Biomimetic microstructure design for ultrasensitive piezoionic mechanoreceptors in multimodal object recognition
Mingqi Ding,
Pengshan Xie,
Jingwen Wang,
Wu Guo,
Haifan Li,
Siliang Hu,
Dengji Li,
Bowen Li,
Nan Wang,
Chun-Yuen Wong,
Jia Sun () and
Johnny C. Ho ()
Additional contact information
Mingqi Ding: City University of Hong Kong
Pengshan Xie: City University of Hong Kong
Jingwen Wang: Central South University
Wu Guo: Polymer Research Institute of Sichuan University
Haifan Li: City University of Hong Kong
Siliang Hu: City University of Hong Kong
Dengji Li: City University of Hong Kong
Bowen Li: City University of Hong Kong
Nan Wang: City University of Hong Kong
Chun-Yuen Wong: City University of Hong Kong
Jia Sun: Central South University
Johnny C. Ho: City University of Hong Kong
Nature Communications, 2025, vol. 16, issue 1, 1-11
Abstract:
Abstract The challenge of achieving high recognition accuracy in artificial mechanoreceptors arises from the trade-off between sensitivity and stability in the sensing unit. Inspired by human skin, we developed a biomimetic approach that involves structural and engineering enhancements for ionic-conducting polyvinyl alcohol/Ti3C2Tx (PVA/MXene) composite hydrogel microneedles (HM) to enhance the sensitivity. By integrating the HM with a polyethylene terephthalate/indium tin oxide (PET/ITO) film, we create a non-faradaic junction that ensures stable electrical output without transmission loss under stimulation. Furthermore, the significant alteration in nanosheet spacing facilitates proton transport along the MXene microchannels, increasing the plasmonic gradient between the junction and the hydrogel’s center, thereby boosting piezoionic efficiency. Consequently, the biomimetic sensing unit achieves a high power density of 165.6 mW m-2 and exceptional sensing stability over 10,000 cycles. When combined with vertical memristor units, this system effectively captures and transforms characteristic signals from various objects, achieving a recognition accuracy of 90%.
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.nature.com/articles/s41467-025-63115-9 Abstract (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-63115-9
Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/
DOI: 10.1038/s41467-025-63115-9
Access Statistics for this article
Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie
More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().