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Article / Jul 08, 2021

Augmenting Adaptive Machine Learning with Kinetic Modeling for Reaction Optimization

  • A. Filipa Almeida
  • Filipe Ataide
  • Rui Loureiro
  • Rui Moreira
  • Tiago Rodrigues
Journal of Organic Chemistry, July 8, 2021

We combine random sampling and active machine learning (ML) to optimize the synthesis of isomacroin, executing only 3% of all possible Friedländer reactions. Employing kinetic modeling, we augment machine intuition by extracting mechanistic knowledge and verify that a global optimum was obtained with ML. Our study contributes evidence on the potential of multiscale approaches to expedite the access to chem. matter, further democratizing organic chem. in a data-motivated fashion.