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Graphene-based flexible wearable sensors: mechanisms, challenges, and future directions

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Abstract

The increasing interest in wearable smart healthcare systems has sparked considerable attention toward flexible sensors owing to their high sensitivity and flexibility. However, these sensors still face challenges in terms of performance imbalances and instability. To address these issues, graphene-based conductive materials with exceptional mechanical and electrical properties have been incorporated into flexible sensors. Despite the potential of graphene, a comprehensive understanding of the sensing mechanisms and influence of fabrication methods on the performance of graphene-based flexible sensors is lacking. This article aims to bridge this gap by providing an overview of the latest research progress in flexible graphene sensors. We begin by analyzing the main properties of graphene materials, including tensile strength, specific surface area, thermal conductivity, and electrical conductivity. These properties highlight the superior characteristics of graphene for flexible sensor applications. The sensing mechanisms of strain/pressure, gas, and temperature flexible sensors are reviewed, with a focus on innovations in graphene composites, regular microstructures, and emerging preparation methods that enable an effective balance of the individual properties of a single flexible sensor. Furthermore, the article discusses graphene-based multifunctional flexible sensors that allow for the simultaneous monitoring of multiple stimuli, self-powered performance studies, and wireless communication performance studies. Performance analysis of these sensors in the context of flexible systems is provided. Finally, this article presents a comprehensive summary of flexible graphene sensors and offers an outlook for the future. We aim to provide theoretical guidance and technical support for the realization of individual whole-life physical sign detection using flexible graphene-based sensors.

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Abbreviations

A :

Cross-sectional area of the conductor

AgNPs :

Silver particles

AgNWs :

Silver nanowires

AuNWs :

Gold nanowires

CB :

Carbon black

CNTs :

Carbon nanotube

COVID-19 :

Corona Virus Disease 2019

CS :

Chitosan

d :

Distance between the Elastomer and conductor

e :

Quantum of electricity

GEM :

General effective media

GNPs :

Graphene nanosheets

GO :

Graphene oxide

h :

Planck's constant

IoT :

Internet of Things

J :

Tunneling current density

m :

Electron mass

MWCNTs :

Multi-walled carbon nanotubes

NR :

Natural rubber

NTC :

Negative temperature Coefficient

NWF :

Nonwoven fabric

PDMS :

Polydimethylsiloxane

PEDOT:PSS :

Poly(3,4-ethylenedioxythiophene)-polystyrene sulfonic acid

Pl :

Poly milled imide

Pl :

Polymilled imide

PTC :

Positive temperature coefficient

PU :

Polyurethane

PVDF :

Polyvinylidene fluoride

R cn :

Resistance of the graphene body

RFID :

Radio frequency identification

rGO :

Reduced graphene oxide

RGOH :

Graphene oxide hydrogel

R Tunnel :

Tunnel resistance of graphene

SARS :

Severe Acute Respiratory Syndrome

SWCNTs :

Single-walled carbon nanotube

TCR :

Temperature coefficient of resistance

TENGs :

Frictional electric nanogenerators

V :

Electric potential

λ :

Height of the energy barrier of the elastomer

σ h :

Conductivity at which the formed conductive network is saturated

σ l :

Conductivity of the composite material with the unformed conductive network

σ m :

Electrical conductivity of the conductive filler material of the composite at φ

φ :

Volume concentration of the conductive filler material

φ c :

Denotes the seepage threshold

ω :

Morphological parameter of the composite

MEMS :

Microelectromechanical system

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Funding

This study was financially supported by the Science and Technology Plan Source Innovation Project of the West Coast of Qingdao New District (Flexible wearable data acquisition system of thermoelectric conversion for human body temperature domain and preparation process of electric traction, 2020–98).

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Authors and Affiliations

  1. School of Mechanical Engineering, Qingdao University of Technology, Qingdao, 266520, China

    Ming Kong, Min Yang, Xin Cui & Changhe Li

  2. College of Physics, Qingdao University, Qingdao, 266071, China

    Min Yang, Yun-Ze Long & Jun Zhang

  3. Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, 90089-1111, USA

    Runze Li

  4. School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin, 300072, China

    Xian Huang

  5. State Key Laboratory of Ultra-Precision Machining Technology, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, China

    Yanbin Zhang

  6. College of Engineering, University of Sharjah, 27272, Sharjah, United Arab Emirates

    Zafar Said

Authors
  1. Ming Kong
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  2. Min Yang
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  3. Runze Li
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  7. Xin Cui
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  8. Yanbin Zhang
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  10. Changhe Li
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Contributions

Ming Kong: investigation, writing (original draft), and writing (review and editing);

Min Yang: writing (review and editing);

Runze Li: formal analysis, validation;

Yun-Ze Long: formal analysis, validation, and writing (review and editing);

Jun Zhang: formal analysis, validation;

Xian Huang: formal analysis, validation;

Xin Cui: modify paper, formal analysis;

Yanbin Zhang: formal analysis, validation;

Zafar Said: statistical analysis, validation;

Changhe Li: technical and material support; instructional support, and writing (review).

Corresponding authors

Correspondence to Min Yang or Changhe Li.

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Kong, M., Yang, M., Li, R. et al. Graphene-based flexible wearable sensors: mechanisms, challenges, and future directions. Int J Adv Manuf Technol 131, 3205–3237 (2024). https://doi.org/10.1007/s00170-023-12007-7

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