Connor J. Taylor

TL;DR: Algorithms used for the self-optimisation of chemical reactions in an accessible way for the general chemist are reviewed.

TL;DR: The combination of multi-objective optimisation based on machine learning methods (TSEMO algorithm) with self-optimising platforms for the optimisation of multi -step continuous reaction processes with respect to multiple objectives has the potential to make substantial savings in time and resources.

TL;DR: This automated approach to gaining full process understanding, whereby a small number of data-rich experiments are conducted, and the kinetics are evaluated autonomously, shows significant improvements on current industrial optimisation techniques in terms of labour, time and overall cost.

TL;DR: In this article, the applied frequency of the alternating polarity has been shown to have a significant impact on the observed reaction rate of the Cu(I)-NHC complex formation, which can be manipulated to give enhanced yield that is stable over extended reaction times.

TL;DR: In this paper, a flow chemistry laboratory practical for integrating design of experiments optimisation techniques into an organic chemistry laboratory session is presented, in which students construct a simple flow reactor and perform a structured series of experiments followed by computational processing and analysis of the results.