Synthesis Platforms for Generating High-Quality Polymer Datasets Utilizing Continuous and Discontinuous Reaction Setups

Abstract

Availability of experimental data of high quality and in large quantity is fundamental to unlock opportunities for accelerating research and development by the application of data science and AI. In this context, we will present automated continuous and discontinuous experimentation setups for the synthesis of polymers and polymeric networks to further drive the adoption of automation. Besides synthesizing a series of 100 distinct block copolymers in 9 minutes, continuous flow reactors also allowed the synthesis of tailored segmented polyurethanes under real-time process monitoring and provided access to performing controlled ring-opening polymerization in milliseconds timeframe. Due to their facile de-/assembly, continuous flow reactor setups offer reconfigurability and wide customizability. To overcome the resulting necessity to redevelop automation code, we developed a control and simulation software, LabDCS, and it will be presented how LabDCS allows to build, simulate, and operate chemical plants based on flow reactor hardware. In the second part, we will cover the utilization of a single channel pipettor for generating a dataset of sol-gel materials and how ensemble models were trained to represent the growth of the sol what constitutes an important process parameter for industrial clients.