Triboelectric Signals Research Articles

Dual-sensory fusion self-powered triboelectric taste-sensing system towards effective and low-cost liquid identification.

Infusing human taste perception into smart sensing devices to mimic the processing ability of gustatory organs to perceive liquid substances remains challenging. Here we developed a self-powered droplet-tasting sensor system based on the dynamic morphological changes of droplets and liquid-solid contact electrification. The sensor system has achieved accuracies of liquid recognition higher than 90% in five different applications by combining triboelectric fingerprint signals and deep learning. Furthermore, an image sensor is integrated to extract the visual features of liquids, and the recognition capability of the liquid-sensing system is improved to up to 96.0%. The design of this dual-sensory fusion self-powered liquid-sensing system, along with the droplet-tasting sensor that can autonomously generate triboelectric signals, provides a promising technological approach for the development of effective and low-cost liquid sensing for liquid food safety identification and management.

Transparent, Stretchable, and Adhesive Conductive Ionic Hydrogel-Based Self-Powered Sensors for Smart Elderly Care Systems.

Nowadays, with the intensification of the aging society, the demand for elderly care and medical services is increasing and the elderly care and health systems are facing serious challenges. Therefore, it is imperative to develop a smart elderly care system to achieve real-time interaction between the elderly, the community, and medical personnel and to improve the efficiency of caring for the elderly. Here, we prepared ionic hydrogels with stable properties of high mechanical strength, high electrical conductivity, and high transparency by the one-step immersion method and used them in self-powered sensors for smart elderly care systems. The complexation of Cu2+ ions with polyacrylamide (PAAm) endows ionic hydrogels with excellent mechanical properties and electrical conductivity. Meanwhile, potassium sodium tartrate prevents the generated complex ions from precipitating into precipitates, thus ensuring the transparency of the ionic conductive hydrogel. After optimization, the transparency, tensile strength, elongation at break, and conductivity of the ionic hydrogel reached 94.1% at 445 nm, 192 kPa, 1130%, and 6.25 S/m, respectively. By processing and coding the collected triboelectric signals, a self-powered human-machine interaction system attached to the finger of the elderly was developed. The elderly can complete the transmission of distress and basic needs by simply bending their fingers, greatly reducing the pressure of inadequate medical care in an aging society. This work demonstrates the value of self-powered sensors in the field of smart elderly care systems, showing a wide implication in human-computer interface.

Worm Generator: A System for High-Throughput in Vivo Screening.

Large-scale screening of molecules in organisms requires high-throughput and cost-effective evaluating tools during preclinical development. Here, a novel in vivo screening strategy combining hierarchically structured biohybrid triboelectric nanogenerators (HB-TENGs) arrays with computational bioinformatics analysis for high-throughput pharmacological evaluation using Caenorhabditis elegans is described. Unlike the traditional methods for behavioral monitoring of the animals, which are laborious and costly, HB-TENGs with micropillars are designed to efficiently convert animals' behaviors into friction deformation and result in a contact-separation motion between two triboelectric layers to generate electrical outputs. The triboelectric signals are recorded and extracted to various bioinformation for each screened compound. Moreover, the information-rich electrical readouts are successfully demonstrated to be sufficient to predict a drug's identity by multiple-Gaussian-kernels-based machine learning methods. This proposed strategy can be readily applied to various fields and is especially useful in in vivo explorations to accelerate the identification of novel therapeutics.

Ultrastretchable, Self-Healing Conductive Hydrogel-Based Triboelectric Nanogenerators for Human–Computer Interaction

The rapid development of wearable electronic devices and virtual reality technology has revived interest in flexible sensing and control devices. Here, we report an ionic hydrogel (PTSM) prepared from polypropylene amine (PAM), tannic acid (TA), sodium alginate (SA), and MXene. Based on the multiple weak H-bonds, this hydrogel exhibits excellent stretchability (strain >4600%), adhesion, and self-healing. The introduction of MXene nanosheets endows the hydrogel sensor with a high gauge factor (GF) of 6.6. Meanwhile, it also enables triboelectric nanogenerators (PTSM-TENGs) fabricated from silicone rubber-encapsulated hydrogels to have excellent energy harvesting efficiency, with an instantaneous output power density of 54.24 mW/m2. We build a glove-based human-computer interaction (HMI) system using PTSM-TENGs. The multidimensional signal features of PTSM-TENG are extracted and analyzed by the HMI system, and the functions of gesture visualization and robot hand control are realized. In addition, triboelectric signals can be used for object recognition with the help of machine learning techniques. The glove based on PTSM-TENG achieves the classification and recognition of five objects through contact, with an accuracy rate of 98.7%. Therefore, strain sensors and triboelectric nanogenerators based on hydrogels have broad application prospects in man-machine interface, intelligent recognition systems, auxiliary control systems, and other fields due to their excellent stretchable and high self-healing performance.

