On Modeling of Surface Tension of CMC-α-Fe2O3 Nanoparticles by Fuzzy-Hybrid Approach: A Comparison Study

Köçken H., Insel M. A., Temelcan G., Karakuş S., Albayrak F. İ.

CANADIAN JOURNAL OF CHEMICAL ENGINEERING, vol.101, no.11, pp.6446-6454, 2023 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 101 Issue: 11
  • Publication Date: 2023
  • Doi Number: 10.1002/cjce.24884
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Aqualine, Chemical Abstracts Core, Chimica, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, Pollution Abstracts, Civil Engineering Abstracts
  • Page Numbers: pp.6446-6454
  • Keywords: fuzzy regression, mathematical modelling, nanomaterials, surface tension
  • Yıldız Technical University Affiliated: Yes


Surface tension is one of the most important rheological parameters of nanoliquids. It influences the thermophysical and mass transfer properties of nanostructures. Accurate estimation of the surface tension from operating variables is critical for determining optimal production processes. However, the challenges of producing nanoparticles and measuring their properties introduce experimental errors in the data used for mathematical modeling. Crisp regression approaches provide adequate representation of the data, but they do not provide information about the experimental uncertainty. In this study, a fuzzy-hybrid approach is proposed for mathematical modeling of surface tension of carboxymethyl cellulose/chitosan-α-Fe2O3 nanoparticles. Then, the proposed model is compared with a crisp model from a previous study. Error analysis is conducted to validate the constructed fuzzy model. It is observed that the fuzzy-hybrid modeling approach has yielded significantly lower error values (60% - 90% improvement in all error metrics on average), and thus, it is superior to the crisp approach. This study contributes to the subject of modeling rheological properties. It is shown that the fuzzy-hybrid approach has an impressive potential to be utilized for modeling the rheological properties of nanostructures.