On the basis of the theoretical linear solvation energy relationship(TLSER) suggested by Wilson et al.and the quantum chemical descriptors computed by AM1 Hamiltonian,a predicting model was developed to characterize t...On the basis of the theoretical linear solvation energy relationship(TLSER) suggested by Wilson et al.and the quantum chemical descriptors computed by AM1 Hamiltonian,a predicting model was developed to characterize the activity coefficients at infinite dilution γi∞ of 34 organic solutes in ionic liquids(ILs) 1-butyl-3-methylimidazolium trifluoromethanesulfonate(BMIMCF3SO3) and 1-propyl-2,3-di-methylimidazolium tetrafluoroborate(PDMIMBF4) at 323.15 K.The results showed that the model had an good correlation and could successfully describe γi∞.In addition,correlation parameters are analyzed to understand the interactions that affect infinite dilution activity coefficients.展开更多
The study deals with modeling the vapor pressures of(solvent + salt) systems depending on the linear solvation energy relation(LSER) principles. The LSER-based vapor pressure model clarifies the simultaneous impact of...The study deals with modeling the vapor pressures of(solvent + salt) systems depending on the linear solvation energy relation(LSER) principles. The LSER-based vapor pressure model clarifies the simultaneous impact of the vapor pressure of a pure solvent estimated by the Xiang-Tan equation, the solubility and solvatochromic parameters of the solvent and the physical properties of the ionic salt. It has been performed independently two structural forms of the generalized solvation model, i.e. the unified solvation model with the integrated properties(USMIP) containing nine physical descriptors and the reduced property-basis solvation model. The vapor pressure data of fourteen(solvent + salt) systems have been processed to analyze statistically the reliability of existing models in terms of a log-ratio objective function. The proposed vapor pressure approaches reproduce the observed performance relatively accurately, yielding the overall design factors of 1.0643 and1.0702 for the integrated property-basis and reduced property-basis solvation models.展开更多
Inverse chromatography (IC) has been widely applied to characterize surface, interface, and bulk characteristics of technologically important materials. Probe molecules with known properties are injected into an isoth...Inverse chromatography (IC) has been widely applied to characterize surface, interface, and bulk characteristics of technologically important materials. Probe molecules with known properties are injected into an isothermal chromatographic system with the material of interest as stationary phase. The molecular interactions between chemicals and this material can be characterized from the retention of the probe chemicals. Linear solvation energy relationships (LSERs) have been successfully used for the characterization of molecular interactions involved in many partition[1] and adsorption[2,3] equilibria. In this study we combined the inverse liquid chromatography (ILC) and LSER method to characterize the molecular interactions between hydrophobic organic compounds (HOCs) and soils based on the retention factors of 28 probe HOCs, which were measured by soil column liquid chromatography (SCLC)[4-6].展开更多
基金Supported by the Beijing Municipal Training Programme for the Excellent Talents(Grant No.20081D0500500140)
文摘On the basis of the theoretical linear solvation energy relationship(TLSER) suggested by Wilson et al.and the quantum chemical descriptors computed by AM1 Hamiltonian,a predicting model was developed to characterize the activity coefficients at infinite dilution γi∞ of 34 organic solutes in ionic liquids(ILs) 1-butyl-3-methylimidazolium trifluoromethanesulfonate(BMIMCF3SO3) and 1-propyl-2,3-di-methylimidazolium tetrafluoroborate(PDMIMBF4) at 323.15 K.The results showed that the model had an good correlation and could successfully describe γi∞.In addition,correlation parameters are analyzed to understand the interactions that affect infinite dilution activity coefficients.
基金the Research Fund of Istanbul University for the technical support of this study.Project number 33167
文摘The study deals with modeling the vapor pressures of(solvent + salt) systems depending on the linear solvation energy relation(LSER) principles. The LSER-based vapor pressure model clarifies the simultaneous impact of the vapor pressure of a pure solvent estimated by the Xiang-Tan equation, the solubility and solvatochromic parameters of the solvent and the physical properties of the ionic salt. It has been performed independently two structural forms of the generalized solvation model, i.e. the unified solvation model with the integrated properties(USMIP) containing nine physical descriptors and the reduced property-basis solvation model. The vapor pressure data of fourteen(solvent + salt) systems have been processed to analyze statistically the reliability of existing models in terms of a log-ratio objective function. The proposed vapor pressure approaches reproduce the observed performance relatively accurately, yielding the overall design factors of 1.0643 and1.0702 for the integrated property-basis and reduced property-basis solvation models.
文摘Inverse chromatography (IC) has been widely applied to characterize surface, interface, and bulk characteristics of technologically important materials. Probe molecules with known properties are injected into an isothermal chromatographic system with the material of interest as stationary phase. The molecular interactions between chemicals and this material can be characterized from the retention of the probe chemicals. Linear solvation energy relationships (LSERs) have been successfully used for the characterization of molecular interactions involved in many partition[1] and adsorption[2,3] equilibria. In this study we combined the inverse liquid chromatography (ILC) and LSER method to characterize the molecular interactions between hydrophobic organic compounds (HOCs) and soils based on the retention factors of 28 probe HOCs, which were measured by soil column liquid chromatography (SCLC)[4-6].
