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Brandon J Reizman1, Yi-Ming Wang2, Stephen L Buchwald2

  • 1Department of Chemical Engineering , Novartis-MIT Center for Continuous Manufacturing , Massachusetts Institute of Technology , 77 Massachusetts Avenue , Cambridge , MA 02139 , USA .

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|December 9, 2016
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Summary
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This study introduces an automated microfluidic system for optimizing palladium-catalyzed Suzuki-Miyaura cross-coupling reactions. The system efficiently identifies optimal conditions and catalyst attributes, accelerating complex reaction development.

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Area of Science:

  • Organic Chemistry
  • Chemical Engineering
  • Catalysis

Background:

  • Palladium-catalyzed Suzuki-Miyaura cross-coupling reactions are vital in organic synthesis.
  • Optimization of these reactions often involves numerous experiments and complex variable interactions.
  • Automated systems can accelerate the discovery and optimization of catalytic processes.

Purpose of the Study:

  • To develop and implement an automated, droplet-flow microfluidic system for optimizing Pd-catalyzed Suzuki-Miyaura cross-coupling reactions.
  • To employ a smart optimal Design of Experiments (DoE)-based algorithm for simultaneous optimization of discrete and continuous variables.
  • To identify key attributes of successful precatalysts and understand ligand effects on reaction mechanisms.

Main Methods:

  • Utilized a droplet-flow microfluidic system for automated reaction exploration.
  • Implemented a smart optimal DoE-based algorithm to guide experiments.
  • Simultaneously varied discrete variables (palladacycle, ligand) and continuous variables (temperature, time, loading).
  • Employed feedback loops to steer experiments towards optimal conditions.

Main Results:

  • Achieved complex reaction optimization within 96 experiments.
  • Generated and validated response surfaces predicting reaction performance near optima.
  • Identified shared attributes of successful precatalysts.
  • Gained insights into the influence of ligand selection on transmetalation and oxidative addition.

Conclusions:

  • The automated microfluidic system significantly accelerates the optimization of Suzuki-Miyaura cross-coupling reactions.
  • The DoE-based algorithm effectively navigates complex parameter spaces for efficient optimization.
  • Understanding ligand influence on reaction mechanisms is crucial for designing improved catalytic systems.