Computer search for solvent and solute parameters that determine partition data

Yoelit Migron; Yizhak Marcus; Marian Dodu

doi:10.1016/0169-7439(93)E0056-A

Computer search for solvent and solute parameters that determine partition data

Yoelit Migron
, Yizhak Marcus^*
, Marian Dodu

^*Corresponding author for this work

Institute of Chemistry

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

Migron, Y., Marcus, Y. and Dodu, M., 1994. Computer Search for solvent and solute parameters that determine partition data. Chemometrics and Intelligent Laboratory Systems, 22: 191-197. Solute partitioning between water-immiscible organic solvents and water can be summarized by the matrix product D = PCQ^T. Here P is the matrix of solute properties, Q is that of solvent properties (Q^T is its transpose), and C describes the weight of each contribution to the data (log partition coefficient) matrix D. Factor analysis, employing singular value decomposition, yields an 'improved' data matrix D and an 'improved' matrix C. Factor analysis and target factor analysis, applied to the 28 × 9 matrix D, showed that there are three principal factors and allowed their selection from among the various parameters offered for this analysis.

Original language	English
Pages (from-to)	191-197
Number of pages	7
Journal	Chemometrics and Intelligent Laboratory Systems
Volume	22
Issue number	2
DOIs	https://doi.org/10.1016/0169-7439(93)E0056-A
State	Published - Feb 1994

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abstract = "Migron, Y., Marcus, Y. and Dodu, M., 1994. Computer Search for solvent and solute parameters that determine partition data. Chemometrics and Intelligent Laboratory Systems, 22: 191-197. Solute partitioning between water-immiscible organic solvents and water can be summarized by the matrix product D = PCQT. Here P is the matrix of solute properties, Q is that of solvent properties (QT is its transpose), and C describes the weight of each contribution to the data (log partition coefficient) matrix D. Factor analysis, employing singular value decomposition, yields an 'improved' data matrix D and an 'improved' matrix C. Factor analysis and target factor analysis, applied to the 28 × 9 matrix D, showed that there are three principal factors and allowed their selection from among the various parameters offered for this analysis.",

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AB - Migron, Y., Marcus, Y. and Dodu, M., 1994. Computer Search for solvent and solute parameters that determine partition data. Chemometrics and Intelligent Laboratory Systems, 22: 191-197. Solute partitioning between water-immiscible organic solvents and water can be summarized by the matrix product D = PCQT. Here P is the matrix of solute properties, Q is that of solvent properties (QT is its transpose), and C describes the weight of each contribution to the data (log partition coefficient) matrix D. Factor analysis, employing singular value decomposition, yields an 'improved' data matrix D and an 'improved' matrix C. Factor analysis and target factor analysis, applied to the 28 × 9 matrix D, showed that there are three principal factors and allowed their selection from among the various parameters offered for this analysis.

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Computer search for solvent and solute parameters that determine partition data

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