scholarly journals Flexible and Highly Sensitive Strain Sensor Based on Laser-Induced Graphene Pattern Fabricated by 355 nm Pulsed Laser

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4867 ◽  
Author(s):  
Sung-Yeob Jeong ◽  
Yong-Won MA ◽  
Jun-Uk Lee ◽  
Gyeong-Ju Je ◽  
Bo-sung Shin
Keyword(s):  
Focal Length ◽  
Pulsed Laser ◽  
Strain Sensor ◽  
High Sensitivity ◽  
Gauge Factor ◽  
Functional Evaluation ◽  
Mechanical Fracture ◽  
Highly Sensitive ◽  
Human Finger ◽  
Small Deformations

A laser-induced-graphene (LIG) pattern fabricated using a 355 nm pulsed laser was applied to a strain sensor. Structural analysis and functional evaluation of the LIG strain sensor were performed by Raman spectroscopy, scanning electron microscopy (SEM) imaging, and electrical–mechanical coupled testing. The electrical characteristics of the sensor with respect to laser fluence and focal length were evaluated. The sensor responded sensitively to small deformations, had a high gauge factor of ~160, and underwent mechanical fracture at 30% tensile strain. In addition, we have applied the LIG sensor, which has high sensitivity, a simple manufacturing process, and good durability, to human finger motion monitoring.

Ultra-stretchable and highly sensitive strain sensor based on gradient structure carbon nanotubes

Nanoscale ◽  
2018 ◽  
Vol 10 (28) ◽  
pp. 13599-13606 ◽  
Author(s):  
Binghao Liang ◽  
Zhiqiang Lin ◽  
Wenjun Chen ◽  
Zhongfu He ◽  
Jing Zhong ◽  
...  
Keyword(s):  
Carbon Nanotubes ◽  
Carbon Nanotube ◽  
Strain Sensor ◽  
High Sensitivity ◽  
Strain Sensors ◽  
Sensitive Strain ◽  
Gauge Factor ◽  
Gradient Structure ◽  
Highly Sensitive ◽  
Highly Stretchable

A highly stretchable and sensitive strain sensor based on a gradient carbon nanotube was developed. The strain sensors show an unprecedented combination of both high sensitivity (gauge factor = 13.5) and ultra-stretchability (>550%).

scholarly journals A Study of Highly Sensitive Wearable Strain Sensor Based on Graphical Sensitive Units

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Jie Wang ◽  
Yi Du ◽  
Qiang Zhang ◽  
Zhu Jing ◽  
Kai Zhuo ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Real Time ◽  
Silver Nanowires ◽  
Strain Sensor ◽  
High Sensitivity ◽  
Sine Wave ◽  
Gauge Factor ◽  
Soft Substrate ◽  
Highly Sensitive ◽  
Sensitivity Improvement

The sensitivity improvement is the choke point of the soft strain sensor’s development. This paper focuses on heightening the soft strain sensor’s sensitivity through changing the sensitive unit’s shape. The sensitive units in shape of square or sine wave with different periods were studied in this work. Silver nanowires (Ag NWs) in excellent electrical conductivity and flexible polydimethylsiloxane (PDMS) were used as sensitive nanomaterials and soft substrate. The soft strain sensor whose sensitive unit is double cycled square wave performs the highest sensitivity whose gauge factor (GF) reaches to 14763.8. Based on the high sensitivity, the sensor was applied on real-time detection of the human expression.

scholarly journals Development of Highly Sensitive Strain Sensor Using Area-Arrayed Graphene Nanoribbons

Nanomaterials ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1701
Author(s):  
Ken Suzuki ◽  
Ryohei Nakagawa ◽  
Qinqiang Zhang ◽  
Hideo Miura
Keyword(s):  
Graphene Nanoribbons ◽  
Strain Sensor ◽  
Strain Sensors ◽  
Sensitive Strain ◽  
Bending Test ◽  
Gauge Factor ◽  
Four Point Bending ◽  
Current Voltage ◽  
Highly Sensitive ◽  
Current Voltage Relationship

