Our research spans thermal-, electro-, and photo-chemistry in batch and flow, kinetics and optimization, automation, and machine learning to develop new methods that accelerate chemical discovery and development. We explore new automated reaction systems integrated with online analytics, robotics, optimization, and machine learning algorithms toward autonomous discovery. In collaboration with our colleagues in the MIT consortium for Machine Learning for Chemical Discovery and Synthesis (mlpds.mit.edu), we develop new algorithms for synthesis planning and process chemistry.
Recent and current areas of research
- Reactions in microliter droplets
- Automated optimization of multistep synthesis in flow & data-rich experimentations
- Toward autonomous molecular discovery