setup is used successfully to carry out a stationary polymerization. This study shows that instationary experiments in a micro‐fluidic reactor system equipped with in‐line analytics allow for the fast development of a kinetic model for RAFT polymerizations.