| Literature DB >> 30212208 |
Daniel Cortés-Borda1, Eric Wimmer1, Boris Gouilleux1, Elvina Barré1, Nicolas Oger1, Lubna Goulamaly1, Louis Peault1, Benoît Charrier1, Charlotte Truchet2, Patrick Giraudeau1,3, Mireia Rodriguez-Zubiri1, Erwan Le Grognec1, François-Xavier Felpin1,3.
Abstract
A modular autonomous flow reactor combining monitoring technologies with a feedback algorithm is presented for the synthesis of the 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 online 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 multidimensional 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 multistep synthesis where all discrete steps were optimized with an autonomous flow reactor.Entities:
Year: 2018 PMID: 30212208 DOI: 10.1021/acs.joc.8b01821
Source DB: PubMed Journal: J Org Chem ISSN: 0022-3263 Impact factor: 4.354