Crystal Phase Ionic Liquids for Energy Applications: Heat Capacity Prediction via a Hybrid Group Contribution Approach

• Published in: Molecules (Basel, Switzerland) Vol. 29; no. 9; p. 2130
• Main Authors: Shahin, Moh'd Basel, Liaqat, Shehzad, Nancarrow, Paul, McCormack, Sarah J
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.05.2024
• Subjects: crystal phase; Design; Energy storage; Force and energy; Fuel cell industry; group contribution; Heat; heat capacity; Heat storage; International economic relations; ionic liquids; Molecular structure; Phase transitions; predictive model; Python; Technology application; Thermal energy; Thermodynamics; VOCs; Volatile organic compounds; heat capacity; crystal phase; predictive model; group contribution; ionic liquids
• ISSN: 1420-3049; 1420-3049
• DOI: 10.3390/molecules29092130

In the selection and design of ionic liquids (ILs) for various applications, including heat transfer fluids, thermal energy storage materials, fuel cells, and solvents for chemical processes, heat capacity is a key thermodynamic property. While several attempts have been made to develop predictive models for the estimation of the heat capacity of ILs in their liquid phase, none so far have been reported for the ILs' solid crystal phase. This is particularly important for applications where ILs will be used for thermal energy storage in the solid phase. For the first time, a model has been developed and used for the prediction of crystal phase heat capacity based on extending and modifying a previously developed hybrid group contribution model (GCM) for liquid phase heat capacity. A comprehensive database of over 5000 data points with 71 unique crystal phase ILs, comprising 42 different cations and 23 different anions, was used for parameterization and testing. This hybrid model takes into account the effect of the anion core, cation core, and subgroups within cations and anions, in addition to the derived indirect parameters that reflect the effects of branching and distribution around the core of the IL. According to the results, the developed GCM can reliably predict the crystal phase heat capacity with a mean absolute percentage error of 6.78%. This study aims to fill this current gap in the literature and to enable the design of ILs for thermal energy storage and other solid phase applications.