A correlation-based predictor for pair-association in ionic liquids

Literature Information

Publication Date 2011-06-03
DOI 10.1039/C1CP21018A
Impact Factor 3.676
Authors

A. Maiti, R. D. Rogers


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Abstract

Pair association in Ionic Liquids is an important quantity that affects many of their physical and chemical properties. However, the association constant is a complex function of the component ions as well as of the solvent environment, and no single theory can compute or predict it with quantitative accuracy. In this work we analyze infinite-dilution association data from a number of recent conductance measurements, and develop a linear model correlating the association constant with two relevant interaction energies, i.e., (1) the dielectrically screened Coulomb attraction and hydrogen bonding between ion-pairs, and (2) the ion solvation energy, which in turn takes into account solvent-specific interactions like hydrogen-bond acidity/basicity and hydrophobic/hydrophilic interactions. The results reveal the unique nature of water as a solvent in that it affects ionic association in ways qualitatively different from other common solvents.

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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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