TY - JOUR
T1 - 2H-MoS2 lubrication-enhanced MWCNT nanocomposite for subtle bio-motion piezoresistive detection with deep learning integration
AU - Yao, Ke Yu
AU - Lai, Derek Ka Hei
AU - Lim, Hyo Jung
AU - So, Bryan Pak Hei
AU - Chan, Andy Chi Ho
AU - Yip, Patrick Yiu Man
AU - Wong, Duo Wai Chi
AU - Dai, Bingyang
AU - Zhao, Xin
AU - Wong, Siu Hong Dexter
AU - Cheung, James Chung Wai
N1 - Publisher Copyright:
© 2025 The Author(s)
PY - 2025/5
Y1 - 2025/5
N2 - Intelligent piezoresistive health monitoring systems integrate advanced nanocomposite architectures with precise algorithmic analysis for real-time physiological assessment. However, existing works often prioritize high sensitivity at the expense of strain tolerance and require complex fabrication procedures. Herein, we present an environmentally friendly, low-cost, and nonionic fabrication approach for a 2H-phase molybdenum disulfide (2H-MoS2)-enhanced multi-walled carbon nanotube (MWCNT) strain sensor, developed via a systematically optimized vacuum-assisted filtration process. This study is the first to validate the dual enhancement effect of MoS2, leveraging its shear-exfoliation properties to simultaneously improve strain gauge performance and mechanical robustness. The resulting nacre-like layered hybrid nanocomposite achieves a remarkable gauge factor of 675.7 (R2∼0.993) at low strain (∼0–4.5 %), representing a 3881.5 % improvement over pure MWCNT systems, alongside enhanced toughness (∼89.17 %) and strain tolerance (∼53.93 %). Meanwhile, the optimized composition ensures low rest-state resistance (∼13.1 Ω), minimal hysteresis (∼5.7 %), and robust durability over 5000 cycles at 10 % strain. As a result, the proposed sensor enables highly consistent, high-fidelity monitoring of various subtle-to-moderate biomotions. Integrated with a fine-tuned InceptionTime deep learning model, it achieves an F1-score of 98 % in classifying Dysphagia Diet Standardization Initiative (IDDSI)-standard swallowing activities, demonstrating its potential for AI-driven health monitoring applications.
AB - Intelligent piezoresistive health monitoring systems integrate advanced nanocomposite architectures with precise algorithmic analysis for real-time physiological assessment. However, existing works often prioritize high sensitivity at the expense of strain tolerance and require complex fabrication procedures. Herein, we present an environmentally friendly, low-cost, and nonionic fabrication approach for a 2H-phase molybdenum disulfide (2H-MoS2)-enhanced multi-walled carbon nanotube (MWCNT) strain sensor, developed via a systematically optimized vacuum-assisted filtration process. This study is the first to validate the dual enhancement effect of MoS2, leveraging its shear-exfoliation properties to simultaneously improve strain gauge performance and mechanical robustness. The resulting nacre-like layered hybrid nanocomposite achieves a remarkable gauge factor of 675.7 (R2∼0.993) at low strain (∼0–4.5 %), representing a 3881.5 % improvement over pure MWCNT systems, alongside enhanced toughness (∼89.17 %) and strain tolerance (∼53.93 %). Meanwhile, the optimized composition ensures low rest-state resistance (∼13.1 Ω), minimal hysteresis (∼5.7 %), and robust durability over 5000 cycles at 10 % strain. As a result, the proposed sensor enables highly consistent, high-fidelity monitoring of various subtle-to-moderate biomotions. Integrated with a fine-tuned InceptionTime deep learning model, it achieves an F1-score of 98 % in classifying Dysphagia Diet Standardization Initiative (IDDSI)-standard swallowing activities, demonstrating its potential for AI-driven health monitoring applications.
KW - Deep learning
KW - Flexible piezoresistive sensor
KW - Lubrication toughening
KW - MWCNT/MoS nanocomposite
KW - Subtle-to-moderate biophysical signal
UR - http://www.scopus.com/inward/record.url?scp=105001340477&partnerID=8YFLogxK
U2 - 10.1016/j.matdes.2025.113861
DO - 10.1016/j.matdes.2025.113861
M3 - Journal article
AN - SCOPUS:105001340477
SN - 0264-1275
VL - 253
JO - Materials and Design
JF - Materials and Design
M1 - 113861
ER -