Predicting physical properties of ionic liquids

Literature Information

Publication Date 2005-12-01
DOI 10.1039/B513453F
Impact Factor 3.676
Authors

Michael Shara


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Abstract

A simple method to predict the densities of a range of ionic liquids from their surface tensions, and vice versa, using a surface-tension-weighted molar volume, the parachor, is reported. The parachors of ionic liquids containing 1-alkyl-3-methylimidazolium cations were determined experimentally, but were also calculated directly from their structural compositions using existing parachor contribution data for neutral compounds. The calculated and experimentally determined parachors were remarkably similar, and the latter data were subsequently employed to predict the densities and surface tensions of the investigated ionic liquids. Using a similar approach, the molar refractions of ionic liquids were determined experimentally, as well as calculated using existing molar refraction contribution data for uncharged compounds. The calculated molar refraction data were employed to predict the refractive indices of the ionic liquids from their surface tensions. The errors involved in the refractive index predictions were much higher than the analogous predictions employing the parachor, but nevertheless demonstrated the potential for developing parachor and molar refraction contribution data for ions as tools to predict ionic liquid physical properties.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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