A graphene-based resistive pressure sensor with record-high sensitivity in a wide pressure range.

This paper presents the design and simulation of MEMS based piezoresistive pressure sensor for microfluidic applications. Geometrical parameters are very much considerable when designing microstructure of the pressure sensor. Hence, an analysis is carried out by changing the dimensional parameters of three different diaphragm geometries namely square shaped diaphragm, circular shaped diaphragm and cross sectional beam shaped diaphragm respectively. This is performed in three dimensional mesh plots using Matlab. The Finite Element Method (FEM) analyses are performed in COMSOL and by comparing the results, the square type diaphragm is chosen as best diaphragm geometry for the microfluidic applications. In addition, modal analysis is carried out by using Ansys to identify the natural frequency of the best diaphragm geometry. Also Piezoresistive sensing elements are designed and simulated by performing coupled field analysis using COMSOL Multiphysics. Simulation results reveal that piezo resistive square type pressure sensors have high sensitivity in a wide range of pressures.

Flexible piezo-resistive pressure sensor based on conducting PANI on paper substrate

Flexible piezoresistive sensors have huge potential for health monitoring, human-machine interfaces, prosthetic limbs, and intelligent robotics. A variety of nanomaterials and structural schemes have been proposed for realizing ultrasensitive flexible piezoresistive sensors. However, despite the success of recent efforts, high sensitivity within narrower pressure ranges and/or the challenging adhesion and stability issues still potentially limit their broad applications. Herein, we introduce a biomaterial-based scheme for the development of flexible pressure sensors that are ultrasensitive (resistance change by 5 orders) over a broad pressure range of 0.1-100 kPa, promptly responsive (20 ms), and yet highly stable. We show that employing biomaterial-incorporated conductive networks of single-walled carbon nanotubes as interfacial layers of contact-based resistive pressure sensors significantly enhances piezoresistive response via effective modulation of the interlayer resistance and provides stable interfaces for the pressure sensors. The developed flexible sensor is capable of real-time monitoring of wrist pulse waves under external medium pressure levels and providing pressure profiles applied by a thumb and a forefinger during object manipulation at a low voltage (1 V) and power consumption (<12 μW). This work provides a new insight into the material candidates and approaches for the development of wearable health-monitoring and human-machine interfaces.

With the rapid development of wearable devices, flexible pressure sensors with high sensitivity and wide workable range are highly desired. In nature, there are many well-adapted structures developed through natural selection, which inspired us for the design of biomimetic materials or devices. Particularly, human fingertip skin, where many epidermal ridges amplify external stimulations, might be a good example to imitate for highly sensitive sensors. In this work, based on unique chemical vapor depositions (CVD)-grown 3D graphene films that mimic the morphology of fingertip skin, we fabricated flexible pressure sensing membranes, which simultaneously showed a high sensitivity of 110 (kPa)−1 for 0–0.2 kPa and wide workable pressure range (up to 75 kPa). Hierarchical structured PDMS films molded from natural leaves were used as the supporting elastic films for the graphene films, which also contribute to the superior performance of the pressure sensors. The pressure sensor showed a low detection limit (0.2 Pa), fast response (< 30 ms), and excellent stability for more than 10,000 loading/unloading cycles. Based on these features, we demonstrated its applications in detecting tiny objects, sound, and human physiological signals, showing its potential in wearable electronics for health monitoring and human/machine interfaces.

In this research, an ultrathin, biocompatible, and flexible pressure sensor with a wide pressure range has been developed and applied in biomedical applications. The pressure sensing mechanism is based on the variation of contact resistance between an electrode and a three-dimensional microstructured polyimide/carbon nanotube composite film. The sensor has a thickness of about 31.3 μm, a maximum sensitivity of 41.0 MPa-1, and a sensing range of 10-500 kPa. Moreover, in situ temperature measurement by an integrated resistive temperature detector enables data correction for varying temperature conditions. In order to show the advantages of the fabricated sensor, it is attached to the human body and integrated with the surface of a radiofrequency ablation (RFA) needle with small radius of curvature. In the experiments, the proposed pressure sensor measured subtle pressure levels (pulse pressure) and high pressure levels (fingertip pressure) without losing conformal contact with the skin. In addition, when the pressure-sensor-integrated RFA needle was inserted into a bovine liver, successful detection of steam popping phenomenon was observed.

