Ganesan A/l Kadirgama creator author. text my 2025 2025 monographic eng xv, 138 pages : illustration ; 30 cm.+ 1 CD-ROM Efficient thermal management plays a critical role in various industrial applications, particularly in systems utilizing Therminol 55, where the selection of appropriate heat transfer fluids can significantly influence system performance. This study investigates the thermophysical properties of hybrid alumina-copper oxide (Al2O3-CuO) nanoparticles dispersed in Therminol 55, focusing on enhancing both thermal conductivity and viscosity. The research aims to develop a superior heat transfer fluid for medium-temperature applications by optimizing the nanoparticle concentration and hybrid ratio. A one-step ultrasonication method was employed to achieve homogeneous dispersion of the nanoparticles, ensuring optimal stability. Concentrations of the hybrid nanoparticles were varied from 0.1 wt% to 1.0 wt%, with three hybrid ratios of Al2O3 to CuO (10:90, 20:80, and 30:70) tested.The experimental results demonstrated that the hybrid nanofluids exhibited notable improvements in thermal properties. Specifically, the formulation with a 0.5 wt% concentration and a 30:70 ratio of Al2O3 to CuO achieved the highest thermal conductivity, recording a 27% increase compared to pure Therminol 55. This enhanced thermal conductivity was attributed to the synergistic effects of combining Al2O3, known for its thermal stability, with CuO, which offers high thermal conductivity. In contrast, the viscosity of the optimized nanofluid increased by 45%, presenting a challenge in balancing improved heat transfer and fluid flow. The study also observed that viscosity decreased with increasing temperature, highlighting the potential for practical applications at elevated operating conditions.To further analyze the complex interactions influencing the thermal behavior of the hybrid nanofluids, a machine learning model was developed using the Adaptive Neuro-Fuzzy Inference System (ANFIS). The model was designed to predict both thermal conductivity and viscosity under varying conditions of temperature, concentration, and nanoparticle ratio. The ANFIS model achieved high accuracy, with a mean absolute error (MAE) of 0.015 W/m.K for thermal conductivity and 0.009 mPa.s for viscosity predictions. This demonstrated the model’s capability to capture nonlinear dependencies between input parameters. The findings from this study indicate that hybrid alumina-copper oxide nanofluids in Therminol 55 hold significant promise for enhancing the efficiency of medium-temperature heat transfer systems. In addition to offering improved thermal performance over conventional nanofluids containing either Al2O3 or CuO alone, the hybrid formulation also demonstrated long-term stability and resistance to sedimentation, making it suitable for real-world industrial applications. The study’s contributions are aligned with global sustainability goals, particularly SDG 7 (Affordable and Clean Energy) and SDG 9 (Industry, Innovation, and Infrastructure) with 10-10 MySTIE Framework in Energy and Advanced Materials the research offers practical insights into sustainable energy. specialized Ganesan A/l Kadirgama Faculty of Chemical and Process Engineering Technology Thesis (Doctor of Philosophy) -- Universiti Malaysia Pahang Al Sultan Abdullah - 2025 Include bibliographical reference Faculty of Chemical and Process Engineering Technology Dissertations Universities and colleges Dissertations Theses Dissertations THE0010341 (Local) UMPSA 260216 20260216183025.0 eng