Duros, V., Grizou, J. , Sharma, A. , Mehr, S. H. M., Bubliauskas, A., Frei, P., Miras, H. N. and Cronin, L. (2019) Intuition-enabled machine learning beats the competition when joint human-robot teams perform inorganic chemical experiments. Journal of Chemical Information and Modeling, 59(6), pp. 2664-2671. (doi: 10.1021/acs.jcim.9b00304) (PMID:31025861) (PMCID:PMC6593393)
|
Text
185445.pdf - Published Version Available under License Creative Commons Attribution. 2MB |
Abstract
Traditionally, chemists have relied on years of training and accumulated experience in order to discov-er new molecules. But the space of possible molecules so vast, only a limited exploration with the tra-ditional methods can be ever possible. This means that many opportunities for the discovery of inter-esting phenomena have been missed, and in addition, the inherent variability of these phenomena can make them difficult to control and understand. The current state-of-the-art is moving towards the de-velopment of automated and eventually fully autonomous systems coupled with in-line analytics and decision-making algorithms. Yet even these, despite the substantial progress achieved recently, still cannot easily tackle large combinatorial spaces as they are limited by the lack of high-quality data. Herein, we explore the utility of active learning methods for exploring the chemical space by compar-ing collaboration between human experimenters with an algorithm-based search, against their perfor-mance individually to probe the self-assembly and crystallization of the polyoxometalate cluster Na6[Mo120Ce6O366H12(H2O)78]·200H2O (1). We show that the robot-human teams are able to increase the prediction accuracy to 75.6±1.8%, from 71.8±0.3% with the algorithm alone and 66.3±1.8% from only the human experimenters demonstrating that human-robot teams beat robots or humans working alone.
Item Type: | Articles |
---|---|
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Sharma, Mr Abhishek and Moiras, Professor Haralampos and Grizou, Dr Jonathan and Bubliauskas, Mr Andrius and Duros, Mr Wasilios and Frei, Mr Przemyslaw and Cronin, Professor Lee |
Authors: | Duros, V., Grizou, J., Sharma, A., Mehr, S. H. M., Bubliauskas, A., Frei, P., Miras, H. N., and Cronin, L. |
College/School: | College of Science and Engineering > School of Chemistry |
Journal Name: | Journal of Chemical Information and Modeling |
Publisher: | American Chemical Society |
ISSN: | 1549-9596 |
ISSN (Online): | 1549-960X |
Published Online: | 26 April 2019 |
Copyright Holders: | Copyright © 2019 American Chemical Society |
First Published: | First published in Journal of Chemical Information and Modeling 59(6): 2664-2671 |
Publisher Policy: | Reproduced under a Creative Commons License |
University Staff: Request a correction | Enlighten Editors: Update this record