Towards the Application of Structure–Property Relationship Modeling in Materials Science: Predicting the Seebeck Coefficient for Ionic Liquid/Redox Couple Systems. Issue 11 (22nd March 2016)

• Record Type: Journal Article
• Authors: Sosnowska, Anita; Barycki, Maciej; Gajewicz, Agnieszka; Bobrowski, Maciej; Freza, Sylwia; Skurski, Piotr; Uhl, Stefanie; Laux, Edith; Journot, Tony; Jeandupeux, Laure; Keppner, Herbert; Puzyn, Tomasz
• Is Part Of: Chemphyschem. Volume 17:Issue 11(2016)
• Page Start: 1591
• Page End: 1600
• Publication Date: 2016-03-22
• Subjects: computational chemistry -- ionic liquids -- materials science -- redox chemistry -- structure–activity relationships; Chemistry, Physical and theoretical -- Periodicals; 541.05
• DOI: 10.1002/cphc.201600080
• Languages: English
• ISSNs: 1439-4235

Abstract

Abstract: This work focuses on determining the influence of both ionic‐liquid (IL) type and redox couple concentration on Seebeck coefficient values of such a system. The quantitative structure–property relationship (QSPR) and read‐across techniques are proposed as methods to identify structural features of ILs (mixed with LiI/I2 redox couple), which have the most influence on the Seebeck coefficient ( S e ) values of the system. ILs consisting of small, symmetric cations and anions with high values of vertical electron binding energy are recognized as those with the highest values of S e . In addition, the QSPR model enables the values of S e to be predicted for each IL that belongs to the applicability domain of the model. The influence of the redox‐couple concentration on values of S e is also quantitatively described. Thus, it is possible to calculate how the value of S e will change with changing redox‐couple concentration. The presence of the LiI/I2 redox couple in lower concentrations increases the values of S e, as expected. Abstract : Go where no IL has gone before : Experimentally measured Seebeck coefficient ( S c ) values for systems composed of an ionic liquid (IL) and LiI/I2 redox couple are presented. Parameters responsible for the variation of S c for different systems are described. A mathematical model is introduced that allows the prediction of S c on the basis of a combined computational chemistry and chemometric approach (see figure).