As the clinical interest of robotic devices shifts to the development of small, autonomous, or remotely controlled systems, challenges remain regarding material biocompatibility, biodegradability, and execution of functional tasks in a programmed way. An ideal material so...
Active microswimmers have attracted considerable attention because of their potential applications, especially for biomedical applications such as cargo transport, targeted drug delivery, biosensors, and environment remediation. The main objective of our team is to develop new material platforms and system...
Macromolecular Bioscience, (0):1700377, March 2018 (article)
Abstract Programming materials with tunable physical and chemical interactions among its components pave the way of generating 3D functional active microsystems with various potential applications in tissue engineering, drug delivery, and soft robotics. Here, the development of a recapitulated fascicle‐like implantable muscle construct by programmed self‐folding of poly(ethylene glycol) diacrylate hydrogels is reported. The system comprises two stacked layers, each with differential swelling degrees, stiffnesses, and thicknesses in 2D, which folds into a 3D tube together. Inside the tubes, muscle cell adhesion and their spatial alignment are controlled. Both skeletal and cardiac muscle cells also exhibit high viability, and cardiac myocytes preserve their contractile function over the course of 7 d. Integration of biological cells with smart, shape‐changing materials could give rise to the development of new cellular constructs for hierarchical tissue assembly, drug testing platforms, and biohybrid actuators that can perform sophisticated tasks.
Programming local chemical properties of microscale soft materials with 3D complex shapes is indispensable for creating sophisticated functionalities, which has not yet been possible with existing methods. Precise spatiotemporal control of two-photon crosslinking is employed as an enabling tool for 3D patterning of microprinted structures for encoding versatile chemical moieties.
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems