This analysis reveals how hemodynamic factors like Reynolds number and hematocrit affect microrobot manipulation forces.
Microrobots hold significant promise for biomedical applications, yet precise determination of manipulation forces under hemodynamic conditions remains a challenge. Traditional numerical methods exhibit numerical instability or are limited to specific particle size ranges. In this study, we introduce a novel algorithm that integrates two immersed boundary methods for the hybrid computation of flexible deformable bodies and rigid particles. This algorithm exhibits high computational efficiency, minimal time step constraints, and is applicable across a wide range of particle stiffnesses. Utilizing this approach, we analyze the influence of Reynolds number, hematocrit, and particle position on the manipulation forces of spherical microrobots, which exhibit notable fluctuations due to random particle-cell interactions. During radial translation from the tube center to the wall, drag decreases while torque increases linearly, with lift peaking at intermediate radial positions. Increasing hematocrit enhances both drag and lift but has minimal effect on torque. Reynolds number shows a linear relationship with drag but a non-linear relationship with lift and torque. These findings provide crucial mechanical insights for the precise control of microrobots during hovering and radial translation in microvascular blood flow.
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Zhou et al. (2025) studied this question.
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