A robotic platform for flow synthesis of organic compounds informed by AI planning

Abstract

Progress in automated synthesis of organic compounds has been proceeding along parallel tracks. One goal is algorithmic prediction of viable routes to a desired compound; the other is implementation of a known reaction sequence on a platform that needs little to no human intervention. Coley et al. now report preliminary integration of these two protocols. They paired a retrosynthesis prediction algorithm with a robotically reconfigurable flow apparatus. Human intervention was still required to supplement the predictor with practical considerations such as solvent choice and precise stoichiometry, although predictions should improve as accessible data accumulate for training.

Document Details

Document Type
Pub Defense Publication
Publication Date
Aug 09, 2019
Source ID
10.1126/science.aax1566

Entities

People

  • A. John Hart
  • Christopher P. Breen
  • Connor W. Coley
  • Dale A. Thomas
  • Hanyu Gao
  • John S. Piotti
  • Jonathan N. Jaworski
  • Joshua Byington
  • Joshua S. Fishman
  • Justin A. M. Lummiss
  • Klavs F. Jensen
  • Luke Rogers
  • Pieter P. Plehiers
  • Robert W. Hicklin
  • Timothy F. Jamison
  • Travis Hart
  • Victor Schultz
  • William H. Green

Organizations

  • Massachusetts Institute of Technology

Tags

Fields of Study

  • Computer science

Readers

  • Electrochemical Engineering/ Fuel Cell Technologies
  • Robotics and Automation.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks
  • Autonomy