82. An Autonomous Self-Optimizing Flow Reactor for the Synthesis of Natural Product Carpanone
Daniel Cortés-Borda, Eric Wimmer, Boris Gouilleux, Elvina Barré, Nicolas Oger, Lubna Goulamaly, Louis Peault, Benoît Charrier, Charlotte Truchet, Patrick Giraudeau, Mireia Rodriguez-Zubiri, Erwan Le Grognec, and François-Xavier Felpin, The Journal of Organic Chemistry, (2018) DOI: 10.1021/acs.joc.8b01821
A modular autonomous flow reactor combining monitoring technologies with a feedback algorithm is presented for the synthesis of natural product carpanone. The autonomous self-optimizing system, controlled via MATLAB®, was designed as a flexible platform enabling an adaptation of the experimental setup to the specificity of the chemical transformation to be optimized. The reaction monitoring uses either on-line high pressure liquid chromatography (HPLC) or in-line benchtop nuclear magnetic resonance (NMR) spectroscopy. The custom-made optimization algorithm derived from the Nelder-Mead and golden section search methods performs constrained optimizations of black-box functions in a multi-dimensional search domain, thereby, assuming no a priori knowledge of the chemical reactions. This autonomous self-optimizing system allowed fast and efficient optimizations of the chemical steps leading to carpanone. This contribution is the first example of a multi-step synthesis optimized with an autonomous flow reactor.