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Han J, Dong X, Yin Z, Zhang S, Li M, Zheng Z, Ugurlu MC, Jiang W, Liu H, Sitti M. Actuation-enhanced multifunctional sensing and information recognition by magnetic artificial cilia arrays. Proc Natl Acad Sci U S A 2023; 120:e2308301120. [PMID: 37792517 PMCID: PMC10589697 DOI: 10.1073/pnas.2308301120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 09/04/2023] [Indexed: 10/06/2023] Open
Abstract
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.
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Affiliation(s)
- Jie Han
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569Stuttgart, Germany
- State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, 710054Xi’an, China
- School of Mechanical Engineering, Xi’an Jiaotong University, 710054Xi’an, China
| | - Xiaoguang Dong
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN37212
| | - Zhen Yin
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569Stuttgart, Germany
- Department of Control Science and Engineering, Tongji University, Shanghai201800, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai200120, China
| | - Shuaizhong Zhang
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569Stuttgart, Germany
- School of Mechanical Engineering, Yanshan University, Qinhuangdao066004, China
- National Key Laboratory of Hoisting Machinery Key Technology, Yanshan University, Qinhuangdao066004, China
- Hebei Key Laboratory of Heavy Machinery Fluid Power Transmission and Control, Yanshan University, Qinhuangdao066004, China
| | - Meng Li
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569Stuttgart, Germany
| | - Zhiqiang Zheng
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569Stuttgart, Germany
| | - Musab Cagri Ugurlu
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569Stuttgart, Germany
| | - Weitao Jiang
- State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, 710054Xi’an, China
- School of Mechanical Engineering, Xi’an Jiaotong University, 710054Xi’an, China
| | - Hongzhong Liu
- State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, 710054Xi’an, China
- School of Mechanical Engineering, Xi’an Jiaotong University, 710054Xi’an, China
| | - Metin Sitti
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569Stuttgart, Germany
- Institute for Biomedical Engineering, ETH Zürich, 8092Zürich, Switzerland
- School of Medicine and College of Engineering, Koç University, 34450Istanbul, Turkey
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