Studies of self association in alcohols as functions of concentrations and temperature: Part 1. Sample selection

Based on the assumption that physicochemical properties reflect differences in the size and number of self-associated aggregates of open chain mono-hydroxyl alcohols, six alcohols were chosen from a set of 57 alcohols characterised by 12 physical properties. The aim of the sample selection is to capture the variation of the property matrix in a smaller, representative sub-set. Principal components analysis (PCA) on the property matrix was used in combination with Soft Independent Modelling of Class Analogy (SIMCA) to select the six alcohols interactively using score plots. Due to missing values in the property matrix, the available PCA algorithm was compared with a new algorithm that handles missing values correctly. Because of the chosen pre-processing, the available algorithm could be used. The procedure of sample selection was to (i) select alcohols which spanned the principal components, (ii) include an alcohol located close to the origin of the principal component co-ordinate system and finally (iii) select alcohols which had a large residual with respect to the principal component model of the full property matrix. After the initial selection, the left-out alcohols were tested to be members of the principal component model of the first sub-set. Left-out alcohols found not to be members are to be included/exchanged in the sub-set. The membership testing is repeated until all left-out alcohols are defined to be members of the final sub-set.