Research on the Motion Characteristics of Microrobots in Complex Viscoelastic Fluid Environments

Abstract

Microrobot technology demonstrates revolutionary potential in the biomedical field, enabling critical functions such as targeted drug delivery, minimally invasive interventions, and precise lesion clearance. However, significant challenges remain in understanding their motion mechanisms within complex biological environments. This study systematically investigates the dynamic behavior of capsule-shaped microrobots in Newtonian and viscoelastic fluids, focusing on the coupling effects of complex boundary conditions, surface-driven strategies, and rheological parameters. By constructing a multi-physics coupling framework based on the Linear Phan-Thien-Tanner (LPTT) constitutive model and employing numerical simulations and the control variable method, the nonlinear regulatory mechanisms of polymer viscosity , relaxation time , and elongation rate  on motion performance are revealed.Key findings include:In Newtonian fluids, an exponential-type surface-driven velocity profile generates stable propulsion due to its high-gradient velocity distribution, resulting in significantly higher average speeds compared to logarithmic and sinusoidal profiles.In viscoelastic fluids described by LPTT, a critical threshold for polymer viscosity (0.005Pa·s) exists: below this threshold, elastic stress dominates propulsion, while above it, viscous dissipation reduces efficiency.The parameter relaxation time regulates the dynamic balance between elastic stress accumulation and relaxation. Short (e.g., in lymph) facilitates rapid response, whereas long  causes local stress concentration, hindering propulsion. The influence of elongation rate is negligible in shear-dominated flow fields.The study proposes a multimodal driving strategy based on flow field-parameter adaptation criteria, providing theoretical guidance for targeted delivery and precise manipulation in heterogeneous biological environments such as blood and mucus. By integrating theory and simulation, this work lays a foundation for the design and optimization of next-generation medical microrobots.