Solubility of freons in polar and non-polar liquids at 298.15 K

Guha, A.; Panda, Dibya Sundar

doi:10.1016/j.jfluchem.2003.09.005

Cited by 4 publications

(3 citation statements)

References 35 publications

(60 reference statements)

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“…The predicted value implied that the vaporization of SF 5 CF 3 from the water bodies to the atmosphere is remarkably high. On the other hand, the predicted value of K H for SF 5 CF 3 is significantly larger than the measured value (i.e., ln K H (MPa) = 10.04) of K H for SF 6 at 298.15 K [31,32]. It was also noted that SF 5 CF 3 is very stable in the atmosphere, implying that it does not exactly react with highly oxidative species (e.g., O 3 ) and free radicals such as hydroxyl radical and could not be decomposed by direct or sensitized photolysis, either.…”

Section: Henry's Law Constantmentioning

confidence: 62%

The prediction of environmental fate for trifluoromethyl sulfur pentafluoride (SF5CF3), a potent greenhouse gas

Tsai

2007

Journal of Hazardous Materials

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Section: Henry's Law Constantmentioning

confidence: 62%

The prediction of environmental fate for trifluoromethyl sulfur pentafluoride (SF5CF3), a potent greenhouse gas

Tsai

2007

Journal of Hazardous Materials

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“…Physical properties and parameters of solvents and solutes as the inputs of ANN that are listed in Section 1 have been extracted from literature works [27][28][29][30]. Also, the actual values of solubility are given in literature works [27][28][29][30][31][32][33][34][35].…”

Section: Resultsmentioning

confidence: 99%

“…Also, the actual values of solubility are given in literature works [27][28][29][30][31][32][33][34][35].…”

Section: Resultsmentioning

confidence: 99%

The solubility modelling of non-polar gases in polar and non-polar solvent based on scaled particle theory by artificial neural network

Akbari

Modarress

2013

Physics and Chemistry of Liquids

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In this work, the effective parameters of the scaled particle theory (SPT) are used as the input to the artificial neural network (ANN) to calculate as the output, the solubility (mole fraction of gas in liquid phase) of non-polar gases in polar and non-polar solvents at 298.15 K and 101.325 kPa. It has been found that ANN used in this work should has five neurons in the hidden layer to achieve the least error. The results of ANN have been compared with the experimental values. The results of this comparison are quite satisfactory. The average relative deviations of the simulations in training and testing stages have been calculated 0.92% and 0.89%, respectively. Finally, the results of ANN were compared with the results of SPT. According to this comparison, it is clear that SPT as a thermodynamic model predicts the solubility of the studied gases in the solvents with the same accuracy of ANN which is a purely mathematical model.

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Investigation and prediction of the salting-out effect of methane in various aqueous electrolyte solutions

Kim

Seo

Lee

et al. 2016

Journal of Industrial and Engineering Chemistry

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Solubility of freons in polar and non-polar liquids at 298.15 K

Cited by 4 publications

References 35 publications

The prediction of environmental fate for trifluoromethyl sulfur pentafluoride (SF5CF3), a potent greenhouse gas

The prediction of environmental fate for trifluoromethyl sulfur pentafluoride (SF5CF3), a potent greenhouse gas

The solubility modelling of non-polar gases in polar and non-polar solvent based on scaled particle theory by artificial neural network

Investigation and prediction of the salting-out effect of methane in various aqueous electrolyte solutions

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