Imidazolium-Based Ionic Liquids Formed with Dicyanamide Anion:  Influence of Cationic Structure on Ionic Conductivity

2007 ◽  
Vol 111 (42) ◽  
pp. 12204-12210 ◽  
Author(s):  
Yukihiro Yoshida ◽  
Osamu Baba ◽  
Carlos Larriba ◽  
Gunzi Saito
Keyword(s):  
Ionic Liquids ◽  
Ionic Conductivity

ChemInform Abstract: Ionic Conductivity of Nanostructured Hybrid Materials Designed from Imidazolium Ionic Liquids and Kaolinite.

ChemInform ◽  
2009 ◽  
Vol 40 (8) ◽  
Author(s):  
Sadok Letaief ◽  
Thomas Diaco ◽  
Wendy Pell ◽  
Serge I. Gorelsky ◽  
Christian Detellier
Keyword(s):  
Ionic Liquids ◽  
Ionic Conductivity ◽  
Hybrid Materials ◽  
Imidazolium Ionic Liquids

scholarly journals 2D assemblies of ionic liquid crystals based on imidazolium moieties: formation of ion-conductive layers

2015 ◽  
Vol 39 (6) ◽  
pp. 4471-4477 ◽  
Author(s):  
Junji Sakuda ◽  
Masafumi Yoshio ◽  
Takahiro Ichikawa ◽  
Hiroyuki Ohno ◽  
Takashi Kato
Keyword(s):  
Ionic Liquid ◽  
Ionic Liquids ◽  
Liquid Crystals ◽  
Ionic Conductivity ◽  
Imidazolium Ionic Liquids ◽  
Ionic Liquid Crystals

Organization of imidazolium ionic liquids into 2D ion-conductive pathways enhances the ionic conductivity of the imidazolium-based ionic liquid crystals.

Effect of storage time on the ionic conductivity of chitosan-solid polymer electrolytes incorporating cyano-based ionic liquids

2017 ◽  
Vol 232 ◽  
pp. 22-29 ◽  
Author(s):  
Rita Leones ◽  
Rodrigo C. Sabadini ◽  
José M.S.S. Esperança ◽  
Agnieszka Pawlicka ◽  
M. Manuela Silva
Keyword(s):  
Ionic Liquids ◽  
Ionic Conductivity ◽  
Polymer Electrolytes ◽  
Storage Time ◽  
Solid Polymer Electrolytes ◽  
Solid Polymer

Phase Behavior and Ionic Conductivity in Lithium Bis(trifluoromethanesulfonyl)imide-Doped Ionic Liquids of the Pyrrolidinium Cation and Bis(trifluoromethanesulfonyl)imide Anion

2009 ◽  
Vol 113 (32) ◽  
pp. 11247-11251 ◽  
Author(s):  
Anna Martinelli ◽  
Aleksandar Matic ◽  
Per Jacobsson ◽  
Lars Börjesson ◽  
Alessandra Fernicola ◽  
...  
Keyword(s):  
Ionic Liquids ◽  
Ionic Conductivity ◽  
Phase Behavior

scholarly journals Developing Machine Learning Models for Ionic Conductivity of Imidazolium-Based Ionic Liquids

2021 ◽  
Author(s):  
Pratik Dhakal ◽  
Jindal Shah
Keyword(s):  
Machine Learning ◽  
Ionic Liquid ◽  
Ionic Liquids ◽  
Ionic Conductivity ◽  
Liquid Mixtures ◽  
Support Vector ◽  
Learning Models ◽  
Ideal Behavior ◽  
Original Dataset ◽  
Machine Learning Models

In this work, we have developed machine learning models based on support vector machine (SVM) and artificial neural network (ANN) to correlate ionic conductivity of imidazolium-based ionic liquids. The data, collected from the NIST ILThermo Database, spans six orders of magnitude and ranges from 275-475 K. Both models were found to exhibit very good performance. The ANN-model was then used to predict ionic conductivity for all the possible combinations of cations and anions contained in the original dataset, which led to the identification of an ionic liquid with 30% higher ionic conductivity than the highest conductivity reported in the database at 298 K. The model was further employed to predict ionic conductivity of binary ionic liquid mixtures. A large number of ionic liquid mixtures were found to possess non-ideal behavior in that an intermediate mole fraction for such ionic liquid mixtures resulted in either a maximum or minimum in the ionic conductivity.

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