Use of the DIPPR Database for Development of QSPR Correlations:  Surface Tension

Abstract

Combination of commercial QSPR (quantitative structure−property relationship) software with an evaluated database creates a powerful tool for development of thermophysical property correlations. By using data quality codes in the DIPPR relational database, a training set of property values within a desired accuracy level can be obtained for use in QSPR regression software. Moreover, additional database queries can be used to restrict the training set to specified families or functional groups and further refine the molecular descriptors that are used to correlate the property. This provides a good basis for rapid development of QSPR correlations of known uncertainty and chemical domain. This procedure is illustrated by its application to the extension of the Macleod−Sugden (Trans. Faraday Soc. 1923, 19, 38. Chem. Soc. 1924, 125, 32.) correlation for surface tension based upon the parachor. Quayle (Chem. Rev. 1953, 53, 439−591.) correlated the parachor in terms of additive atomic and structural increments but used a training set limited in temperature and scope. In this work, new molecular descriptors were selected consistent with the accuracy of the training set extracted from the DIPPR database, and their additive increments to the parachor were regressed from 8697 surface tension values of uncertainty less than 5% for 649 different compounds. This produced a correlation with an average absolute deviation (AAD) of 3.2%. This can be compared with an AAD of 6.9% using the Quayle descriptors for the same set.

Surface Tension of Ionic Liquids Analogues Using the QSPR Correlation

“…These differences in surface tension values might be due to the difference in water content in samples of Harris work and this work. The values of measured densities of DES2, DES5, DES8 and DES9 are almost equal to that reported in our previous work [19].To calculate the parachor of each DES, the parachors of constituting individual components (salt and HBD) of each DES were calculated using the published parachor contribution data [10]. In this study, only the accurate parachor data set (with uncertainties of less than 1%) proposed by Knotts et al [10] were employed.…”

“…To calculate the parachor of each DES, the parachors of constituting individual components (salt and HBD) of each DES were calculated using the published parachor contribution data [10]. In this study, only the accurate parachor data set (with uncertainties of less than 1%) proposed by Knotts et al [10] were employed.…”

“…In addition, Knotts et al [10] developed a QSPR correlation for the parachors using the huge amount of physical data available for neutral organic compounds in the DIPPR database [11]. Knotts et al [10] reported two individual parachor contribution data sets; the first data set was achieved using a training set containing experimental surface tension values with an uncertainty less than 5% and the second was obtained using surface tension data with uncertainties of less than 1%.…”

“…In addition, Knotts et al [10] developed a QSPR correlation for the parachors using the huge amount of physical data available for neutral organic compounds in the DIPPR database [11]. Knotts et al [10] reported two individual parachor contribution data sets; the first data set was achieved using a training set containing experimental surface tension values with an uncertainty less than 5% and the second was obtained using surface tension data with uncertainties of less than 1%.Although the parachor correlation proposed by Knotts et al [10] Deetlefs et al [12] attempted to employ the Knotts's parachor correlation for prediction of ionic liquids surface tension. They calculated parachors of ionic liquids using the neutral parachor contribution values and revealed that the differences between the corresponding experimental and calculated parachor values were sufficiently small.…”

Use of the DIPPR Database for the Development of QSPR Correlations: Solid Vapor Pressure and Heat of Sublimation of Organic Compounds

“…We have used this methodology to develop new predictive techniques for normal boiling point [2], surface tension [3], and the heat capacity [4] of solid organic compounds. Here, we extend that previous work to heats of sublimation, ∆H sub , and vapor pressures of solid organic compounds (SVP).…”