In this study, a basic design of area-arrayed graphene nanoribbon (GNR) strain sensors was proposed to realize the next generation of strain sensors. To fabricate the area-arrayed GNRs, a top-down approach was employed, in which GNRs were cut out from a large graphene sheet using an electron beam lithography technique. GNRs with widths of 400 nm, 300 nm, 200 nm, and 50 nm were fabricated, and their current-voltage characteristics were evaluated. The current values of GNRs with widths of 200 nm and above increased linearly with increasing applied voltage, indicating that these GNRs were metallic conductors and a good ohmic junction was formed between graphene and the electrode. There were two types of GNRs with a width of 50 nm, one with a linear current–voltage relationship and the other with a nonlinear one. We evaluated the strain sensitivity of the 50 nm GNR exhibiting metallic conduction by applying a four-point bending test, and found that the gauge factor of this GNR was about 50. Thus, GNRs with a width of about 50 nm can be used to realize a highly sensitive strain sensor.

scholarly journals Giant gauge factor of Van der Waals material based strain sensors

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Wenjie Yan ◽  
Huei-Ru Fuh ◽  
Yanhui Lv ◽  
Ke-Qiu Chen ◽  
Tsung-Yin Tsai ◽  
...  
Keyword(s):  
Carrier Mobility ◽  
Large Range ◽  
Van Der Waals ◽  
High Sensitivity ◽  
Strain Sensors ◽  
Strain Gauges ◽  
Gauge Factor ◽  
Proof Of Concept ◽  
High Flexibility ◽  
Small Deformations

AbstractThere is an emergent demand for high-flexibility, high-sensitivity and low-power strain gauges capable of sensing small deformations and vibrations in extreme conditions. Enhancing the gauge factor remains one of the greatest challenges for strain sensors. This is typically limited to below 300 and set when the sensor is fabricated. We report a strategy to tune and enhance the gauge factor of strain sensors based on Van der Waals materials by tuning the carrier mobility and concentration through an interplay of piezoelectric and photoelectric effects. For a SnS2 sensor we report a gauge factor up to 3933, and the ability to tune it over a large range, from 23 to 3933. Results from SnS2, GaSe, GeSe, monolayer WSe2, and monolayer MoSe2 sensors suggest that this is a universal phenomenon for Van der Waals semiconductors. We also provide proof of concept demonstrations by detecting vibrations caused by sound and capturing body movements.

scholarly journals Understanding the Impact of Machine Learning Models on the Performance of Different Flexible Strain Sensor Modalities

2021 ◽  
Vol 8 ◽  
Author(s):  
Brett C. Hannigan ◽  
Tyler J. Cuthbert ◽  
Wanhaoyi Geng ◽  
Mohammad Tavassolian ◽  
Carlo Menon
Keyword(s):  
Machine Learning ◽  
Mean Squared Error ◽  
Strain Sensor ◽  
High Sensitivity ◽  
Signal Amplitude ◽  
Electrical Signal ◽  
Gauge Factor ◽  
Piezoresistive Sensor ◽  
Fibre Strain ◽  
The Impact

Fibre strain sensors commonly use three major modalities to transduce strain—piezoresistance, capacitance, and inductance. The electrical signal in response to strain differs between these sensing technologies, having varying sensitivity, maximum measurable loading rate, and susceptibility to deleterious effects like hysteresis and drift. The wide variety of sensor materials and strain tracking applications makes it difficult to choose the best sensor modality for a wearable device when considering signal quality, cost, and difficulty of manufacture. Fibre strain sensor samples employing the three sensing mechanisms are fabricated and subjected to strain using a tensile tester. Their mechanical and electrical properties are measured in response to strain profiles designed to exhibit particular shortcomings of sensor behaviour. Using these data, the sensors are compared to identify materials and sensing technologies well suited for different textile motion tracking applications. Several regression models are trained and validated on random strain pattern data, providing guidance for pairing each sensor with a model architecture that compensates for non-ideal effects. A thermoplastic elastomer-core piezoresistive sensor had the highest sensitivity (average gauge factor: 12.6) and a piezoresistive sensor of similar construction with a polyether urethane-urea core had the largest bandwidth, capable of resolving strain rates above 300% s−1 with 36% signal amplitude attenuation. However, both piezoresistve sensors suffered from larger hysteresis and drift than a coaxial polymer sensor using the capacitive strain sensing mechanism. Machine learning improved the piezoresistive sensors’ root-mean-squared error when tracking a random strain signal by up to 58% while maintaining their high sensitivity, bandwidth, and ease of interfacing electronically.

