High-Throughput Screening of Helical Microbot Geometries in Viscoelastic Media

Helical geometries are widely employed in magnetic micro-robotics to convert rotational actuation into translational motion for propulsion at low Reynolds numbers. Simplified models, including resistive force theory and slender body theory, enable prediction of the hydrodynamic performance of helical structures in viscous fluids. However, these models often fail to accurately capture behavior in viscoelastic media including biological soft tissues, which are highly relevant for biomedical applications. Efficient experimental methodologies are required to evaluate and optimize helical designs. Here, for the first time, we present a high-throughput screening framework for the parallel evaluation of multiple helical microbots in a viscoelastic medium. A library of helices with varying geometries was fabricated via 3D printing, incorporating interchangeable magnetic actuation components, and complemented by automated video-tracking algorithms for quantitative motion analysis. As a proof of concept, the helical pitch parameter was systematically investigated within a gelatin-based viscoelastic phantom. The results demonstrate a strong dependence of propulsion velocity on the pitch, with optimal performance observed for pitches in the range of 125.0-157.5 μm, consistent with single-robot validation results. This work establishes a scalable and efficient platform for the systematic characterization and optimization of helical microbots operating in complex viscoelastic environments.