Magnetic cilia carpets with programmable metachronal waves


Date

2020

Publication Type

Journal Article

ETH Bibliography

yes

Citations

Altmetric

Data

Abstract

Metachronal waves commonly exist in natural cilia carpets. These emergent phenomena, which originate from phase differences between neighbouring self-beating cilia, are essential for biological transport processes including locomotion, liquid pumping, feeding, and cell delivery. However, studies of such complex active systems are limited, particularly from the experimental side. Here we report magnetically actuated, soft, artificial cilia carpets. By stretching and folding onto curved templates, programmable magnetization patterns can be encoded into artificial cilia carpets, which exhibit metachronal waves in dynamic magnetic fields. We have tested both the transport capabilities in a fluid environment and the locomotion capabilities on a solid surface. This robotic system provides a highly customizable experimental platform that not only assists in understanding fundamental rules of natural cilia carpets, but also paves a path to cilia-inspired soft robots for future biomedical applications.

Publication status

published

Editor

Book title

Volume

11 (1)

Pages / Article No.

2637

Publisher

Nature

Event

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Applied physics; Biological physics; Engineering; Fluid dynamics

Organisational unit

03734 - Jackson, Andrew / Jackson, Andrew check_circle
03627 - Nelson, Bradley J. / Nelson, Bradley J. check_circle
08705 - Gruppe Pané Vidal check_circle
09700 - Ahmed, Daniel (ehemalig) / Ahmed, Daniel (former) check_circle

Notes

Funding

743217 - Soft Micro Robotics (EC)
185039 - Arbeitstitel "Soft Magnetic Robots: Modeling, Design and Control of Magnetically Guided Continuum Manipulators" (SNF)
179834 - The role of ambient flow and physico-chemical microenvironment in determining the microstructure of the biofilm matrix (SNF)

Related publications and datasets