Operator-independent high-throughput polymerization screening based on automated inline NMR and online SEC

Traditional protocols for high-throughput screening and experimentation are inherently time-consuming and cost-ineffective. Herein, we present a continuous flow-based automated synthesis platform that allows for rapid screenings of polymerizations. The platform uses online monitoring to acquire real time analytic data. Software is developed to guide data acquisition, and most importantly, to carry out reactions and their analysis autonomously. Further algorithms automatically detect experimental inaccuracies, and clean data. Data is aggregated and provided directly in a machine-readable manner, opening pathways towards creation of 'big data' sets for kinetic information that is independent of individual user biases and systematic errors. We demonstrate this platform on reversible-addition fragmentation chain transfer polymerization (RAFT). 8 different operators, ranging from PhD students with no prior experience in flow chemistry or RAFT polymerization, up to the professor of the research group created in this way a coherent dataset spanning 8 different monomers containing 3600 NMR spectra and about 400 molecular weight distribution analyses. Coherence of the dataset is demonstrated by reducing key kinetic information that describe the whole covered reaction space in a single parameter. Automated continuous flow is used as high-throughput method with high accuracy.

Automated summary

In this paper, a continuous flow-based automated synthesis platform for rapid screening of polymerizations is presented. The platform employs online monitoring to acquire real-time analytic data, and software is developed for autonomous reactions and data analysis. Algorithms are used to detect experimental inaccuracies and clean data. The aggregated data is provided in a machine-readable format, enabling the creation of 'big data' sets for kinetic information that are independent of individual biases and errors. The platform is demonstrated on reversible-addition fragmentation chain transfer polymerization (RAFT). The results show that the platform can generate a coherent dataset with high accuracy using automated continuous flow as a high-throughput method.