Discovering new chemistry with an autonomous robotic platform driven by a reactivity-seeking neural network

Caramelli, D., Granda, J. M., Mehr, S. H. M. , Cambie, D. , Henson, A. B. and Cronin, L. (2021) Discovering new chemistry with an autonomous robotic platform driven by a reactivity-seeking neural network. ACS Central Science, 7(11), pp. 1821-1830. (doi: 10.1021/acscentsci.1c00435)

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Abstract

We present a robotic chemical discovery system capable of navigating a chemical space based on a learned general association between molecular structures and reactivity, while incorporating a neural network model that can process data from online analytics and assess reactivity without knowing the identity of the reagents. Working in conjunction with this learned knowledge, our robotic platform is able to autonomously explore a large number of potential reactions and assess the reactivity of mixtures, including unknown chemical spaces, regardless of the identity of the starting materials. Through the system, we identified a range of chemical reactions and products, some of which were well-known, some new but predictable from known pathways, and some unpredictable reactions that yielded new molecules. The validation of the system was done within a budget of 15 inputs combined in 1018 reactions, further analysis of which allowed us to discover not only a new photochemical reaction but also a new reactivity mode for a well-known reagent (p-toluenesulfonylmethyl isocyanide, TosMIC). This involved the reaction of 6 equiv of TosMIC in a “multistep, single-substrate” cascade reaction yielding a trimeric product in high yield (47% unoptimized) with the formation of five new C–C bonds involving sp–sp2 and sp–sp3 carbon centers. An analysis reveals that this transformation is intrinsically unpredictable, demonstrating the possibility of a reactivity-first robotic discovery of unknown reaction methodologies without requiring human input.

Item Type:Articles
Additional Information:The authors gratefully acknowledge financial support from the EPSRC (Grants EP/S030603/1, EP/S019472/1, EP/S017046/1, EP/L015668/1, EP/L023652/1) and the ERC (project 670467 SMART-POM). J. M. Granda acknowledges financial support from the Polish Ministry of Science and Higher Education grant 1295/MOB/IV/2015/0.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Henson, Dr Alon and Granda, Dr Jaroslaw and Mehr, Dr Hessam and Caramelli, Dr Dario and Cronin, Professor Lee and Cambie, Mr Dario
Authors: Caramelli, D., Granda, J. M., Mehr, S. H. M., Cambie, D., Henson, A. B., and Cronin, L.
College/School:College of Science and Engineering > School of Chemistry
Journal Name:ACS Central Science
Publisher:American Chemical Society (ACS)
ISSN:2374-7943
ISSN (Online):2374-7951
Published Online:11 November 2021
Copyright Holders:Copyright © 2021 The Authors
First Published:First published in ACS Central Science 7(11):1821–1830
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
304037EPSRC International Centre-to-Centre CroninLeroy CroninEngineering and Physical Sciences Research Council (EPSRC)EP/S030603/1Chemistry
303747Digital-Chemical-Robotics for Translation of Code to Molecules and Complex Chemical SystemsLeroy CroninEngineering and Physical Sciences Research Council (EPSRC)EP/S019472/1Chemistry
3026673DSynth: Design and fabrication of cartridges for digital chemical synthesisLeroy CroninEngineering and Physical Sciences Research Council (EPSRC)EP/S017046/1Chemistry
168917A Digital DNA Nano Writer (DNA NanoFab)Leroy CroninEngineering and Physical Sciences Research Council (EPSRC)EP/L015668/1Chemistry
190796Programmable 'Digital' Synthesis for Discovery and Scale-up of Molecules, Clusters and NanomaterialsLeroy CroninEngineering and Physical Sciences Research Council (EPSRC)EP/L023652/1Chemistry
172151SMARTPOM: Artificial-Intelligence Driven Discovery and Synthesis of Polyoxometalate ClustersLeroy CroninEuropean Research Council (ERC)670467Chemistry