A simple correlation to predict surface tension of binary mixtures containing ionic liquids

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@Article{ESMAEILI:2021:JML,

• author = "Hadi Esmaeili and Hassan Hashemipour",
• title = "A simple correlation to predict surface tension of binary mixtures containing ionic liquids",
• journal = "Journal of Molecular Liquids",
• volume = "324",
• pages = "114660",
• year = "2021",
• ISSN = "0167-7322",
• DOI = "doi:10.1016/j.molliq.2020.114660",
• URL = "https://www.sciencedirect.com/science/article/pii/S0167732220369026",
• keywords = "genetic algorithms, genetic programming, Surface tension, Ionic liquids, Binary mixture, Multi-gene genetic programming, Correlation",
• abstract = "Ionic liquids are in a developing situation in nowadays research and industrial atmosphere. In some industrial applications and academic researches, one will face with binary mixtures containing ionic liquids, therefore; many studies have been done evaluating the properties of binary mixtures containing ionic liquids. In this study, it has been tried to find a general trend and precise correlation to predict surface tension of binary mixtures containing ionic liquids. To do this, Multi-Gene Genetic Programming (MGGP), which is one of the most powerful techniques of soft computing, has been used. Mole fraction, Temperature, Molecular weight of two components and boiling point have been used as input parameters of the network, where surface tension of the mixture was the output parameter. Using the mentioned parameters and MGGP, precise networks obtained. On top of that, using MGGP, a general correlation has been generated for obtaining surface tension of binary mixtures containing Ionic Liquids variable with just mole fraction and in constant temperature. Moreover, adding one term to the mentioned correlation gave a precise correlation for the surface tension variable with mole fraction and temperature. These two correlations are very promising and simplifying for determining the surface tension of binary mixtures containing ionic liquids. The precision of these correlations has been evaluated using correlation coefficient (R2) and AARD, which was respectively, average 0.994 and 0.9567percent for all used binary mixtures",

}

Genetic Programming entries for Hadi Esmaeili Hassan Hashemipour

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