Electro-osmotic metachronal cilia transport of viscoelastic blood infused with penta-hybrid nanoparticles in an oviduct: Analytical and neural network modeling.

An analytical and computational model is developed for the electro-osmotic peristaltic transport of pentahybrid nanoparticle-infused Phan-Thien-Tanner viscoelastic blood through a heated, cilia-lined human fallopian tube, integrating metachronal ciliary wave dynamics, electric double layer forcing, shear-thinning rheology, viscous dissipation, and Joule ohmic heating within a unified framework. Closed-form solutions are derived under the Debye-Hückel linearisation and long-wavelength approximations for the transport profiles and metrics across six blood formulations of progressively increasing nanoparticle enrichment. Key results show that electro-osmotic forcing consistently augments axial velocity and reduces the pressure gradient burden, while a co-directional electric field enhances and an opposing field suppresses net peristaltic flux; bulk temperature rises with Joule heating and viscous dissipation but falls with increasing viscoelasticity and cilia density; and streamline bolus morphology is sensitively governed by the electro-osmotic parameter, electric field polarity, Weissenberg number, and flow rate, each producing distinct recirculation cell structures with implications for near-wall drug mixing. Levenberg-Marquardt trained artificial neural network surrogate models for wall shear stress and heat transfer coefficient achieve near-unity regression coefficients, Gaussian zero-centred error distributions, and statistically white residuals, establishing their reliability as computationally efficient surrogate predictive model for parametric design for parametric design of electro-osmotically driven reproductive drug delivery and electrostimulation therapy systems.