Study of nanoparticle morphology effect on fluid flow between two active parallel plates.

The thermophysical performance of nanofluids is strongly influenced by nanoparticle morphology, making realistic property modeling essential for accurately predicting coupled flow and heat transfer characteristics in advanced thermal systems. Motivated by this need, the present study investigates magnetohydrodynamic flow of nanofluid between two active parallel plates embedded in a porous medium under quadratic thermal radiation and convective boundary condition. Multiple viscosity and thermal conductivity correlations, including morphology-dependent models for spherical, brick, cylindrical and platelet nanoparticles, are incorporated to quantify their influence on momentum and heat transfer. The governing nonlinear partial differential equations are transformed into coupled ordinary differential equations using similarity transformations and solved through the Tchebichef polynomial collocation method. Numerical accuracy is verified using the Runge-Kutta-Fehlberg fourth-fifth order method, while a Levenberg-Marquardt artificial neural network is employed to predict the nonlinear velocity and temperature fields. Results demonstrate that increasing magnetic field strength and porous resistance suppress velocity, whereas larger radiation and Biot numbers enhance temperature. The proposed framework provides reliable guidance for thermal management technologies.