Irreversibility scrutinization on EMHD Darcy–Forchheimer slip flow of Carreau hybrid nanofluid through a stretchable surface in porous medium with temperature-variant properties

The significance of hybrid nanofluids in controlling heat transmission cannot be overemphasized. Therefore, this article scrutinizes the electromagnetized flow of Carreau hybrid nanofluid towards a stretching surface in a Darcy–Forchheimer porous medium with the occurrence of slip conditions. To form the hybrid nanofluid, the amalgamation of silver and alumina nanoparticles (NPs) embedded in water as conventional fluid is assumed. For accurate interception of the rate of heat and mass transport, thermal conductivity and mass diffusion conductance are presumed to be temperature variants. The modeling system of partial differential equations has been translated into a nondimensional form by means of suitable similarity conversions. Then, the subsequent system of ordinary differential equations is handled using overlapping domain decomposition spectral local linearization method to acquire numerical solutions. The choice of the method has been justified through the provision of errors, condition numbers, and computation time. The behavior of distinct fluid parameters on the flow features, quantities of engineering curiosity, and entropy is analyzed. Findings of paramount importance constitute that the superior thermal conductivity, heat transfer efficiency, and low production cost can be achieved through the hybridization of silver and alumina NPs. The role of thermal radiation and temperature-variant thermal conductivity is to enhance the thermal transport performance of Carreau hybrid nanofluids. The velocity, energy, and mass profiles grow with the utilization of injection effects. The principal aspiration of the second law of thermodynamics (minimizing the rate of entropy generation) can be achieved by considering shear-thinning Carreau fluid while reducing the porosity parameter and Brinkman number in the existence of velocity slip conditions in the flow system. Outcomes of the current flow model can play a significant role in biomedical, technological, and various manufacturing processes. The approximation of entropy contributes towards power engineering and aeronautical propulsion to anticipate the smartness of the overall system.