Abstract
A phenomenological study of solubility has been conducted using a combination of quantitative structure-property relationship (QSPR) and principal component analysis (PCA). A solubility database of 4540 experimental data points was used that utilized available experimental data into a matrix of 154 solvents times 397 solutes. Methodology 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. © 2005 American Chemical Society.
Cite
CITATION STYLE
Katritzky, A. R., Tulp, I., Fara, D. C., Lauria, A., Maran, U., & Acree, W. E. (2005). A general treatment of solubility. 3. Principal component analysis (PCA) of the solubilities of diverse solutes in diverse solvents. Journal of Chemical Information and Modeling, 45(4), 913–923. https://doi.org/10.1021/ci0496189
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.