An efficient pressure sensor based on environmental-friendly CNTs-graphene-PDMS film

With the fast development of electronic skin, there is a great demand for wearable sensing devices. Herein, a piezoresistive sensor has been fabricated comprising a conductive film of Polydimethylsiloxane (PDMS)-carbon nanotubes (CNTs) sandwiched by two protection films of PDMS. A simple and low-cost manufacturing method has been proposed to wrap CNTs inside the flexible PDMS to obtain a soft sensor with excellent conductivity, high sensitivity, and fast response to various pressures. Additionally, films with different percentages of CNTs were compared. The results show that the film with 7% CNTs has higher conductivity and sensitivity. Moreover, the surface morphologies and microstructures of the superior PDMS-CNTs film were studied by scanning electron microscope, and sensing properties of the pressure sensor were tested. Furthermore, applications of single sensor and sensor array were studied. The results exhibit that the as-prepared pressure sensor successfully detected different human motions and recognized Morse code and words, indicating that the portable sensor can be potentially applied in wide areas such as smart devices and flexible robotics.

Nature-motivated pressure sensors have been greatly important components integrated into flexible electronics and applied in artificial intelligence. Here, we report a high sensitivity, ultrathin, and transparent pressure sensor based on wrinkled graphene prepared by a facile liquid-phase shrink method. Two pieces of wrinkled graphene are face to face assembled into a pressure sensor, in which a porous anodic aluminum oxide (AAO) membrane with the thickness of only 200 nm was used to insulate the two layers of graphene. The pressure sensor exhibits ultrahigh operating sensitivity (6.92 kPa-1), resulting from the insulation in its inactive state and conduction under compression. Formation of current pathways is attributed to the contact of graphene wrinkles through the pores of AAO membrane. In addition, the pressure sensor is also an on/off and energy saving device, due to the complete isolation between the two graphene layers when the sensor is not subjected to any pressure. We believe that our high-performance pressure sensor is an ideal candidate for integration in flexible electronics, but also paves the way for other 2D materials to be involved in the fabrication of pressure sensors.

Wearable textile pressure sensors with piezoelectric properties are a very effective way of detecting movements of the human body based on the force exerted by the sensor. Owing to the merits of flexibility and breathability, the textile pressure sensor finds potential application in biomedical monitoring and human-machine interaction. The textile pressure sensor works on the principle of piezoelectricity where an electrode of conductive woven fabric forms the outer layer and a semi-conductive material such as ZnO is sandwiched between two conductive layers. ZnO is prepared using a simple hydrothermal method and SEM, XRD are two effective methods to detect the presence of ZnO on the conductive fabric. The pressure applied on the fabric is translated into voltage and the output voltages are compared using two samples of ZnO nanostructures. The effect of the seed layer is investigated under identical growth and measurement which influences the output performance of voltage. This property can be used to change the sensitivity and working range of pressure sensor for specific applications. The pressure sensor designed can be sewn directly onto the clothing which conforms to the human body’s flexible curved surface.

The development of wearable electronic devices for human health monitoring requires materials with high mechanical performance and sensitivity. In this study, we present a novel transparent tissue-like ionogel-based wearable sensor based on silver nanowire-reinforced ionogel nanocomposites, P(AAm-co-AA) ionogel-Ag NWs composite. The composite exhibits a high stretchability of 605% strain and a moderate fracture stress of about 377 kPa. The sensor also demonstrates a sensitive response to temperature changes and electrostatic adsorption. By encapsulating the nanocomposite in a polyurethane transparent film dressing, we address issues such as skin irritation and enable multidirectional stretching. Measuring resistive changes of the ionogel nanocomposite in response to corresponding strain changes enables its utility as a highly stretchable wearable sensor with excellent performance in sensitivity, stability, and repeatability. The fabricated pressure sensor array exhibits great proficiency in stress distribution, capacitance sensing, and discernment of fluctuations in both external electric fields and stress. Our findings suggest that this material holds promise for applications in wearable and flexible strain sensors, temperature sensors, pressure sensors, and actuators.

The paper presents a novel fabrication process for single or arrays of micro pressure sensors. The fabrication process is almost the reverse of the surface micromachining process used for the pressure sensor. This allows the use of SU-8 to form a cavity that can be much deeper for pressure measurement. Thus, the sensor can provide a much wider range of pressure measurement. The fabrication process has a complete absence of diaphragm stiction. In addition, arrays of pressure sensors can be readily made and integrated into a complicated micro system. More detailed design and fabrication techniques developed for this sensor are presented.