Construction of foot-movement monitoring sensor based on triboelectric signals via embroidery technique with PDMS coated conductive cotton yarn

Construction of foot-movement monitoring sensor based on triboelectric signals via embroidery technique with PDMS coated conductive cotton yarn

Humanoid Ionotronic Skin for Smart Object Recognition and Sorting

Nowadays, there is an urgent need for humanoid robots containing human finger-like electronic skins with mechanical endurance and tactile perception. This study reports the development of an ionotronic skin-based humanoid robot hand that can recognize objects precisely through finger tapping or touching. The ionotronic skin is composed of a cytoskeleton-like filament network structure and possesses mechanical properties highly akin to human skins, including softness (Young’s modulus of 51 ± 15 MPa), toughness (1.6 ± 0.7 MJ m–3), and antifatigue-fracture ability. In addition, the i-skin functions as a triboelectric nanogenerator with the ability to perceive the triboelectric signals of an object when in contact with it. By combining triboelectric sensing information, machine learning, and Internet of Things techniques, the humanoid robot hand can accurately recognize different materials among a diverse set of spherical objects and further deliver them to the designated location. The high sorting success rate of 97.2% in 600 tests of recognizing five types of spherical objects, together with the outstanding mechanical and environmental tolerance, allow such humanoid robot hands to be used for intelligent sorting, automatic operation, and assembly in unmanned factories, as well as for the classification of garbage and hazardous materials.

A Smart Pen Based on Triboelectric Effects for Handwriting Pattern Tracking and Biometric Identification.

The rapid development of artificial intelligence places high demands on human-machine interfaces. Various types of huma-machine interfaces have been implemented, including smart keyboards, electronic skins, and wearable motion sensors. Handwriting behavior has a high degree of interaction freedom, and handwriting characteristics offer high-security standards for human-machine systems. Herein, we propose a portable smart pen integrated with triboelectric displacement vector sensors to trace handwriting trajectories for human-machine interactions and biometric identification. A triboelectric pressure sensor array is evenly distributed along the pen case to sense displacement vectors, and an additional triboelectric sensor is placed on top of the pen to detect vertical force. By leveraging the resin pen refill as a tribopositive material and a nanowired polyethylene tribonegative layer attached to a Cu electrode, triboelectric signals are generated during the writing/moving process. The calculation and analysis of the sensor signals enable the recognition of handwritten patterns, including Latin letters and Arabic numerals. Moreover, the smart pen can be used to authenticate users based on their unique handwriting patterns, which can help take human-machine interfaces and cyber security to the next level. Furthermore, a custom smart pen operation mode that enables the control of a slide presentation demonstrates the smart pen's potential for various human-machine interface applications.

Kirigami interactive triboelectric mechanologic

Mechanical logic and computation embedded in deployable structures are complementary to conventional digital logic schemes for autonomous sense, decision, and response in artificial intelligence and bio-robots. It is highly desired that responsive and adaptive structures can readily interact with external stimuli to implement mechanologic (e.g., writing, erasing, and rewriting mechanical bit) in an energy-efficient way. Here, we demonstrate kirigami interactive triboelectric mechanologic composed of a deployable kirigami geometry triggered by triboelectric signal for the first time, aiming at developing interactive and programmable mechanical computation. The interactive triboelectric mechanologic is inspired by human somatic reflex arc system to emulate the continual sensation–decision–response loop, which includes a self-powered triboelectric nanogenerator (TENG) mechanoreceptor, a signal transmission/processing module, and an elaborately designed kirigami geometry with bistable resistive states to represent mechanologic. When the mechanoreceptor is imposed to mechanical stimuli, the induced triboelectric signals activate the bistable state conversion in the kirigami geometry and endow it with adaptive capacity to output binary mechanical bits. We successfully demonstrate the application of interactive triboelectric mechanologic as a mechanical flip-flop, register, and asynchronous binary counter. This work provides a new route to self-activation mechanologic computation relying on the extended application of TENG for self-driven sensing and actuation.

