Modeling heat capacity of ionic liquids using group method of data handling: A hybrid and structure-based approach

Alireza Rostami, Abdolhossein Hemmati-Sarapardeh, Abdorreza Karkevandi-Talkhooncheh, Maen M. Husein, Shahaboddin Shamshirband, Timon Rabczuk

Research output: Contribution to journalArticlepeer-review

36 Citations (Scopus)


Ionic liquids (ILs) are a significant class of chemicals with applications in solar cells, sensors, capacitors, batteries, plasticizers and thermal fluids. These compounds have attracted wide attention due to their low vapor pressure, tunable viscosity, non-flammability, wide liquid region phase diagrams and substantial chemical and thermal stability. Moreover, ILs structures can be easily modified leading to highly tunable physicochemical properties, which widen the application of these compounds. Heat capacity of ILs is an essential property for heat transfer evaluation as well as the estimation of widely used thermodynamic properties. Establishing a generalized and accurate model for predicting the heat capacity of ILs is valuable for their further development. In this manuscript, a hybrid group method of data handling (GMDH) was employed to establish a model estimating the ILs heat capacities. The database employed is an all-inclusive source of data taken from NIST standard, which includes the heat capacities of 56 ILs as a function of temperature and four structural parameters. About 80% of the database was assigned for building the model, and the remainder was used for evaluating the model performance. Statistical parameters and graphical techniques revealed that the model developed in this study is very accurate, with an R2 value of 0.982 and an average absolute percent relative error (AAPRE) of 1.84%. Moreover, the sensitivity analysis showed that the chemical structure of the cation has the highest impact on the heat capacity of ILs.

Original languageEnglish
Pages (from-to)7-17
Number of pages11
JournalInternational Journal of Heat and Mass Transfer
Publication statusPublished - 2019 Feb


  • Comprehensive error analysis
  • Group method of data handling
  • Heat capacity
  • Ionic liquids
  • Model
  • Sensitivity analysis

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Mechanical Engineering
  • Fluid Flow and Transfer Processes


Dive into the research topics of 'Modeling heat capacity of ionic liquids using group method of data handling: A hybrid and structure-based approach'. Together they form a unique fingerprint.

Cite this