2H-MoS2润滑增强MWCNT纳米复合材料用于精细生物运动压阻检测与深度学习集成

IF 7.6 2区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
Ke-Yu Yao , Derek Ka-Hei Lai , Hyo-Jung Lim , Bryan Pak-Hei So , Andy Chi-Ho Chan , Patrick Yiu-Man Yip , Duo Wai-Chi Wong , Bingyang Dai , Xin Zhao , Siu Hong Dexter Wong , James Chung-Wai Cheung
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引用次数: 0

摘要

智能压阻式健康监测系统集成了先进的纳米复合材料结构和精确的算法分析,用于实时生理评估。然而,现有的工程往往以牺牲应变容限为代价优先考虑高灵敏度,并且需要复杂的制造过程。在此,我们提出了一种环保、低成本、非离子的2h相二硫化钼(2H-MoS2)增强多壁碳纳米管(MWCNT)应变传感器的制造方法,该传感器是通过系统优化的真空辅助过滤工艺开发的。该研究首次验证了MoS2的双重增强效应,利用其剪切-剥落特性同时提高应变片性能和机械鲁棒性。在低应变(~ 0 - 4.5%)下,纳米复合材料获得了675.7 (R2 ~ 0.993)的显著规范因子,比纯MWCNT系统提高了3881.5%,同时增强了韧性(~ 89.17%)和应变容限(~ 53.93%)。同时,优化后的成分确保了低静息状态电阻(~ 13.1 Ω)、最小迟滞(~ 5.7%)以及在10%应变下超过5000次循环的耐用性。因此,所提出的传感器能够高度一致,高保真地监测各种细微到中度的生物运动。与经过微调的InceptionTime深度学习模型相结合,它在对吞咽困难饮食标准化倡议(IDDSI)标准吞咽活动进行分类方面达到了98%的f1分,显示了其在人工智能驱动的健康监测应用中的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

2H-MoS2 lubrication-enhanced MWCNT nanocomposite for subtle bio-motion piezoresistive detection with deep learning integration

2H-MoS2 lubrication-enhanced MWCNT nanocomposite for subtle bio-motion piezoresistive detection with deep learning integration
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.
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来源期刊
Materials & Design
Materials & Design Engineering-Mechanical Engineering
CiteScore
14.30
自引率
7.10%
发文量
1028
审稿时长
85 days
期刊介绍: Materials and Design is a multi-disciplinary journal that publishes original research reports, review articles, and express communications. The journal focuses on studying the structure and properties of inorganic and organic materials, advancements in synthesis, processing, characterization, and testing, the design of materials and engineering systems, and their applications in technology. It aims to bring together various aspects of materials science, engineering, physics, and chemistry. The journal explores themes ranging from materials to design and aims to reveal the connections between natural and artificial materials, as well as experiment and modeling. Manuscripts submitted to Materials and Design should contain elements of discovery and surprise, as they often contribute new insights into the architecture and function of matter.
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