Developing a two-grade model for the thermal conductivity of ionic liquids and their mixtures

[Display omitted] •A two-grade model associating λ of ILs to λref, ρref and vref is developed.•The model is extended to binary mixture without requiring λ of each component.•The validity of the developed models is verified using collected database. Thermal conductivity (λ) is a crucial factor in the...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Chemical engineering science 2024-05, Vol.290, p.119881, Article 119881
Hauptverfasser: Wang, Chengjie, Wei, Xiaoyan, Jin, Xin, Li, Jinggang, He, Maogang
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:[Display omitted] •A two-grade model associating λ of ILs to λref, ρref and vref is developed.•The model is extended to binary mixture without requiring λ of each component.•The validity of the developed models is verified using collected database. Thermal conductivity (λ) is a crucial factor in the screening and design of ionic liquids (ILs) with desired thermal properties. Given the time consumption and computational inconvenience associated with structure-based models, a model grading strategy is proposed. This strategy aims to associate λ of ILs with their three reference properties separately in a two-grade model based on the kinetic theory and previous work. Subsequently, the model parameters are derived from the gathered database, and the prediction of λ is made with an average relative deviation (ARD) less than 5.78%. Further comparisons were conducted with the other three models, illustrating that our model exhibits high accuracy and is easily applicable, requiring only one of three reference properties. Finally, this model grading strategy is expanded to the determination of the thermal conductivity of binary mixtures (λm) of ILs without necessitating the individual λ values of each component. This approach accurately predicts the λm with an ARD less than 4.20%.
ISSN:0009-2509
1873-4405
DOI:10.1016/j.ces.2024.119881