ABSTRACTIn this study, epoxy shape‐memory polymer (ESMP) was infiltrated into the scaffolds of vertically aligned carbon nanotubes (CNTs) array grown by chemical vapor deposition (CVD). In the fabricated CNTs array/ESMP nanocomposite, the CNTs interconnected with each other and a three‐dimensional (3D) network of the CNTs was formed. As a result, both thermal conductivity and electrical conductivity of the CNTs array/ESMP nanocomposite were higher than the random CNTs/ESMP composite fabricated by conventional high‐speed mechanical stirring. In the random CNTs/ESMP composite, the CNTs aggregated seriously in the matrix. Along the CNTs axis, The CNTs array/ESMP nanocomposite showed a higher modulus and hardness than the random CNTs/ESMP composite, as revealed by nanoindentation tests. Under microwave radiation, the temperature of the CNTs array/ESMP nanocomposite increased more rapidly than pristine ESMP and the random CNTs/ESMP composite. Consequently, the CNTs array/ESMP nanocomposite showed a faster shape recovery speed compared with pristine ESMP and the random CNTs/ESMP composite in their microwave‐triggered shape memory behaviors. Especially, the CNTs array/ESMP nanocomposite can recover the deformation fully in response to as low as 60 W microwaves. The presented CNTs array/ESMP nanocomposite with improved mechanical property and fast responses to low‐power microwaves may find potential applications in smart devices. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci.2019,136, 47563.

Flexible wearable pressure sensors play a pivotal role in healthcare monitoring, disease prevention, and humanmachine interactions. However, their narrow sensing ranges, low detection sensitivities, slow responses, and complex preparation processes restrict their application in smart wearable devices. Herein, a capacitive pressure sensor with high sensitivity and flexibility that uses an ionic collagen fiber material as the dielectric layer is proposed. The sensor exhibits a high sensitivity (5.24 kPa−1), fast response time (40 ms), long-term stability, and excellent repeatability over 3000 cycles. Because the sensor is resizable, flexible, and has a simple preparation process, it can be flexibly attached to clothes and the human body for wearable monitoring. Furthermore, the practicality of the sensor is proven by attaching it to different measurement positions on the human body to monitor the activity signal.

Electronic skin (E-skin) has gained significant attention due to its potential applications in the Internet of Things (IoT), artificial intelligence (AI), and flexible multi-sensing systems. Mimicking human skin, e-skin sensing devices can be employed in various scenarios. Among the most important sensing elements for tactile e-skin sensors are pressure and temperature sensors, which have increasingly garnered research interest over the past few decades. However, the design and fabrication of advanced pressure and temperature sensors can be challenging owing to complications such as signal interference, complex mechanism integration, and structural design issues. This review provides an overview of flexible pressure and temperature sensors used in e-skin, covering four main perspectives: material selection, mechanism integration, structural design, and manufacturing methods. The materials of different elements in the entire sensing system are comprehensively discussed, along with single and compound mechanisms of pressure and temperature sensing. Pressure and temperature sensors are divided into two types based on their electric output signals, which are exemplified in detail. The manufacturing methods used to fabricate these sensors, including printing methods, are outlined. Lastly, a summary of the future challenges faced by flexible pressure and temperature sensors used in e-skin is presented.

The fast progress in artificial intelligence has increased the need for wearable electronics. Herein, a piezoresistive pressure sensor consisting of three layers has been proposed. The soft sensing film has been fabricated by filling PDMS (polydimethylsiloxane) with Ag-graphene by a simple mixing method, which possesses low cost and excellent sensing properties, including high sensitivity, high conductivity, and quick response to different pressures. Furthermore, the characterizations were performed by using a scanning electron microscope to study the microstructure and surface morphologies of the Ag-graphene-PDMS film to explore its internal working mechanism. Moreover, the single sensor and sensor array were tested for many applications. The results showed that the fabricated pressure sensor effectively identified various human movements and distinguished pressures with different values and positions. As a result, this sensor has a wide range of applications, including smart wearable technologies and soft robotics.

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

Over the last decade, the rapid development in health care industry and security has driven innovations in the field of wearable electronics and smart sensors. This report demonstrates the fabrication of molybdenum diselenide (MoSe2) by a facile, low-cost and scalable hydrothermal synthesis method followed by a vacuum filter deposition on cellulose paper. The fabricated device is utilized as a pressure and strain sensor. The fabricated device is passivated using polydimethylsiloxane (PDMS), and also, PDMS film enhances the flexibility of the device. The calculated sensitivity of pressure sensor is ~0.3 kPa <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> , which is comparable and relatively better than the pressure sensor fabricated using sophisticated techniques. Furthermore, the device exhibited significant of merit for strain sensing with a gauge factor of ~6.84. The fabricated device showed excellent resilience in 500 cycle bending tests, which promises the robustness of the device. As an application, the fabricated sensor is used to develop a wireless keyboard by integrating the sensor on fingertips of an individual and a real-time human motion monitoring application in which the data are transmitted wirelessly to a smartphone with a dedicated android application. The successful fabrication of MoSe2/paper-based cost-effective, flexible, and biodegradable pressure-strain sensor shows tremendous applications in future intelligent user interface systems, human security, and personal health care monitoring.