Self-Powered Force Sensors for Multidimensional Tactile Sensing

A tactile sensor is the centerpiece in human-machine interfaces, enabling robotics or prosthetics to manipulate objects dexterously. Specifically, it is crucial to endow the sensor with the ability to detect and distinguish normal and shear forces in real time, so that slip detection and more complex control could be achieved during the interaction with objects. Here, a self-powered multidirectional force sensor (SMFS) based on triboelectric nanogenerators with a three-dimensional structure is proposed for sensing and analysis of normal and shear forces in real time. Four polydimethylsiloxane (PDMS) cylinders act as the force sensing structure of the SMFS. A flexible tip array made of carbon black/MXene/PDMS composites is used to generate triboelectric signals when the SMFS is driven by an external force. The SMFS can sense multidimensional force due to the adaptability of the PDMS cylinders and detect tiny force due to the sensitivity of the flexible tips. A small shear force as low as 50 mN could be recognized using the SMFS. The direction of the externally applied force could be recognized by analyzing the location and output voltage amplitude of the SMFS. Moreover, the tactile sensing applications, including reagent weighing and force direction perception, are also achieved by using the SMFS, which demonstrates the potential in promoting developments of self-powered wearable sensors, human-machine interactions, electronic skin, and soft robotic applications.

A method for quantitatively separating the piezoelectric component from the as-received \u201cPiezoelectric\u201d signal

Polymer-based piezoelectric devices are promising for developing future wearable force sensors, nanogenerators, and implantable electronics, etc. The electric signals generated by them are often assumed as solely coming from the piezoelectric effect. However, triboelectric signals originated from contact electrification between the piezoelectric devices and the contacted objects can produce non-negligible interfacial electron transfer, which is often combined with the piezoelectric signal to give a triboelectric-piezoelectric hybrid output, leading to an exaggerated measured “piezoelectric” signal. Herein, a simple and effective method is proposed for quantitatively identifying and extracting the piezoelectric charge from the hybrid signal. The triboelectric and piezoelectric parts in the hybrid signal generated by a poly(vinylidene fluoride)-based device are clearly differentiated, and their force and charge characteristics in the time domain are identified. This work presents an effective method to elucidate the true piezoelectric performance in practical measurement, which is crucial for evaluating piezoelectric materials fairly and correctly.

A triboelectric-inductive hybrid tactile sensor for highly accurate object recognition

Tactile sensors can enable a robotic manipulator to identify the object in contact. However, due to the dynamics and diversity of target objects, as well as the complexity of real environment, accurate recognition of objects by existing tactile sensors has been very challenging. This paper proposes a hybrid tactile sensor that integrates a triboelectric active sensing unit with an electromagnetic inductance transducer. The triboelectric signal relates strongly to the specific charge condition of the surface material of a target object, while the inductive signal manifests the electromagnetic characteristics at a certain depth inside the object. With the help of machine learning, the triboelectric signals and inductive signals can be used for object identification. We demonstrate a robotic gripper with random operation settings can recognize eight different fruits with an accuracy as high as 98.75%. Furthermore, the hybrid sensor can recognize objects packaged in different ways. The recognition accuracy of four different fruits in three different packages can reach 95.93%. This study demonstrates the potential of hybrid tactile sensor to improve the artificial intelligence of robots, in particular their ability to distinguish objects in complex settings and sorting them effectively.

Self‐Powered and Imperceptible Electronic Tattoos Based on Silk Protein Nanofiber and Carbon Nanotubes for Human–Machine Interfaces

AbstractTriboelectric electronic skins (E‐skins) can be used as primary interactive devices for human–machine interfaces (HMIs). However, devices for seamless on‐skin operations must be soft and deformable, and attachable to and compatible with the skin. In this paper, a substrate‐free, skin‐compatible, skin‐attachable, mechanically deformable, and self‐powered E‐tattoo sticker consisting of carbon nanotubes (CNTs) and silk nanofibers (SNFs) is presented. The E‐tattoo can be imperceptibly tattooed on the skin and removed with water. When the device touches naked skin, triboelectric signals are generated. Because of the micro‐to‐nano hierarchical pores (with high surface‐to‐volume ratios), contact‐induced electrification generates a power density of ≈6 mW m−2 and pressure sensitivity of ≈0.069 kPa−1. The power generated on the tattooed skin can activate small electronic devices. Moreover, whole‐body joint movements can be monitored and tactile movements can be mapped by reading the generated electrical signals. The presented E‐tattoo system can promote the development of flexible energy and sensor systems for self‐powered, energy‐autonomous, imperceptible E‐skin devices for HMIs and artificial intelligent robotics and prostheses.

