Computational enhancement of radiative and reactive magneto-thermal performance with CPHNF: A python-assisted analytical framework for biomedical applications

The aim of this study is to analyze the magnetohydrodynamic (MHD) behavior of Casson penta hybrid nanofluids (PHNFs) squeezed between two parallel plates, considering the effects of chemical reactions and thermal radiation. The Casson PHNF is composed of five nanomaterials: molybdenum disulfide, copper, magnesium oxide, aluminum oxide, and silver, each selected for its unique properties that enhance thermal conductivity, fluid behavior, and heat transfer. Partial differential equations (PDE) are converted into ordinary differential equations (ODE) using appropriate transformations and solved using Akbari Ganji Method (AGM). The novelty of this research is the use of PHNF as a new class of nanofluids and also the solution of the equations of the problem using the AGM method. The results indicate that the velocity is reduced by the rising squeeze number, Casson fluid parameter, and Hartmann number. Temperature profile is boosted by the rising Eckert number, while the elevated concentrations of nanoparticles reduce the temperature profile. Concentration profile is reduced by the rising Schmidt number. The results show that PHNF reduces the skin friction coefficient and Schroeder number and increases the Nusselt number compared to THNF. Using PHNF instead of THNF at constant parameters reduces the skin friction coefficient by 3.69%. At constant values of parameters, using PHNF instead of THNF improves the Nusselt number by 28.16%. Also, increasing Schmidt number from 1.5 to 2 increases the Sherwood number by 27.84%. The applications of Casson PHNFs are promising in advanced cooling systems, energy storage, and biomedical engineering, where efficient thermal management and friction reduction are critical.