Suzuki–Miyaura cross-coupling optimization enabled by automated feedback
Name
Jensen_Suzuki-Miyaura.pdf
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3.23 MB
Format
Adobe PDF
Checksum (MD5)
5098b04391da219a3ae1ddd97d98e692
Author(s)
Reizman, Brandon Jacob
Wang, Yiming
Buchwald, Stephen Leffler
Jensen, Klavs F
Date Issued
October 2016
Journal
Reaction Chemistry & Engineering
Publisher
Royal Society of Chemistry
Citation
Reizman, Brandon J. et al. “Suzuki–Miyaura Cross-Coupling Optimization Enabled by Automated Feedback.” React. Chem. Eng. 1.6 (2016): 658–666. © 2016 Royal Society of Chemistry
Version
Final published version
Abstract
An automated, droplet-flow microfluidic system explores and optimizes Pd-catalyzed Suzuki–Miyaura cross-coupling reactions. A smart optimal DoE-based algorithm is implemented to increase the turnover number and yield of the catalytic system considering both discrete variables—palladacycle and ligand—and continuous variables—temperature, time, and loading—simultaneously. The use of feedback allows for experiments to be run with catalysts and under conditions more likely to produce an optimum; consequently complex reaction optimizations are completed within 96 experiments. Response surfaces predicting reaction performance near the optima are generated and validated. From the screening results, shared attributes of successful precatalysts are identified, leading to improved understanding of the influence of ligand selection upon transmetalation and oxidative addition in the reaction mechanism. Dialkylbiarylphosphine, trialkylphosphine, and bidentate ligands are assessed.
MIT Department
Novartis-MIT Center for Continuous Manufacturing
Massachusetts Institute of Technology. Department of Chemical Engineering
Massachusetts Institute of Technology. Department of Chemistry
Terms of Use
Creative Commons Attribution 3.0 Unported license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1039/c6re00153j
