Two-Phase Hybrid Nanofluid–Liquid Metal MHD Flow with Interfacial Slip for Drug Delivery

Magnetohydrodynamic (MHD) flows of hybrid nanofluids offer significant potential in biomedical engineering, particularly for enhancing site-specific drug delivery. Traditional drug transport methods often lack precise control over particle accumulation, limiting therapeutic efficiency. This study develops a novel two-phase MHD model that couples an Fe₂O₃–H₂O nanofluid with a gallium-based liquid metal under interfacial slip conditions to improve targeted drug delivery. The primary objective is to investigate the combined effects of magnetic fields, interfacial slip, and nanoparticle dynamics on fluid transport, heat transfer, and drug accumulation at the nanofluid–metal interface. The model incorporates Brownian motion, thermophoresis, viscous dissipation, thermal radiation, and chemical reaction effects to accurately capture the coupled mass and heat transfer processes. The governing nonlinear equations are transformed using similarity methods and solved numerically with a finite difference approach, incorporating adaptive mesh refinement to ensure stability and convergence. Results indicate that increasing the magnetic field (Hartmann number) enhances interface stability by up to 36%. Brownian motion and thermophoresis increase nanoparticle concentration near the interface by approximately 22% and 18%, respectively, facilitating improved drug transport. The combined electromagnetic and thermophoretic effects further raise the local drug accumulation by nearly 30% compared to non-magnetic flow conditions. In conclusion, the proposed hybrid nanofluid–liquid metal two-phase model provides a new computational framework for magnetically guided, site-specific drug delivery. The findings offer valuable insights for designing advanced biomedical systems where precise control of nanoparticle-mediated drug transport is critical, demonstrating that interfacial slip and electromagnetic effects can significantly enhance therapeutic efficiency.