Exploring the role of biopolymers and surfactants on the electrical conductivity of water-based CuO, Fe₃O₄, and hybrid nanofluids

Abstract

The research on the application of nanofluids in the thermal management of electric components is gaining widespread attention. In this context, and as past studies on nanofluids mainly focus on thermal properties, the investigation of the electrical properties of nanofluids has become important. The role of dispersants on the electrical conductivity of nanofluids stabilized using two biopolymer dispersants, chitosan, and gum arabica (GA), and a synthetic dispersant Sodium Dodecyl Benzoic Sulfate (SDBS) is investigated in this work. The nanofluids are prepared with water, nanoparticles (0.1 wt%), and dispersants (0.05 and 0.5 wt%), and the electrical conductivity is measured to examine the role of nanoparticle materials (CuO, Fe₃O₄, and CuO + Fe₃O₄), dispersants, and temperatures (25–40 °C). According to observations, the dispersants significantly affect the electrical conductivity, while nanoparticle material has a minimal impact. At 0.5 wt% concentration, SDBS stabilized nanofluids have electrical conductivity 708.7 times higher than water, whereas, with chitosan and GA, it is 144.2 and 12.8 times higher than water, respectively. CuO-water nanofluids show relatively higher electrical conductivity than Fe₃O₄ and hybrid CuO + Fe₃O₄ water nanofluids. Measured electrical conductivity is used for regression analysis using response surface methodology (RSM). Three quadratic nonlinear polynomial equations are developed to predict the electrical conductivity based on the input parameters (dispersant concentration and temperature). The predicted and measured values were in excellent agreement with each other. The current study offers a novel perspective on the electrical behavior of nanofluids with biopolymer dispersants and provides a prediction model for nanofluid electrical conductivity.

Graphical Abstract

Keywords:

• Nanofluids
• biopolymers
• electrical conductivity
• RSM
• regression

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.