Contact-electrification-activated artificial afferents at femtojoule energy

Low power electronics endowed with artificial intelligence and biological afferent characters are beneficial to neuromorphic sensory network. Highly distributed synaptic sensory neurons are more readily driven by portable, distributed, and ubiquitous power sources. Here, we report a contact-electrification-activated artificial afferent at femtojoule energy. Upon the contact-electrification effect, the induced triboelectric signals activate the ion-gel-gated MoS2 postsynaptic transistor, endowing the artificial afferent with the adaptive capacity to carry out spatiotemporal recognition/sensation on external stimuli (e.g., displacements, pressures and touch patterns). The decay time of the synaptic device is in the range of sensory memory stage. The energy dissipation of the artificial afferents is significantly reduced to 11.9 fJ per spike. Furthermore, the artificial afferents are demonstrated to be capable of recognizing the spatiotemporal information of touch patterns. This work is of great significance for the construction of next-generation neuromorphic sensory network, self-powered biomimetic electronics and intelligent interactive equipment.

Triboelectric signal generation and its versatile utilization during gear-based ordinary power transmission

Gear is one of the most ordinary and effective components for transmitting mechanical power and thus, it has been used in various industrial fields as a core component of machines. In this paper, the mechanism of triboelectric signal generation during gear-based ordinary power transmission is firstly proposed. The signal generation mechanism during contact and separation of engaged gear teeth is verified by intensive analytical, numerical as well as experimental analyses. Given that the remarkable amount of the electric signal can be periodically generated during its operation, the generated signal can be utilized to develop a real-time and self-triggered gear-based power transmission monitoring system, which is simple, cost-effective and user-friendly compared to the other existing methods. Beyond detecting the electric signals, a binary code generator is established using the change in signals. Furthermore, scavenging the spontaneously generated triboelectric signals while operating the gearbox enables us to advantageously utilize wasted energy. The simple electronic devices such as Bluetooth based wireless thermo-hygrometer, calculator and custom-built LED display with more than 100 LEDs can be sufficiently operated by using the wasted energy that is easily harvested during ordinary power transmission. • Proposal of triboelectric signal generation with gear-based ordinary power transmission. • Analytical, numerical and experimental Intensive analyses on triboelectric signal generation. • Development of a real-time and self-triggered gear status monitoring system. • Energy harvesting during gear-based ordinary power transmission.

A universal and arbitrary tactile interactive system based on self-powered optical communication

Internet of Things (IoT) has diffused into practically every profession relying on various functional sensors and interactive interfaces. It is desirable to develop a cheap, facile, and energy-autonomous interactive system based on highly efficient optical communication. Here, we demonstrate a universal and stable tactile interactive system (TIS) on arbitrary objects through a self-powered optical communicator triggered by the triboelectric electric signals. The TIS includes a triboelectric nanogenerator (TENG) as the signal generator, a self-powered rectifying optical communicator, and a signal processing unit. Through the developed system, we can more effectively utilize the irregular/imperfect triboelectric signals to drive the optical communicator and implement various applications (including tactile switch, flowing LEDs, paper piano, PPT and domestic appliances wireless controller). The proposed TIS is simple in circuit design, capable of converting arbitrarily irregular/imperfect triboelectric signals and consumes low power and cost. It is believed the TIS will make great contributions to intelligent mechanosensation, precise digital control, smart home systems and advanced industrial manufacturing in future.

High-Performance Electronic Cloth for Facilitating the Rehabilitation of Human Joints.

The concern about easily characterizing the conditions of human joints to facilitate rehabilitation during recovery training has been out of sight, even though it is acknowledged that timely recovering functions of injured joints is a must. To facilitate the situation to be addressed, a stretchable, air-permeable electronic cloth (SApEC) was fabricated by electrostatic spinning and hot-pressing. The SApEC consists of conductive-elastic fabric Ag and composite nanofibrous membrane (CNFM) with components of poly(vinylidene fluoride- co-hexa-fluoropropyiene) and thermoplastic urethane. The electronic cloth not only owns chemical stability and ultralight weight, but scavenges triboelectric signals from joint movements. These characters allow the SApEC to be an easy and convenient indicator to indicate the activity of joints, when users get rehabilitation training in non-hospital places. With the assistance of several electronic components, the SApEC could control alarms, such as a warning lamp. This favorable ability allows the SApEC to make alerts, once users face any accidents again, like sudden fall or heart failure. Given the advantages mentioned above, it is reasonable to believe that the SApEC has a promising prospect in portable and wearable electronics, involving indicating rehabilitation of joints and keeping an eye on users' safety.

