Prediction of Infinite Dilution Activity Coefficients of Halogenated Hydrocarbons in Water

Geometrical optimization and electrostatic potential calculations have been performed for a series of halogenated hydrocarbons at the HF/Gen-6d level. A number of electrostatic potentials and the statistically based structural descriptors derived from these electrostatic potentials have been obtained. Multiple linear regression analysis and artificial neural network are employed simultaneously in this paper. The result shows that the parameters derived from electrostatic 2 potentials σtot^2, V s and ∑ Vs^＋, together with the molecular volume （Vine） can be used to express the quantitative structure-infinite dilution activity coefficients （γ^∞） relationship of halogenated hydrocarbons in water. The result also demonstrates that the model obtained by using BFGS quasiNewton neural network method has much better predictive capability than that from multiple linear regression. The goodness of the model has been validated through exploring the predictive power for the external test set. The model obtained via neural network may be applied to predict γ^∞ of other halogenated hydrocarbons not present in the data set.

Prediction of Infinite Dilution Activity Coefficients of Alcohol and Ether Organic Compounds in Water

Based on QSPR of alcohol and ether organic compounds in water,geometrical optimization and electrostatic potential calculations were performed at the HF/6-31G＊ level for 73 alcohol and ether organic compounds.Linear relationships between infinite dilution activity coef-ficient（lnγ∞） of alcohols and ethers in water and theoretical descriptors of the molecular structure were established by multiple regression method.The result shows that the parameters derived from molecular electrostatic potential together with molecular surface area can be preferably used to express the quantitative structure-lnγ∞ relationship of alcohols and ethers in water.This reveals that this model has good predictive capabilities（RCV=0.969）.The molecular electrostatic potential has also been proved to have the general applicability in QSPR model of alcohol and ether organic compounds about γ∞ in water.The QSPR model established may provide a new powerful method for predicting γ∞ of organic compounds in aqueous systems.

Ant Colony Optimization as a Powerful Tool for Descriptor Selection in QSPR Study of Infinite Dilution Activity Coefficients of Halogenated Hydrocarbons in Water

A quantitative structure-property relationship （QSPR） study was suggested for the prediction of infinite dilution activity coefficients of halogenated hydrocarbons, γ∞ , in water at 298.15 K. After optimization of 3D geometry of the halogenated hydrocarbons with semi-empirical quantum chemical calculations at the AM1 level, different descriptors （1514 descriptors） were calculated by the HyperChem and Dragon softwares. A major problem of QSPR is the high dimensionality of the descriptor space; therefore, descriptor selection is the most important step. In this paper, an ant colony optimization （ACO） algorithm was proposed to select the best descriptors. Then the selected descriptors were applied for model development using multiple linear regression. The average absolute relative deviation and correlation coefficient for the training set were obtained as 4.36% and 0.951, respectively, while the corresponding values for the test set were 5.96% and 0.929, respectively. The results showed that the applied procedure is suitable for the prediction of γ∞ of halogenated hydrocarbons in water.

Application of Genetic Programming in Predicting Infinite Dilution Activity Coefficients of Organic Compounds in Water

In this paper, we calculated 37 structural descriptors of 174 organic compounds. The 154 molecules were used to derive quantitative structure - infinite dilution activity confficient relationship by genetic programming, the other 20 compounds were used to test the model. The result showed that molecular partition property and three-dimensional structural descriptors have significant influence on the infinite dilution activity coefficients.

Measurement of activity coefficients at infinite dilution for hydrocarbons in imidazolium-based ionic liquids and QSPR model

The separations of olefin/paraffin,aromatic/aliphatic hydrocarbons or olefin isomers using ionic liquids instead of volatile solvents have interested many researchers.Activity coefficientsγ∞at infinite dilution of a solute in ionic liquid are generally used in the selection of solvents for extraction or extractive distillation.In fact,the measurement ofγ∞by gas-liquid chromatography is a speedy and cost-saving method.Activity coefficients at infinite dilution of hydrocarbon solutes,such as alkanes,hexenes,alkylben-zenes,styrene,in 1-allyl-3-methylimidazolium tetrafluorobo-rate([AMIM][BF4])and 1-butyl-3-methyl imidazolium hexafluorophosphate([BMIM][PF6]),1-isobutenyl-3-methylimidazolium tetrafluoroborate([MPMIM][BF4])and[MPMIM][BF4]-AgBF4 have been determined by gas-liquid chromatography using ionic liquids as stationary phase.The measurements were carried out at different temperatures from 298 to 318 K.The separating effects of these ionic liquids for alkanes/hexane,aliphatic hydrocarbons/benzene and hexene isomers have been discussed.The hydrophobic parameter,dipole element,frontier molecular orbital energy gap and hydration energy of these hydrocarbons were calculated with the PM3 semi-empirical quantum chemistry method.The quantitative relations among the computed structure para-meters and activity coefficients at infinite dilution were also developed.The experimental activity coefficient data are consistent with the correlated and predicted results using QSPR models.