Hybrid nanofluid heat transfer optimization for energy storage applications

The global energy crisis, driven by rising demand and finite fossil fuel reserves, demands advanced energy storage technologies. Hybrid nanofluids, with superior thermophysical properties arising from nanoparticle synergy, offer a transformative pathway for enhancing Thermal Energy Storage (TES) systems. This study optimizes the heat transfer performance of an engine oil-based hybrid nanofluid containing Ag and Cu nanoparticles for TES applications, focusing on radiative effects in a three-dimensional flow over a permeable stretching surface. Governing PDEs were reduced via similarity transformations and solved numerically using MATLAB's bvp4c and shooting method, while Response Surface Methodology (RSM) modeled the effects of nanoparticle volume fraction, heat source intensity, and magnetic field strength. Results show significant improvements in heat transfer and skin friction with the hybrid nanofluid compared to Cu/oil. Skin friction increased ∼50 % within 0.5 ≤ M ≤ 1.5 and 0.01 < Φ ≤ 0.03, while the heat source parameter (0.1 ≤ Hs ≤ 0.3) enhanced heat transfer by 32.5 %. Thermal performance improved by ∼50.83 % for Cu–Ag/oil versus Cu/oil. Quadratic models demonstrated excellent predictive accuracy (adjusted R 2 up to 100 %). Nanoparticle shape and density were also found to strongly influence flow and heat transfer. These findings highlight the Ag Cu hybrid nanofluid as a promising candidate for advanced energy systems.