Battery-free, wireless, and electricity-driven soft swimmer for water quality and virus monitoring

Dengfeng Li (Co-first Author), Jingkun Zhou (Co-first Author), Zichen Zhao (Co-first Author), Xingcan Huang (Co-first Author), Hu Li (Co-first Author), Qing'ao Qu, Changfei Zhou, Kuanming Yao, Yanting Liu, Mengge Wu, Jingyou Su, Rui Shi, Ya Huang, Jingjing Wang, Zongwen Zhang, Yiming Liu, Zhan Gao, Wooyoung Park, Huiling Jia, Xu GuoJiachen Zhang, Pakpong Chirarattananon, Lingqian Chang*, Zhaoqian Xie*, Xinge Yu*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

23 Citations (Scopus)
34 Downloads (CityUHK Scholars)

Abstract

Miniaturized mobile electronic system is an effective candidate for in situ exploration of confined spaces. However, realizing such system still faces challenges in powering issue, untethered mobility, wireless data acquisition, sensing versatility, and integration in small scales. Here, we report a battery-free, wireless, and miniaturized soft electromagnetic swimmer (SES) electronic system that achieves multiple monitoring capability in confined water environments. Through radio frequency powering, the battery-free SES system demonstrates untethered motions in confined spaces with considerable moving speed under resonance. This system adopts soft electronic technologies to integrate thin multifunctional bio/chemical sensors and wireless data acquisition module, and performs real-time water quality and virus contamination detection with demonstrated promising limits of detection and high sensitivity. All sensing data are transmitted synchronously and displayed on a smartphone graphical user interface via near-field communication. Overall, this wireless smart system demonstrates broad potential for confined space exploration, ranging from pathogen detection to pollution investigation. © 2024 the Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. no claim to original U.S. Government Works. distributed under a creative commons Attribution License 4.0 (cc BY).
Original languageEnglish
Article numbereadk6301
JournalScience Advances
Volume10
Issue number2
Online published10 Jan 2024
DOIs
Publication statusPublished - Jan 2024

Funding

This work was supported by the National Natural Science Foundation of China (NSFC) (grant nos. 61421002, 12072057, 32071407, 32101088, and 62003023), the City University of Hong Kong (grant nos. 9610423, 9667199, 9667221, 9680322, and 9678274), and Research Grants Council of the Hong Kong Special Administrative Region (grant nos. CityU 21210820, 11213721, and 11215722) and in part by InnoHK Project on Project 2.2—AI-based 3D ultrasound imaging algorithm at Hong Kong Centre for Cerebro-­Cardiovascular Health Engineering (COCHE), LiaoNing Revitalization Talents Program (grant no. XLYC2007196), Dalian Outstanding Young Talents in Science and Technology (grant no. 2021RJ06), International Cooperation Fund Project of DBJI (grant no. ICR2110), and National Key Research and Development Program of China (grant nos. 2023YFC2415900 and 2022YFB3205600)

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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