Actuation-enhanced multifunctional sensing and information recognition by magnetic artificial cilia arrays

Artificial cilia integrating both actuation and sensing functions allow simultaneously sensing environmental properties and manipulating fluids in situ, which are promising for environment monitoring and fluidic applications. However, existing artificial cilia have limited ability to sense environme...

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Bibliographic Details
Published in:Proceedings of the National Academy of Sciences - PNAS 2023-10, Vol.120 (42), p.1-e2308301120
Main Authors: Han, Jie, Dong, Xiaoguang, Yin, Zhen, Zhang, Shuaizhong, Li, Meng, Zheng, Zhiqiang, Ugurlu, Musab Cagri, Jiang, Weitao, Liu, Hongzhong, Sitti, Metin
Format: Article
Language:English
Subjects:
Actuation
Boundaries
Cilia
Environmental monitoring
Flexible components
Fluid flow
Graphene
Machine learning
Physical Sciences
Sensors
Soft robotics
Viscosity
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Summary:Artificial cilia integrating both actuation and sensing functions allow simultaneously sensing environmental properties and manipulating fluids in situ, which are promising for environment monitoring and fluidic applications. However, existing artificial cilia have limited ability to sense environmental cues in fluid flows that have versatile information encoded. This limits their potential to work in complex and dynamic fluid-filled environments. Here, we propose a generic actuation-enhanced sensing mechanism to sense complex environmental cues through the active interaction between artificial cilia and the surrounding fluidic environments. The proposed mechanism is based on fluid–cilia interaction by integrating soft robotic artificial cilia with flexible sensors. With a machine learning-based approach, complex environmental cues such as liquid viscosity, environment boundaries, and distributed fluid flows of a wide range of velocities can be sensed, which is beyond the capability of existing artificial cilia. As a proof of concept, we implement this mechanism on magnetically actuated cilia with integrated laser-induced graphene-based sensors and demonstrate sensing fluid apparent viscosity, environment boundaries, and fluid flow speed with a reconfigurable sensitivity and range. The same principle could be potentially applied to other soft robotic systems integrating other actuation and sensing modalities for diverse environmental and fluidic applications.
ISSN:0027-8424
1091-6490
DOI:10.1073/pnas.2308301120