Artificial Microtubules from Microrobot Swarm Unraveling for Directed Cargo Transport under Confinement
Abstract
Abstract Cargo transport on artificial microtubules (AMTs) has been extensively explored in various biomedical applications, including drug delivery and cancer therapy. However, the transport velocity and directional controllability are still poor compared to their natural counterparts, especially under confinement. Here, we show that confinement can induce the spontaneous formation of AMTs from structural transformations of microrobot swarms, and that these AMTs are particularly adept at directionally controlled cargo transport. It is shown that a magnetically driven microrobot cluster, when locally pinned, can be unraveled along the boundary into a strand that can function as a microtubule thanks to collective tangential flows. We demonstrate with both experiments and simulations that the local pinning required for AMT formation can come from a single pinned particle, or from corners and necks ubiquitous in microchannels and cavities. By modulating the driving magnetic field, the microtubule formation process can be precisely manipulated following periodic perturbations and re‐establishments of local order, thereby simultaneously controlling the velocity and direction of cargo transport. The general applicability of this method has also been tested in biological environments including flowing blood, as well as in an in vitro delivery model under confinement.
Article Details
Authors (9)
Xiaoyu Wang
Hari Krishna Bisoyi
Materials Science Graduate Program Kent State University Kent Ohio USA
Jie Wang
State Key Laboratory of Molecular Oncology, Beijing Key Laboratory, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology Cancer Hospital, Chinese Academy of Medical Sciences Beijing China
Yongkang Wang
Shuai Huang
Shandong Provincial Key Laboratory of Development and Regeneration, School of Life Sciences, Shandong University
Zhiyang Liu
Tao Yang
Brennan Sprinkle
Department of Applied Math and Statistics, Colorado School of Mines
Quan Li