Chitosan biopolymer‐derived self‐powered triboelectric sensor with optimized performance through molecular surface engineering and data‐driven learning

AbstractThe state‐of‐the‐art triboelectric nanogenerators (TENGs) are constructed with synthetic polymers, curtailing their application prospects and relevance in sustainable technologies. The economically viable transformation and engineering of naturally abundant materials into efficient TENGs for mechanical energy harvesting is meaningful not only for fundamental scientific exploration, but also for addressing societal needs. Being an abundant natural biopolymer, chitosan enables exciting opportunity for low‐cost, biodegradable TENG applications. However, the electrical outputs of chitosan‐based TENGs are low compared with the devices built with synthetic polymers. Here, we explore the facile molecular surface engineering in chitosan to significantly boost the performance of chitosan‐based TENG for enabling the practical applications, for example, self‐powered car speed sensor. The molecular surface engineering offers a potentially promising scheme for designing and implementing high‐performance biopolymer‐based TENGs for self‐powered nanosystems in sustainable technologies. We further explore for the first time the feasibility of data mining approaches to analyze and learn the acquired triboelectric signals from the car speed sensors and predict the relationship between the triboelectric signals and car speed values.

Transparent and stretchable triboelectric nanogenerator for self-powered tactile sensing

Wearable electronic devices have attracted numerous attention in tactile sensing, motion detecting, and biomedical signal monitoring. In particular, a wearable and self-powered sensor combining all the merits of sensitivity, transparency, stretchability, and flexibility is highly demanded to adapt human skins. Herein, we report a fully transparent, highly stretchable, and self-powered contact-separation triboelectric nanogenerator (TENG) as a tactile sensor. The TENG consists of a double-network ionogel with the transparency, stretchability, and conductivity as the electrode and one friction layer, and patterned polydimethylsiloxane (PDMS) as another friction layer. The fabricated sensor reaches a maximum sensitivity of 1.76 V N−1 when detecting impacting forces in the range of 0.1–1 N. Meanwhile, with good stretchability of the sensor, the triboelectric signals maintain a good linearity with impacting forces at different tensile ratios (0%, 10%, 50%, and 80% strain). These properties enable the sensor to be capable of monitoring a variety of human activities, including finger touching and bending, breathing, and pulse beating. We believe such a transparent, stretchable and self-powered tactile TENG sensor has tremendous application potential in wearable and soft electronics.

Performance-enhanced triboelectric nanogenerator enabled by wafer-scale nanogrates of multistep pattern downscaling

Herein, we report a triboelectric nanogenerator (TENG) with improved performance using extremely-long sub-50nm grating patterns with high aspect ratio (4,000,000:1) fabricated by the multistep pattern downscaling (MS-PaD) method, which is advantageous in terms of fast throughput, high resolution, cost-effectiveness, industrial compatibility, and large-area scalability in nanofabrication. The intensely-arrayed nanograting pattern is replicated to the flexible substrate on the 8-in. wafer-scale without any defects for the nanograting-assisted TENG (NGTENG). As the well-aligned nanoscale morphology in sub-50nm grating leads to efficient triboelectric charges, the NGTENG shows an outstanding performance enhancement by a factor of 200 compared to non-patterned surface during repetitive contact electrification. To demonstrate capability of self-powered electronics, the output power from the NGTENG is directly used for charging a commercial capacitor and turning on the LEDs. In addition, theoretical study of triboelectric signals according to nanoscale-tuned metal electrodes were investigated to improve the effective output and robustness of triboelectric device.

Continuous on-line measurement of solid moisture content during fluidized bed drying using triboelectric probes

Wet granulation and drying of solids in fluidized beds are widely used in the pharmaceutical, food and fertilizers industries. Although the moisture content of fluidized solids is the key parameter for on-line process monitoring, reliable, accurate and economical moisture sensors are lacking. The aim of this work was, therefore, to develop a new technique using triboelectric probes for real-time measurement of moisture content in fluidized beds, and to validate its applicability to fluid bed drying of glass beads (Sauter-mean diameter of 171 μm) and silica sand particles (Sauter-mean diameter of 190 μm) wetted by water. Several triboelectric probes, installed at different locations throughout the bed, monitored the bed moisture content during both the liquid spraying and the following drying process. The measuring technique developed in this study makes use of inexpensive probes that do not require any maintenance. The triboelectric signals were continuously recorded by a data acquisition system and, at selected times, samples of bed solids were taken and analyzed for their moisture content using Karl Fischer titration. The triboelectric signals were correlated with the moisture contents determined by titration to calibrate the technique, which was found to be sensitive to moisture contents below 100 ppm. For most of the experiments the bed was operated in the bubbling regime with a superficial gas velocity of 0.4 m/s. The relationship between triboelectric signal and moisture content was unaffected by changes in the fluidization gas velocity of up to 25%, and could be easily automated for direct control of industrial granulation and drying processes.