Mechanically Transduced Soft Magnetic Rollers

ORAL

Abstract

Active soft autonomous systems integrated into biological systems is a new and emerging field with a myriad of potential applications. Here we present a novel soft active robotic system composed of functionalized ferromagnetic rollers. This system leverages the fundamental physical principle of friction at the microscopic level to autonomously control the amount of translational displacement of the ferromagnetic rollers. By functionalizing the ferromagnetic roller with biological ligands and a substrate coated with a corresponding binding ligand partner the friction coefficient is controlled by the strength and density of such biological binding interaction. The coefficient of friction will determine the amount of translational displacement. The ferromagnetic rollers are made active by actuation of an externally applied rotating magnetic and the rollers will proceed to translate as the rotational motion is converted to translational displacement due to friction between the ferromagnetic rollers and the substrate. The larger the coefficient of friction the larger the translational displacement and in this active soft robotic system the friction scales with the strength and density of the biological binding interaction. Here, we demonstrate this soft robotic system by functionalizing the surface of substrate with ubiquitin binding ligands and the rollers were coated with ubiquitin. Ubiqutin is one of the most ubiquitous proteins encountered in biological systems and we demonstrate how the displacement of the roller increases as the strength of interaction between ubitquin and the substrate ligands increases. This new approach opens up novel avenues for these soft robotic rollers to autonomously navigate biological soft substrates decorated with a myriad of different biological ligands.

Publication: https://www.nature.com/articles/s41594-023-01105-5

Presenters

  • Joshua P Steimel

    Cal Poly Humboldt

Authors

  • Joshua P Steimel

    Cal Poly Humboldt

  • Nicholas Brown

    UNC

  • Joseph Harrison

    UOP

  • Alfredo Alexander-Katz

    MIT, Massachusetts Institute of Technology