Autonomous Discovery in the Chemical Sciences Part II: Outlook
Abstract
This two‐part Review examines how automation has contributed to different aspects of discovery in the chemical sciences. In this second part, we reflect on a selection of exemplary studies. It is increasingly important to articulate what the role of automation and computation has been in the scientific process and how that has or has not accelerated discovery. One can argue that even the best automated systems have yet to “discover” despite being incredibly useful as laboratory assistants. We must carefully consider how they have been and can be applied to future problems of chemical discovery in order to effectively design and interact with future autonomous platforms. The majority of this Review defines a large set of open research directions, including improving our ability to work with complex data, build empirical models, automate both physical and computational experiments for validation, select experiments, and evaluate whether we are making progress towards the ultimate goal of autonomous discovery. Addressing these practical and methodological challenges will greatly advance the extent to which autonomous systems can make meaningful discoveries.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jun 11, 2020
- Source ID
- 10.1002/anie.201909989
Entities
People
- Connor W. Coley
- Klavs F. Jensen
- Natalie S. Eyke
Organizations
- Defense Advanced Research Projects Agency
- Massachusetts Institute of Technology