Automated approaches, reaction parameterisation, and data science in organometallic chemistry and catalysis: towards improving synthetic chemistry and accelerating mechanistic understanding

Stuart C. Smith, Christopher S. Horbaczewskyj, Theo F.N. Tanner, Jacob J. Walder, Ian J.S. Fairlamb*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review


Automation technologies and data science techniques have been successfully applied to optimisation and discovery activities in the chemical sciences for decades. As the sophistication of these techniques and technologies have evolved, so too has the ambition to expand their scope of application to problems of significant synthetic difficulty. Of these applications, some of the most challenging involve investigation of chemical mechanism in organometallic processes (with particular emphasis on air- and moisture-sensitive processes), particularly with the reagent and/or catalyst used. We discuss herein the development of enabling methodologies to allow the study of these challenging systems and highlight some important applications of these technologies in problems of considerable interest to applied synthetic chemists.

Original languageEnglish
Number of pages29
JournalDigital Discovery
Early online date24 May 2024
Publication statusE-pub ahead of print - 24 May 2024

Bibliographical note

Funding Information:
We are grateful to the EPSRC for funding (C. S. H. and I. J. S. F.; EP/S009965/1 and EP/W031914/1) and to the Royal Society for an Industry Fellowship (I. J. S. F.). AstraZeneca and GSK have provided PhD studentship co-funding for S. C. S. and J. J. W. respectively. We thank Prof. Jason Lynam from the Department of Chemistry in York and Dr Neil Scott for their comments and valuable input into this review article. We also thank Dr George Clarke for his input into the potential material that could be included in this review paper. We are grateful to the EPSRC, Royal Society and industry funders (AstraZeneca and GSK) for supporting our research efforts in this area.

Publisher Copyright:
© 2024 The Author(s).

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