Stretchable electronic devices and sensors built on thin elastomer substrates may find a wide range of applications in wearable health monitoring devices owing to their ability to conformably adapt to human skin for long-term and comfortable wearing. In this talk, I will present our work on developing intrinsically-stretchable electronic materials that are formulated as electronic inks and patterend using a highly scalable and low-cost inkjet printing process. A variety of soft sensors including silver nanoparticle based ultrasensitive resistive strain sensor and pressure sensor, porous elastomer dielectric based capacitive pressure sensor, and multimodal sensor that can differentiate pressure, strain, and temperature stimuli have all been demonstrated on ultrathin polydimethylsiloxane (PDMS) substrate by printing. These devices have been used in applications including motion and gesture tracking, voice recognition, arterial pulse waveform and photoplethysmogram monitoring. In addition, I will also report our work on the development of a unique porous PDMS sponge electrode as a gel-free dry interface for motion-artifact tolerant recording of electrophysiological signals. The porous structure of the soft electrode significantly increases the effective contact area and lowers the electrode-skin impedance, which result in improved signal-to-noise ratio. Compared to commercial rigid electrodes, the soft and thin form factor also makes the spongy electrode well-suited for long-term recording of high quality biopotential signals including electrocardiogram (ECG) and electromyography (EMG) on ambulatory patients. As a demonstration of its clinical usage with a focus on maternal and fetal health monitoring, I will show an array of such soft electrodes integrated on a printed patch of textile-based interconnections, and used for recording and spatiotemporal mapping of the uterine contraction patterns from patients in active labor.

Flexible and wearable pressure sensors have attracted a tremendous amount of attention due to their wider applications in human interfaces and healthcare monitoring. However, achieving accurate pressure detection and stability against external stimuli (in particular, bending deformation) over a wide range of pressures from tactile to body weight levels is a great challenge. Here, we introduce an ultrawide-range, bending-insensitive, and flexible pressure sensor based on a carbon nanotube (CNT) network-coated thin porous elastomer sponge for use in human interface devices. The integration of the CNT networks into three-dimensional microporous elastomers provides high deformability and a large change in contact between the conductive CNT networks due to the presence of micropores, thereby improving the sensitivity compared with that obtained using CNT-embedded solid elastomers. As electrical pathways are continuously generated up to high compressive strain (∼80%), the pressure sensor shows an ultrawide pressure sensing range (10 Pa to 1.2 MPa) while maintaining favorable sensitivity (0.01-0.02 kPa-1) and linearity ( R2 ∼ 0.98). Also, the pressure sensor exhibits excellent electromechanical stability and insensitivity to bending-induced deformations. Finally, we demonstrate that the pressure sensor can be applied in a flexible piano pad as an entertainment human interface device and a flexible foot insole as a wearable healthcare and gait monitoring device.

The development of flexible pressure sensors for monitoring human motion and physiological signals has attracted extensive scientific research. However, achieving low monitoring limits, a wide detection range, large bending stresses, and excellent mechanical stability simultaneously remains a serious challenge. With the aim of developing a high-performance capacitive pressure sensor (CPS), this paper introduces the successful preparation of a single-walled carbon nanotube (SWNT)/polydimethylsiloxane (S-PDMS) composite dielectric with a foam-like structure (high permittivity and low elasticity modulus) and MXene/SWNT (S-MXene) composite film electrodes with a micro-crumpled structure. The above structurally modified CPS (SMCPS) demonstrated an excellent response output during pressure loading, achieving a wide pressure detection range (up to 700 kPa), a low detection limit (16.55 Pa), fast response/recovery characteristics (48/60 ms), enhanced sensitivity across a wide pressure range, long-term stability under repeated heavy loading and unloading (40 kPa, >2000 cycles), and reliable performance under various temperature and humidity conditions. The SMCPS demonstrated a precise and stable capacitive response in monitoring subtle physiological signals and detecting motion, owing to its unique electrode structure. The flexible device was integrated with an Internet of Things module to create a smart glove system that enables real-time tracking of dynamic gestures. This system demonstrates exceptional performance in gesture recognition and prediction with artificial intelligence analysis, highlighting the potential of the SMCPS in human-machine interface applications.

The graphene-based strain sensors have attracted much attention recently. Usually, there is a tradeoff between the sensitivity and resistance of such devices for larger resistance devices cost higher energy consumption. As the Aorta pressure sensor, smaller device is needed for less invasive to the human body. In this paper, we report an ultra-sensitive graphene-based pressure sensor whose sensitivity can be tuned by the original resistance in different growth condition. For a typical pressure sensor device, the gauge factor can be achieved <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\sim 10^{3}$</tex> while the sheet resistance <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\sim 100 \mathrm{K} \Omega/\square$</tex>. The flexible pressure sensor placed in vivo or in vitro can sense both various blood pressure and heart rate. Cardiac arrhythmias such as atrial fibrillation and ventricular premature contraction can be detected in real-time. After more than 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> cycles test, the performance of the device remains basically unchanged with fast response time less than 50 ms. The highly sensitive, small volume graphene-based Aorta pressure sensor suggests a great potential in future healthcare industry.

