Autonomous Discovery in the Chemical Sciences Part II: Outlook
Name
2003.13755.pdf
Description
Accepted version
Size
4.66 MB
Format
Unknown
Checksum (MD5)
9fba54372e7025d99178a3872e0defd8
Author(s)
Coley, Connor W.
Eyke, Natalie S.
Jensen, Klavs F.
Date Issued
June 2020
Journal
Angewandte Chemie - International Edition
Publisher
Wiley
Version
Author's final manuscript
Abstract
© 2019 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim 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.
MIT Department
Massachusetts Institute of Technology. Department of Chemical Engineering
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1002/anie.201909989
