Abstract
This article outlines the benefits of using 'Design of Experiments' (DoE) optimisation during the development of new synthetic methodology. A particularly important factor in the development of new chemical reactions is the choice of solvent which can often drastically alter the efficiency and selectivity of a process. Whilst solvent optimisation is usually done in a non-systematic way based upon a chemist's intuition and previous laboratory experience, we illustrate how optimisation of the solvent for a reaction can be carried out by using a 'map of solvent space' in a DoE optimisation. A new solvent map has been developed specifically for optimisation of new chemical reactions using principle component analysis (PCA) incorporating 136 solvents with a wide range of properties. The new solvent map has been used to identify safer alternatives to toxic/hazardous solvents, and also in the optimisation of an S(N)Ar reaction.
Highlights
A important factor in the development of new chemical reactions is the choice of solvent which can often drastically alter the efficiency and selectivity of a process
In this article we report a new principle component analysis (PCA) solvent map designed for use in new chemistry development, and outline how this PCA map can be used for identifying alternatives to toxic/undesirable solvents and applied in combination with design of experiments (DoE) for the optimisation of new synthetic methodology
The potential benefits of the ‘Design of Experiments’ approach to reaction optimisation for the development of new methodology have been discussed, with a discussion of how the technique can be applied to reactions during their development
Summary
Despite the fact that well established statistical methods for reaction optimisation are widely used in industry,[2,3] the uptake of these methods has been very low in academic chemistry.[4,5] Often, the ‘optimisation’ process proceeds entirely via a trial and error approach involving the variation of one factor at a time (e.g. solvent, temperature, catalyst, concentration, etc.). Whilst this technique is routinely applied by process chemists in a wide range of industries, and by academics working in engineering disciplines,[7] it is rarely used in academic chemistry This is in spite of the fact that optimisation of particular reactions is often an extremely time-consuming part of any research project focused on the development of new synthetic methodology. In the traditional OVAT approach, repetition of each experiment is advisable to ensure reproducibility, or the entire ‘optimisation’ could be led astray by a single anomalous result
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