QSPR Study of the Henry's Law Constant for Hydrocarbons

PABLO R. DUCHOWICZ; JUAN C. GARRO MARTINEZ; EDUARDO A. CASTRO

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Año: 2007 p. 133 - 140

0169-7439

Abstract We establish a QSPR model between the Henry´s Law constant in the air–water system and the molecular structure of 150 aliphatic hydrocarbons. The simultaneous linear regression analyzes on 1086 numerical descriptors reflecting topological, geometrical, and electronic aspects lead to a seven parameter equation that, when compared to previously reported models, exhibits good calibration and cross-validated parameters: R=0.996, Rl–10%–o=0.997. As a realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. simultaneous linear regression analyzes on 1086 numerical descriptors reflecting topological, geometrical, and electronic aspects lead to a seven parameter equation that, when compared to previously reported models, exhibits good calibration and cross-validated parameters: R=0.996, Rl–10%–o=0.997. As a realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. simultaneous linear regression analyzes on 1086 numerical descriptors reflecting topological, geometrical, and electronic aspects lead to a seven parameter equation that, when compared to previously reported models, exhibits good calibration and cross-validated parameters: R=0.996, Rl–10%–o=0.997. As a realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. simultaneous linear regression analyzes on 1086 numerical descriptors reflecting topological, geometrical, and electronic aspects lead to a seven parameter equation that, when compared to previously reported models, exhibits good calibration and cross-validated parameters: R=0.996, Rl–10%–o=0.997. As a realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. –water system and the molecular structure of 150 aliphatic hydrocarbons. The simultaneous linear regression analyzes on 1086 numerical descriptors reflecting topological, geometrical, and electronic aspects lead to a seven parameter equation that, when compared to previously reported models, exhibits good calibration and cross-validated parameters: R=0.996, Rl–10%–o=0.997. As a realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals. R=0.996, Rl–10%–o=0.997. As a realistic application, we employ this relationship to estimate the partition coefficient for 39 non-yet measured chemicals.