Design of Experiments in Chemistry

Design of Experiments is a vital tool to efficiently explore important factors in a chemical reaction. It facilitates the systematic variation of multiple factors simultaneously in a highly efficient and scientifically rational manner. The inclusion of repeated experiments provides an accurate measure of experimental variation and reproducibility in the reactions, whilst statistical analysis allows for the interpretation of the significance of each of the factors investigated in the reaction.

Any number of factors could affect the performance of a chemical reaction, such as concentration, pressure, pH, solvent, stoichiometry, temperature and time. The factors to investigate are chosen as they are expected to have an effect on the outcome of the reaction (response). Design of Experiments enables the experimenter to investigate the direct effect each factor has on the experiment as well as the combined effect that two or more factors (an interaction) may have on the experiment.

Designs can be devised to interrogate any factor and its interaction with other factors at several levels of understanding:

  • Linear models provide information about main factors only, but are useful in screening situations with a view to determining which of many factors are important;
  • Interaction models provide information about both the main factors and any interactions between those factors;
  • Quadratic models can describe non-linear behaviour of factors by taking the curvature of the response surface into account.

The construction of a quadratic model requires many more experiments than the generation of an interaction model and very many more than for a linear model. Therefore, before designing the set of experiments to be undertaken in the laboratory it is essential to consider the objectives of the experimentation and the level of detail required about main factor effects and interactions.

For more information on Design of Experiments see the link DoE.

Paul Murray Catalysis Consulting will provide our clients with:

  • The selection of appropriate designs, factors and ranges for their experimental investigation.
  • The analysis and interpretation of the experimental data.
  • The prediction of reaction outcomes from the Design of Experiments model.
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