scholarly journals Robust and conductive hydrogel based on mussel adhesive chemistry for remote monitoring of body signals

Friction ◽  
2020 ◽  
Author(s):  
Weijun Li ◽  
Hao Liu ◽  
Yuanyuan Mi ◽  
Miaoran Zhang ◽  
Jinmiao Shi ◽  
...  
Keyword(s):  
Antibacterial Properties ◽  
Strain Sensor ◽  
High Sensitivity ◽  
Smart Device ◽  
Gauge Factor ◽  
Self Healing ◽  
3D Network ◽  
Mussel Adhesive ◽  
Physical And Chemical

AbstractThere is a high demand for hydrogels with multifunctional performance (a combination of adhesive, mechanical, and electrical properties) in biological, tissue engineering, robotics, and smart device applications. However, a majority of existing hydrogels are relatively rigid and brittle, with limited stretchability; this hinders their application in the emerging field of flexible devices. In this study, cheap and abundant potato residues were used with polyacrylamide (PAM) to fabricate a multifunctional hydrogel, and chitosan was used for the design of a three-dimentional (3D) network-structured hydrogel. The as-prepared hydrogels exhibited excellent stretchability, with an extension exceeding 900% and a recovery degree of over 99%. Due to the combination of physical and chemical cross-linking properties and the introduction of dopamine, the designed hydrogel exhibits a remarkable self-healing ability (80% mechanical recovery in 2 h), high tensile strength (0.75 MPa), and ultra-stretchability (900%). The resultant products offer superior properties compared to those of previously reported tough and self-healing hydrogels for wound adhesion. Chitosan and potato residues were used as scaffold materials for the hydrogels with excellent mechanical properties. In addition, in vitro experiments show that these hydrogels feature excellent antibacterial properties, effectively hindering the reproduction of bacteria. Moreover, the ternary hydrogel can act as a strain sensor with high sensitivity and a gauge factor of 1.6. The proposed strategy is expected to serve as a reference for the development of green and recyclable conductive polymers to fabricate hydrogels. The proposed hydrogel can also act as a suitable strain sensor for bio-friendly devices such as smart wearable electronic devices and/or for health monitoring.

scholarly journals Enhanced Stretchable and Sensitive Strain Sensor via Controlled Strain Distribution

Nanomaterials ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 218 ◽  
Author(s):  
Huamin Chen ◽  
Longfeng Lv ◽  
Jiushuang Zhang ◽  
Shaochun Zhang ◽  
Pengjun Xu ◽  
...  
Keyword(s):  
Strain Distribution ◽  
Tensile Strain ◽  
Strain Sensor ◽  
Gauge Factor ◽  
Simple Method ◽  
Practical Applications ◽  
Simple Strategy ◽  
Highly Sensitive ◽  
Highly Stretchable ◽  
Maximum Tensile Strain

Stretchable and wearable opto-electronics have attracted worldwide attention due to their broad prospects in health monitoring and epidermal applications. Resistive strain sensors, as one of the most typical and important device, have been the subject of great improvements in sensitivity and stretchability. Nevertheless, it is hard to take both sensitivity and stretchability into consideration for practical applications. Herein, we demonstrated a simple strategy to construct a highly sensitive and stretchable graphene-based strain sensor. According to the strain distribution in the simulation result, highly sensitive planar graphene and highly stretchable crumpled graphene (CG) were rationally connected to effectively modulate the sensitivity and stretchability of the device. For the stretching mode, the device showed a gauge factor (GF) of 20.1 with 105% tensile strain. The sensitivity of the device was relatively high in this large working range, and the device could endure a maximum tensile strain of 135% with a GF of 337.8. In addition, in the bending mode, the device could work in outward and inward modes. This work introduced a novel and simple method with which to effectively monitor sensitivity and stretchability at the same time. More importantly, the method could be applied to other material categories to further improve the performance.

