A Simple Prediction Method for the Surface Tension of Ionic Liquids as a Function of Temperature

Koller TM, Steininger C, Rausch MH, Fröba AP (2017)


Publication Language: English

Publication Status: Published

Publication Type: Journal article, Original article

Publication year: 2017

Journal

Publisher: SPRINGER/PLENUM PUBLISHERS

Book Volume: 38

Journal Issue: 11

DOI: 10.1007/s10765-017-2301-z

Abstract

In this study, a simple prediction method for the surface tension of ionic liquids (ILs) as a function of temperature is developed. Based on a database of experimental surface tension values collected from the literature, first a prediction scheme for the surface tension at a reference temperature of 298.15 K using only information on the density, molar mass, and anion type of the IL is suggested. By combination of this approach with the temperature dependence of the density, an extended prediction scheme describing the temperature dependence of the surface tension of ILs is recommended. The optimized prediction model for the surface tension allows for the prediction of about 3500 temperature-dependent experimental surface tension data of 226 different ILs with a standard deviation of about 7%. In comparison with fluid-specific prediction methods found in the literature, the developed simple empirical prediction model requires only easily accessible parameters and can be applied for ILs with arbitrary cation and anion combinations. Thus, the proposed prediction method seems to be a valuable engineering tool for the quantitative estimation of the surface tension of ILs.

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APA:

Koller, T.M., Steininger, C., Rausch, M.H., & Fröba, A.P. (2017). A Simple Prediction Method for the Surface Tension of Ionic Liquids as a Function of Temperature. International Journal of Thermophysics, 38(11). https://doi.org/10.1007/s10765-017-2301-z

MLA:

Koller, Thomas Manfred, et al. "A Simple Prediction Method for the Surface Tension of Ionic Liquids as a Function of Temperature." International Journal of Thermophysics 38.11 (2017).

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