Soft pressure sensors may find a wide range of applications in soft robotics, biomedical devices, and smart wearables. Here, an inkjet‐printed resistive pressure sensor that offers high sensitivity and can be fabricated using a very simple process is reported. The device is composed of a conductive silver nanoparticle (AgNP) layer directly printed onto a polydimethylsiloxane substrate and encapsulated by a VHB tape. The pressure is measured through change in electrical resistance caused by pressure‐induced strain in the printed AgNP thin film. The influence of substrate stiffness and thickness on the sensitivity and achieved sensors with an optimized configuration that exhibit highly repeatable response with a sensitivity of up to 0.48 kPa−1 is systematically studied. It is further demonstrated that such a printed soft sensor patch is capable of measuring arterial pulse waveforms or detecting acoustic vibrations under various sound pressure levels. With its simple and low‐cost fabrication process and high sensitivity, the inkjet‐printed resistive pressure sensor is promising for future biomedical and smart wearable device applications.

The sensitivity and linearity are two extremely important performance parameters for pressure sensors. Superior sensitivity and outstanding linearity enable them to adapt to different application scenarios and accurately acquire pressure change. However, it is challenging for current piezoresistive pressure sensors to balance both of these performance aspects. This study proposes a fabric-based resistive pressure sensor with multiscale structures. The constructed resistive pressure sensor exhibits exceptional linearity exceeding 99% within a detection range of 0–1 MPa. Compared to the reported piezoresistive pressure sensors with ultrawide ranges, this sensor demonstrates higher sensitivity and a broader linear response range. In addition, this device exhibits excellent temperature tolerance. Our work will extend the application limits of sensors in fields, such as health monitoring and diagnostics, wearable devices, and human-machine interaction.

Flexible capacitive pressure sensors with a simple structure and low power consumption are attracting attention, owing to their wide range of applications in wearable electronic devices. However, it is difficult to manufacture pressure sensors with high sensitivity, wide detection range, and low detection limits. We developed a highly sensitive and flexible capacitive pressure sensor based on the porous Ecoflex, which has an aligned airgap structure and can be manufactured by simply using a mold and a micro-needle. The existence of precisely aligned airgap structures significantly improved the sensor sensitivity compared to other dielectric structures without airgaps. The proposed capacitive pressure sensor with an alignment airgap structure supports a wide range of working pressures (20–100 kPa), quick response time (≈100 ms), high operational stability, and low-pressure detection limit (20 Pa). Moreover, we also studied the application of pulse wave monitoring in wearable sensors, exhibiting excellent performance in wearable devices that detect pulse waves before and after exercise. The proposed pressure sensor is applicable in electronic skin and wearable medical assistive devices owing to its excellent functional features.

Flexible pressure sensors have been studied as wearable voice-recognition devices to be utilized in human-machine interaction. However, the development of highly sensitive, skin-attachable, and comfortable sensing devices to achieve clear voice detection remains a considerable challenge. Herein, we present a wearable and flexible pressure and temperature sensor with a sensitive response to vibration, which can accurately recognize the human voice by combing with the artificial neural network. The device consists of a polyethylene terephthalate (PET) printed with a silver electrode, a filament-microstructured polydimethylsiloxane (PDMS) film embedded with single-walled carbon nanotubes and a polyimide (PI) film sputtered with a patterned Ti/Pt thermistor strip. The developed pressure sensor exhibited a pressure sensitivity of 0.398 kPa in the low-pressure regime, and the fabricated temperature sensor shows a desirable temperature coefficient of resistance of 0.13% C in the range of 25 C to 105 C. Through training and testing the neural network model with the waveform data of the sensor obtained from human pronunciation, the vocal fold vibrations of different words can be successfully recognized, and the total recognition accuracy rate can reach 93.4%. Our results suggest that the fabricated sensor has substantial potential for application in the human-computer interface fields, such as voice control, vocal healthcare monitoring, and voice authentication.

With the fast development of consumer electronic and artificial intelligence equipment, flexible pressure sensors (FPSs) have become a momentous component in the application of wearable electronic, electronic skin, and human-machine interfacing. The capacitive FPS possesses the merits of low energy consumption, high resolution, and fast dynamic response, so it is ideal for mobile and wearable electronics. However, capacitive FPS is vulnerable to electromagnetic interference and parasitic capacitance due to its low sensitivity. Microstructure or porous dielectric materials have been applied to improve the sensitivity of the capacitive FPS, but the high sensitivity is just limited to a narrow region. In this work, we propose a different strategy that incorporates a high-permittivity MXene nanocomposite dielectric with a 3D network electrode (3DNE) to improve the sensing performance of the capacitive FPS. Thanks to the high permittivity of the dielectric layer and hierarchical deformation of the electrode, the fabricated capacitive FPS exhibits a high sensitivity of 10.2 kPa-1 in the low pressure range (0-8.6 kPa) and still maintains a relatively high sensitivity of 3.65 kPa-1 with a near-linear response in a wide pressure range (8.6-100 kPa). In addition, the capacitive FPS can withstand over 20,000 times pressure loads without significant signal damping. Furthermore, the working mechanism of the capacitive FPS is illustrated by the finite element analysis (FEA) method and theoretical calculation. The application potential of the sensor in wearable electronics was demonstrated by human pulse wave monitoring and pressure mapping tests with a 4 × 6 sensor microarray.

Wide range pressure sensor construction based on tension-compression conversion and gradient stiffness design strategy