Combing PCA with DoE for Effective Experimental Investigation

The combination of Design of Experiments and Principal Component Analysis together facilitates the development of a reaction by informed decision making, where all critical factors may be considered alongside one another in an efficient and effective manner.

PCA analysis on a set of compounds and their properties generates a set of principal components which more accurately reflect the intrinsic molecular properties of the compounds. As these principal components summarise the intrinsic molecular properties they are typically referred to as principal properties. Each of these principal properties becomes a continuum and can be considered similar to a traditional continuous variable in DoE. The combination of two or more principal properties provides a semi continuous map. The map then allows the selection of a representative subset of compounds either diverse or focused on key properties deepening on the needs of the investigation.

A selection of one or more sets of reagents from their respective maps, for example solvents and ligands, can be combined with any additional experimental factors such as concentration, stoichiometry and temperature in experimental designs such as fractional factorial designs.

For more information on combining Design of Experiments and Principal Component Analysis see the link Combining DoE and PCA.

Paul Murray Catalysis Consulting will provide our clients with:

  • The selection of suitable properties for chemical datasets to generate appropriate PCA maps.
  • The selection of materials from PCA maps to enable the efficient understanding of the chemical space and factors to produce a commercially viable chemical reaction.
  • The selection of the appropriate experimental designs and analysis of the resulting experimental data.
  • Partial Least Squares (PLS) modelling to understand the properties of materials that play a significant role in optimum reaction development and prediction of suitability of alternative materials for the chosen reaction.

For examples of combining Design of Experiments and Principal Component Analysis in catalysis see the following case studies:

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