Enhanced heat performances of penta-hybrid nanofluid flow across a stretching surface employing the homotopy perturbation method: An artificial neural network approach

This research investigates the heat and mass transfer properties and flow behavior of magnetohydrodynamic viscous non-Newtonian penta-hybrid nanofluid flow along a porous stretching surface. The present investigation considered the influence of thermal radiation, heat generation/absorption, Joule heating, chemical reaction, and first-order velocity slip at the wall. Similarity transformations are used to reduce the flow's nonlinear partial differential equations to ordinary differential equations and solved through the Homotopy Perturbation Method. Additionally, an artificial neural network is employed to validate and optimize the computational results, enhancing accuracy in predicting skin friction characteristics. A comparative analysis of various nanoparticles, such as metals and metal oxides, is conducted to examine their influence on heat and mass transfer, surface drag. The research identifies that penta-hybrid nanofluids have a significant influence on heat and mass transfer compared to tetra-hybrid and tri-hybrid nanofluids, with the highest contribution to skin friction from silver (Ag), the best heat transfer from zirconium dioxide (ZrO2), and the highest mass transfer from copper oxide (CuO). These results have extensive applications in thermal energy management, electronic cooling, aerospace thermal control, and biomedical systems. They also have applications in nuclear reactor cooling, microfluidic devices, and chemical process industries, where the regulation of heat and mass transfer is critical. The improved properties of penta-hybrid nanofluids also make them applicable to renewable energy systems, such as solar thermal collectors and geothermal energy systems. Since very few previous studies have taken into account penta-hybrid nanofluids, this research presents new knowledge of their potential for improved engineering and industrial applications.