A novel approach of fusing datasets from multiple sensors using a hierarchical support vector machine (HSVM) algorithm is presented. The validation of this method is experimentally carried out using an intelligent learning system that combines two different data sources. The sensors are based on a contactless sensor, which is a radar that detects the movements of the hands and fingers, as well as a wearable sensor, which is a flexible pressure sensor array that measures pressure distribution around the wrist. A HSVM architecture is developed to effectively fuse different data types in terms of sampling rate, data format, and gesture information from the pressure sensors and radar. In this respect, the proposed method is compared with the classification results from each of the two sensors independently. Herein, datasets from 15 different participants are collected and analyzed. The results show that the radar on its own provides a mean classification accuracy of 76.7%, whereas the pressure sensors provide an accuracy of 69.0%. However, enhancing the pressure sensors' output results with radar using the proposed HSVM algorithm improves the classification accuracy to 92.5%.

Wearable sensors have been developed for various healthcare applications with human motion detection. For strain sensors to be adopted in smart wearable devices for human joint motion detection, it is necessary that they have excellent mechanical properties such as stretchability, flexibility, softness, and they should be non-toxic to the human body. In this paper, we report on a possible candidate for such a sensor: the polymer fiber composited with polydimethylsiloxane (PDMS) and Zinc Oxide (ZnO) nanoparticles. This polymer fiber exhibits softness, flexibility, stretchability, and reproducibility. Moreover, it has a tensile property of over 100% and excellent resilience. The strain evaluation of the ZnO-PDMS polymer fiber with silica fibers on the ends was carried out with a light emitting diode (LED) and photodetector. The strain sensor with polymer fiber has good properties of strain measurement; stable signal recovery, as well as rapid, immediate, and repeatable response in real-time. The polymer strain sensor was evaluated on the human finger and wrist joints for detection of the bending motion. Moreover, because this polymer strain sensor is waterproof, it can be used for measuring finger bending and releasing even in wet conditions. The results demonstrate that the ZnO-PDMS optical fiber strain sensor can be employed in wearable devices for healthcare applications such as sports and rehabilitation.

In recent years, smart textiles and flexible wearable products have garnered significant attention in fields such as human-computer interaction, medical rehabilitation training, and motion monitoring. Flexible pressure sensors have attracted significant attention due to their excellent flexibility, stability, and multifunctional integration. Herein, a multifunctional wearable MXene/polydopamine (PDA)@cotton fabric pressure sensor was developed by modifying weft-knitted cotton fabric based on a dual hydrogen bond self-assembly strategy. The MXene/PDA@cotton fabric pressure sensor demonstrates wide linear detection range (0-146 kPa), high sensitivity (0.95 kPa-1), fast response/recovery times (16.434 and 11.952 ms), and outstanding stability after over 5000 cyclic tests. This sensor can achieve the monitoring of physiological parameters for human state detection, such as facial expression signals, abdominal respiratory signals, and joint bending signals. Furthermore, by integrating the MXene/PDA sensors into the interphalangeal and metacarpophalangeal joints of a cotton glove, combined with intelligent algorithms and the human-computer interaction system, static gesture recognition and dynamic sign language translation were successfully realized based on the smart glove. This work demonstrates the potential application of flexible pressure sensors in intelligent human-computer interaction, providing new insights for developing next-generation sign language recognition systems.

Hydrogels’ poor mechanical and recovery characteristics inhibited their application as a plastic deformable three-dimensional cross-linked network polymer with electrical properties for intelligent sensing and human motion detection. Cellulose has also been added to the hydrogel to enhance its mechanical properties. The hydrogel has been enhanced this way, and the double-network hydrogel has superior recovery and mechanical capabilities. This study used the traditional free radical polymerization method to prepare double-mesh hydrogels, with polyacrylamide as the backbone network, xanthan gum double-helix structure, and Al3+ complex structure as the second cross-linked network, and endowing the hydrogels with good mechanical recovery and mechanical properties. Adding cellulose nanowafers (CNWs) improved the mechanical properties of the hydrogels. The hydrogel could detect body movements and various postures in the same environment. Moreover, the hydrogel has excellent recovery, mechanical properties, and tensile strain; the maximum fracture stress is 0.14 MPa, and the maximum strain is 707.1%. In addition, Fourier infrared spectroscopy (FTIR) of xanthan gum and Xanthan gum—Al3+ were analyzed, and thermogravimetric analysis (TGA) and LCR bridge were used to analyze the properties of hydrogels. Notably, hydrogel-based wearable sensors have been successfully constructed to detect human movement. Its mechanical properties, sensitivity, and wide range of properties make hydrogel a great potential for various applications in wearable sensors.