scholarly journals Inkjet printed self-healable strain sensor based on graphene and magnetic iron oxide nano-composite on engineered polyurethane substrate

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Gul Hassan ◽  
Muhammad Umair Khan ◽  
Jinho Bae ◽  
Ahmed Shuja
Keyword(s):  
Iron Oxide ◽  
Strain Sensor ◽  
Gauge Factor ◽  
Self Healing ◽  
Nano Composite ◽  
Mechanical Fracture ◽  
Magnetic Iron Oxide ◽  
Stretching Factor ◽  
Highly Stretchable ◽  
Healing Property

Abstract In recent years, self-healing property has getting tremendous attention in the future wearable electronic. This paper proposes a novel cut-able and highly stretchable strain sensor utilizing a self-healing function from magnetic force of magnetic iron oxide and graphene nano-composite on an engineered self-healable polyurethane substrate through commercialized inkjet printer DMP-3000. Inducing the magnetic property, magnetic iron oxide is applied to connect between graphene flacks in the nano-composite. To find the best nano-composite, the optimum graphene and magnetic iron oxide blending ratio is 1:1. The proposed sensor shows a high mechanical fracture recovery, sensitivity towards strain, and excellent self-healing property. The proposed devices maintain their performance over 10,000 times bending/relaxing cycles, and 94% of their function are recovered even after cutting them. The device also demonstrates stretchability up to 54.5% and a stretching factor is decreased down to 32.5% after cutting them. The gauge factor of the device is 271.4 at 35%, which means its sensitivity is good. Hence, these results may open a new opportunity towards the design and fabrication of future self-healing wearable strain sensors and their applied electronic devices.

scholarly journals A Pressure-Insensitive Self-Attachable Flexible Strain Sensor with Bioinspired Adhesive and Active CNT Layers

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6965
Author(s):  
Minho Seong ◽  
Insol Hwang ◽  
Joosung Lee ◽  
Hoon Eui Jeong
Keyword(s):  
Tensile Strain ◽  
High Strain ◽  
Strain Sensor ◽  
Adhesive Layer ◽  
High Sensitivity ◽  
Gauge Factor ◽  
Tactile Sensors ◽  
Surface Attachment ◽  
Tactile Stimuli ◽  
Flexible Strain Sensor

Flexible tactile sensors are required to maintain conformal contact with target objects and to differentiate different tactile stimuli such as strain and pressure to achieve high sensing performance. However, many existing tactile sensors do not have the ability to distinguish strain from pressure. Moreover, because they lack intrinsic adhesion capability, they require additional adhesive tapes for surface attachment. Herein, we present a self-attachable, pressure-insensitive strain sensor that can firmly adhere to target objects and selectively perceive tensile strain with high sensitivity. The proposed strain sensor is mainly composed of a bioinspired micropillar adhesive layer and a selectively coated active carbon nanotube (CNT) layer. We show that the bioinspired adhesive layer enables strong self-attachment of the sensor to diverse planar and nonplanar surfaces with a maximum adhesion strength of 257 kPa, while the thin film configuration of the patterned CNT layer enables high strain sensitivity (gauge factor (GF) of 2.26) and pressure insensitivity.

Nano-toughening of transparent wearable sensors with high sensitivity and a wide linear sensing range

2020 ◽  
Vol 8 (39) ◽  
pp. 20531-20542
Author(s):  
Shuhua Peng ◽  
Shuying Wu ◽  
Yuyan Yu ◽  
Philippe Blanloeuil ◽  
Chun H. Wang
Keyword(s):  
Wearable Sensors ◽  
Strain Sensor ◽  
High Sensitivity ◽  
Optical Transparency ◽  
Conductive Films ◽  
Sensing Range ◽  
Highly Sensitive

A new highly sensitive and stretchable strain sensor with excellent linearity and optical transparency has been developed by toughening of microcracks within the thin conductive films.

Sign in / Sign up

Export Citation Format

Share Document