A phenomenol. study of soly. has been conducted using a combination of quant. structure-property relationship (QSPR) and principal component anal. (PCA). A soly. database of 4540 exptl. data points was used that utilized available exptl. data into a matrix of 154 solvents times 397 solutes. Methodol. in which QSPR and PCA are combined was developed to predict the missing values and to fill the data matrix. PCA on the resulting filled matrix, where solutes are observations and solvents are variables, shows 92.55 % of coverage with three principal components. The corresponding transposed matrix, in which solvents are observations and solutes are variables, showed 62.96 % of coverage with four principal components.
KATRITZKY AR, TULP I, FARA DC, LAURIA A, MARAN U, ACREE WE (2005). A General Treatment of Solubility. 3. Principal Component Analysis (PCA) of the Solubilities of Diverse Solutes in Diverse Solvents.
A General Treatment of Solubility. 3. Principal Component Analysis (PCA) of the Solubilities of Diverse Solutes in Diverse Solvents
LAURIA, Antonino;
2005-01-01
Abstract
A phenomenol. study of soly. has been conducted using a combination of quant. structure-property relationship (QSPR) and principal component anal. (PCA). A soly. database of 4540 exptl. data points was used that utilized available exptl. data into a matrix of 154 solvents times 397 solutes. Methodol. in which QSPR and PCA are combined was developed to predict the missing values and to fill the data matrix. PCA on the resulting filled matrix, where solutes are observations and solvents are variables, shows 92.55 % of coverage with three principal components. The corresponding transposed matrix, in which solvents are observations and solutes are variables, showed 62.96 % of coverage with four principal components.
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