Thin and soft Ti3C2Tx MXene sponge structure for highly sensitive pressure sensor assisted by deep learning

Wang Guo, Zhiqiang Ma*, Zhou Chen, Haojun Hua, Dong Wang, Mohamed Elhousseini Hilal*, Yatian Fu, Pengyi Lu, Jian Lu, Yuanting Zhang, Derek Ho*, Bee Luan Khoo*

*Corresponding author for this work

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

34 Citations (Scopus)

Abstract

Increasing demand for flexible sensors in healthcare has spurred the development of nanomaterial-polymer composite sensors. However, existing pressure sensors suffer from low sensitivity due to poor interactions between the functional filler and the polymer matrix. For example, the direct chemical bonding of nanomaterials to the surface of chemically inert polymers such as polydimethylsiloxane (PDMS) is not easily achieved. Herein, we demonstrate that MXene can significantly promote the sensitivity of a thin and soft piezoresistive sensor based on a surface functionalized PDMS (FPDMS) sponge. Using plasma treatment, we constructed a MXene-FPDMS (MFP) sponge with high mechanical strength via the interlayer hydrogen bonding effect. The formed MFP sponge structure (~450 μm in thickness) endows the pressure sensor with a high sensitivity of 14.2 kPa− 1 and a low modulus of 9.7 kPa, critical for detecting ultra-low pressures. When operated with deep learning algorithms, the MFP sponge sensor successfully classifies the pronunciation of 26 letters and various polite expressions with an average accuracy of 94 ± 0.6 %. We envision that this work paves the way for the development of intelligent wearable platforms. © 2024 Elsevier B.V. All rights reserved.
Original languageEnglish
Article number149659
JournalChemical Engineering Journal
Volume485
Online published15 Feb 2024
DOIs
Publication statusPublished - 1 Apr 2024

Funding

This work was supported in part by the InnoHK Project on [Project 1-2 - Design of Drug Delivery Systems (DDS) structure and selection of potential drugs for acute CVDs] and [Project 1-5 Multi-modal spectroscopy (MMS) & biosensor platforms for monitoring CVDs] at Hong Kong Centre for Cerebro-cardiovascular Health Engineering (COCHE) - Hong Kong SAR, in part by City University of Hong Kong (9610430, 7020002, 7005464, 7005208, 9667220) - Hong Kong SAR, which is funded by the Research Grants Council (RGC), in part by Pneumoconiosis Compensation Fund Board (9211276) - Hong Kong SAR, and in part by Research Grants Council (RGC 9048206) - Hong Kong SAR, Environment and Conservation Fund (ECF 51/2021) and Innovation and Technology Fund (PRP/001/22FX).

Research Keywords

  • Ti3C2Tx MXene
  • Thin and soft sponge structure
  • High-sensitivity piezoresistive sensor
  • Hydrogen bonding
  • Deep learning

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