A simple correlation to predict surface tension of binary mixtures containing ionic liquids
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- @Article{ESMAEILI:2021:JML,
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author = "Hadi Esmaeili and Hassan Hashemipour",
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title = "A simple correlation to predict surface tension of
binary mixtures containing ionic liquids",
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journal = "Journal of Molecular Liquids",
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volume = "324",
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pages = "114660",
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year = "2021",
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ISSN = "0167-7322",
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DOI = "doi:10.1016/j.molliq.2020.114660",
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URL = "https://www.sciencedirect.com/science/article/pii/S0167732220369026",
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keywords = "genetic algorithms, genetic programming, Surface
tension, Ionic liquids, Binary mixture, Multi-gene
genetic programming, Correlation",
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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
Citations