Algorithms for the self-optimisation of chemical reactions. Issue 9 (12th August 2019)

• Record Type: Journal Article
• Authors: Clayton, Adam D.; Manson, Jamie A.; Taylor, Connor J.; Chamberlain, Thomas W.; Taylor, Brian A.; Clemens, Graeme; Bourne, Richard A.
• Is Part Of: Reaction chemistry & engineering. Volume 4:Issue 9(2019)
• Page Start: 1545
• Page End: 1554
• Publication Date: 2019-08-12
• Subjects: Reaction mechanisms (Chemistry) -- Periodicals; Chemical engineering -- Periodicals; Chemical engineering; Reaction mechanisms (Chemistry); Periodicals; 547.705
• DOI: 10.1039/c9re00209j
• Languages: English
• ISSNs: 2058-9883

Abstract

Abstract : Self-optimising chemical systems have experienced a growing momentum in recent years. Herein, we review algorithms used for the self-optimisation of chemical reactions in an accessible way for the general chemist. Abstract : Self-optimising chemical systems have experienced a growing momentum in recent years, with the evolution of self-optimising platforms leading to their application for reaction screening and chemical synthesis. With the desire for improved process sustainability, self-optimisation provides a cheaper, faster and greener approach to the chemical development process. The use of such platforms aims to enhance the capabilities of the researcher by removing the need for labor-intensive experimentation, allowing them to focus on more challenging tasks. The establishment of these systems have enabled opportunities for self-optimising platforms to become a key element of a laboratory's repertoire. To enable the wider adoption of self-optimising chemical platforms, this review summarises the history of algorithmic usage in chemical reaction self-optimisation, detailing the functionality of the algorithms and their applications in a way that is accessible for chemists and highlights opportunities for the further exploitation of algorithms in chemical synthesis moving forward.