Literature DB >> 21138303

In silico predictions of the temperature-dependent viscosities and electrical conductivities of functionalized and nonfunctionalized ionic liquids.

Philipp Eiden1, Safak Bulut, Tobias Köchner, Christian Friedrich, Thomas Schubert, Ingo Krossing.   

Abstract

The viscosity (η) and electrical conductivity (κ) of ionic liquids are, next to the melting point, the two key properties of general interest. The knowledge of temperature-dependent η and κ data before their first synthesis would permit a much more target-oriented development of ionic liquids. We present in this work a novel approach to predict the viscosity and electrical conductivity of an ionic liquid without further input of experimental data. For the viscosity, only some basic physical observables like the Gibbs solvation energy (ΔG(solv)(*,∞)), which was calculated at the affordable DFT-level (RI-)BP86/TZVP/COSMO, the molecular radius, calculated from the molecular volume V(m) of the ion volumes, and the symmetry number (σ), according to group theory, are necessary as input. The temperature dependency (253-373 K) of the viscosity (4-19000 mPa s) was modeled by an Arrhenius approach. An alternative way, which avoids the deficits of the Arrhenius relation by a series expansion in the exponential term, is also presented. On the basis of their close connection, the same set of parameters is suitable to describe the electrical conductivity as well (238-468 K, 0.003-193 mS/cm). Nevertheless, more elegant alternatives like the usage of the Stokes-Einstein/Nernst-Einstein relation or the Walden rule are highlighted in this work. During this investigation, we additionally found an approach to predict the dielectric constant ε* of an ionic liquid at 298 K by using V(m) and ΔG(solv)(*,∞) between ε* = 9 and 43.

Entities:  

Year:  2010        PMID: 21138303     DOI: 10.1021/jp108059x

Source DB:  PubMed          Journal:  J Phys Chem B        ISSN: 1520-5207            Impact factor:   2.991


  1 in total

1.  Modeling from Theory and Modeling from Data: Complementary or Alternative Approaches? The Case of Ionic Liquids.

Authors:  Alessio Paternò; Laura Goracci; Salvatore Scire; Giuseppe Musumarra
Journal:  ChemistryOpen       Date:  2017-01-09       Impact factor: 2.911

  1 in total

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