ABSTRACT This study examines the effects of thermal radiation, magnetic field intensity, chemical reaction, and activation energy on momentum, heat, and mass transport in a micropolar nanofluid over a stretching sheet. The model incorporates Brownian motion, thermophoresis, and viscous dissipation to analyze velocity, temperature, and concentration fields. High‐resolution numerical solutions using MATLAB's bvp4c are used to train an artificial neural network (ANN) for fast and accurate prediction of flow variables and transport parameters. Engineering quantities such as Nusselt number, skin friction, couple stress, and Sherwood number are evaluated. Increasing magnetic and micropolar parameters enhances effective viscosity and skin friction, while higher radiation and Eckert numbers reduce thermal transport. Larger Schmidt number and chemical reaction increase mass transfer, and higher activation energy raises nanoparticle concentration.
Manojkumar et al. (Wed,) studied this question.