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<p>This study evaluates the synergistic enhancement of thermal conductivity in water-based hybrid nanofluids containing copper (Cu) and boron nitride (BN) nanoparticles. The increasing demand for efficient cooling fluids in industrial and energy systems highlights the need for advanced nanofluids with superior thermal properties. Hybrid nanofluids were synthesized by combining Cu/water nanofluids with BN nanoparticles at varying mass fractions (0.05–0.20 mass%). Thermal conductivity was measured at 30–50&#xa0;°C using the transient hot-wire method. Results demonstrated a nonlinear increase in thermal conductivity with rising temperature and increasing nanoparticle concentration. At 50&#xa0;°C, the hybrid nanofluid with 0.20&#xa0;mass% Cu and BN achieved a maximum thermal conductivity enhancement of 21.2% compared to water. This enhancement was attributed to intensified Brownian motion, nanoparticle clustering, and enhanced phonon transport. A novel empirical correlation was developed to predict the thermal conductivity of BN-Cu hybrid nanofluids with high accuracy (<i>R</i><sup>2</sup> = 0.987), providing a valuable predictive tool for future engineering applications. This work builds on previous research by offering a comprehensive experimental dataset and a predictive model, supporting the optimization of hybrid nanofluids for industrial cooling and heat transfer applications.</p>

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Experimental investigation of synergistic thermal conductivity enhancement in water-based hybrid nanofluids with copper and boron nitride nanoparticles

  • 期刊论文

  • 发表日期：

    2025年5月5日

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  • Rashid Pourrajab,
  • Mohammad Behbahani,
  • Reza Mansouri

摘要

This study evaluates the synergistic enhancement of thermal conductivity in water-based hybrid nanofluids containing copper (Cu) and boron nitride (BN) nanoparticles. The increasing demand for efficient cooling fluids in industrial and energy systems highlights the need for advanced nanofluids with superior thermal properties. Hybrid nanofluids were synthesized by combining Cu/water nanofluids with BN nanoparticles at varying mass fractions (0.05–0.20 mass%). Thermal conductivity was measured at 30–50 °C using the transient hot-wire method. Results demonstrated a nonlinear increase in thermal conductivity with rising temperature and increasing nanoparticle concentration. At 50 °C, the hybrid nanofluid with 0.20 mass% Cu and BN achieved a maximum thermal conductivity enhancement of 21.2% compared to water. This enhancement was attributed to intensified Brownian motion, nanoparticle clustering, and enhanced phonon transport. A novel empirical correlation was developed to predict the thermal conductivity of BN-Cu hybrid nanofluids with high accuracy (R2 = 0.987), providing a valuable predictive tool for future engineering applications. This work builds on previous research by offering a comprehensive experimental dataset and a predictive model, supporting the optimization of hybrid nanofluids for industrial cooling and heat transfer applications.