Machine learning coupled highly sensitive and robust polyvinylidene fluoride thin-film sensor for wearable motion recognition DOI

Qiaobang Xiang,

Haofeng Qiu,

Duo Yang

и другие.

Applied Physics Letters, Год журнала: 2025, Номер 126(20)

Опубликована: Май 19, 2025

Emerging applications in the field of health monitoring and exoskeleton robotics have led to an urgent demand for high-performance body motion recognition. However, available recognition systems face challenges due shortcomings including high cost, complex structure, low accuracy, poor reliability. This work demonstrates a flexible, sensitive, robust polyvinylidene fluoride (PVDF) composite thin-film sensor with enhanced piezoelectric polarization effect highly efficient human The presents sensitivity 27.06 KPa−1 voltage 8.7 V, together broad detection range 0.01–3 MPa attenuation 5.6% after 30 000 loading cycles, which are superior those many reported sensors commercial SDT1-028K sensor. Employing first-principles calculations, we show that doping Cu aluminum zinc oxide (AZO) facilitates transfer piezoelectrically excited charges enhances electron-transferring capacity Cu-AZO/PVDF hybrid leading stronger properties. A machine learning coupled multi-sensor network is engaged inputting signals from insoles knees, exhibiting excellent overall classification rate 95.54% six motions.

Язык: Английский

Reversible and Programmable Wettability of Laser-Induced Graphene Papers via In Situ Joule Heating-Triggered Superslippery Surfaces DOI
Yanan Wang,

Pingping Hao,

Sida Luo

и другие.

ACS Applied Materials & Interfaces, Год журнала: 2025, Номер unknown

Опубликована: Апрель 10, 2025

Reversible surface materials with programmable wettability play an increasingly vital role in a wide variety of fields from science to industry. Based on laser-induced graphene (LIG) technology, we innovatively propose paraffin-infused porous LIG paper (P-LIGP) tunable superslippery wettability. On account graphene's excellent electrical property, paraffin P-LIGP can transit rapidly solid-to-liquid state response the situ Joule heating effect. Thus, LIGP is created dynamic and reversible transition between slippery nonslippery state. In addition, combining patternable performance resistance, layer be selectively melted based Ohm's law Kirchhoff's laws, thus enabling special flow pathways for manipulating droplets various straight/oblique/arc/S-shaped sliding patterns. These applications customizable resistance promise designing intelligent flexible temperature-responsive surfaces.

Язык: Английский

Процитировано

0
Sustainable sensor technology: Laser-induced graphene based capacitive sensors on wooden substrates for touch and liquid level detection DOI

Shivam Dubey,

Abhay Singh Thakur,

V. P. Singh

и другие.

FlatChem, Год журнала: 2025, Номер unknown, С. 100874 - 100874

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0
Machine learning coupled highly sensitive and robust polyvinylidene fluoride thin-film sensor for wearable motion recognition DOI

Qiaobang Xiang,

Haofeng Qiu,

Duo Yang

и другие.

Applied Physics Letters, Год журнала: 2025, Номер 126(20)

Опубликована: Май 19, 2025

Emerging applications in the field of health monitoring and exoskeleton robotics have led to an urgent demand for high-performance body motion recognition. However, available recognition systems face challenges due shortcomings including high cost, complex structure, low accuracy, poor reliability. This work demonstrates a flexible, sensitive, robust polyvinylidene fluoride (PVDF) composite thin-film sensor with enhanced piezoelectric polarization effect highly efficient human The presents sensitivity 27.06 KPa−1 voltage 8.7 V, together broad detection range 0.01–3 MPa attenuation 5.6% after 30 000 loading cycles, which are superior those many reported sensors commercial SDT1-028K sensor. Employing first-principles calculations, we show that doping Cu aluminum zinc oxide (AZO) facilitates transfer piezoelectrically excited charges enhances electron-transferring capacity Cu-AZO/PVDF hybrid leading stronger properties. A machine learning coupled multi-sensor network is engaged inputting signals from insoles knees, exhibiting excellent overall classification rate 95.54% six motions.

Язык: Английский

Процитировано

0