Human versus Robots in the Discovery and Crystallization of Gigantic Polyoxometalates.

Angew Chem Int Ed Engl

WEST Chem, School of Chemistry, University of Glasgow, University Avenue, Glasgow, G12 8QQ, UK.

Published: August 2017

AI Article Synopsis

  • The discovery of new giant molecules involves both their formation and crystallization, which can be complex and challenging.
  • A workflow has been developed that can be used manually or by robots to investigate the synthesis and crystallization of a new polyoxometalate cluster, Na [Mo Ce O H (H O)]⋅200 H O with a unique architecture.
  • An active machine-learning algorithm significantly enhances the crystallization search process, covering nine times more space than random searches and achieving a prediction accuracy of 82.4%, compared to 77.1% from human efforts.

Article Abstract

The discovery of new gigantic molecules formed by self-assembly and crystal growth is challenging as it combines two contingent events; first is the formation of a new molecule, and second its crystallization. Herein, we construct a workflow that can be followed manually or by a robot to probe the envelope of both events and employ it for a new polyoxometalate cluster, Na [Mo Ce O H (H O) ]⋅200 H O (1) which has a trigonal-ring type architecture (yield 4.3 % based on Mo). Its synthesis and crystallization was probed using an active machine-learning algorithm developed by us to explore the crystallization space, the algorithm results were compared with those obtained by human experimenters. The algorithm-based search is able to cover ca. 9 times more crystallization space than a random search and ca. 6 times more than humans and increases the crystallization prediction accuracy to 82.4±0.7 % over 77.1±0.9 % from human experimenters.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5577512PMC
http://dx.doi.org/10.1002/anie.201705721DOI Listing

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