Entropy generation analysis of magnetized Sisko ferro-nanofluid flow over a porous stretching surface with heat and mass transfer effects

Improving the thermodynamic efficiency of magnetically controlled non - Newtonian nanofluid system is of considerable importance for advanced thermal management technologies. Motivated by the limited understanding of coupled irreversibility mechanisms in ferro-nanofluids, this study presents a comprehensive entropy analysis of magnetized Sisko ferro-nanofluid flow through a porous stretching surface under the combined effects of thermal radiation, heat source, viscous dissipation, Brownian diffusion, thermophoresis, and a first-order chemical reaction. Three ferrite nanoparticles namely nickel - zinc ferrite, manganese - zinc ferrite, and cobalt ferrite dispersed in water and ethylene glycol are comparatively investigated to evaluate their thermodynamic performance. The governing nonlinear partial differential equations are transformed into coupled ordinary differential equations using similarity transformations and solved numerically via the fourth-order Runge–Kutta shooting method. The numerical results demonstrate that entropy generation is predominantly governed by the combined influence of magnetic interaction, viscous dissipation, and non-Newtonian rheology. Increasing the Brinkman number, Sisko material parameter, heat source parameter, and Reynolds number intensifies fluid-friction irreversibility, leading to higher entropy generation and Bejan numbers. Conversely, thermal radiation enhances heat-transfer irreversibility and shifts the Bejan number toward unity, whereas porous permeability and magnetic parameter mechanisms contribute to reducing overall thermodynamic losses under appropriate operating conditions. Brownian motion, thermophoresis, chemical reaction, and nanoparticle volume fraction exhibit comparatively moderate effects on entropy generation but remain important for regulating heat and mass transport. Overall, the study identifies the dominant mechanisms governing thermodynamic irreversibility and demonstrates that appropriate combinations of magnetic field strength, porous permeability, nanoparticle loading, and thermal operating conditions can effectively minimize entropy generation. The proposed second-law optimization framework provides practical design guidance for magnetically assisted cooling systems, porous heat exchangers, polymer processing equipment, and advanced energy-conversion technologies.