Triboelectric Signal Research Articles

Triboelectric signal enhancement via interface structural design and integrated with deep learning for real-time online material recognition

Triboelectric nanogenerator (TENG) is a promising technology for material recognition due to a large amount of distinguishable feature information in triboelectric signal when the TENG device touches different materials. Nevertheless, the identification precision has only improved from the perspective of sensor construction and operation of design, rather than from the electrodes and the triboelectric interface structure. To prevent such issues, a design strategy of electrode/triboelectric material interface structure is applied to enhance the output performance and recognition accuracy. Electroless nickel was plated on a sponge to fabricate a TENG device electrode with a roughness of 179.1 µm. A coarse triboelectric material/electrode interface can improve the output performance of corresponding device. Hence, the nickel layer surface generates more the triboelectric charges, further leading to characteristic triboelectric signals, which can be distinguished by deep machine learning. As expected, the collected TENG signal has the unique characteristic of being able to identify the touched material with a recognition accuracy of 96 %. Based on this, combined with deep machine learning and the triboelectric effect, a material awareness system integrating TENG-based sensors, data collation, and display components was also designed and built for real-time material type identification with superior accuracy. The potential application advantages of the manufactured TENG device in nonvisual intelligent recognition can be foreseen.

A bioinspired triboelectric wireless anemometer with low cut-in wind speed for meteorological UAVs

Currently, unmanned aerial vehicles (UAVs) play a pivotal role in meteorological wind speed measurements. Nevertheless, existing anemometers exhibit notable issues, including excessive weight, high cost and high cut-in wind speed. This investigation introduces a biomimetic owl wing airfoil wind speed sensor utilizing the principles of the triboelectric nanogenerator (BOW-TENG) designed for UAV applications. Inspired by owl wings, an airfoil configuration with superior aerodynamic characteristics is ascertained, subsequently fabricating it into an impeller, and a wind speed sensor with low weight, low cost and low cut-in wind speed is developed. Experimental results affirm the BOW-TENG’s precision in depicting wind speed across the range of 1.6–10.7 m/s, featuring a sensitivity of 21.893 Hz/(m·s−1), a goodness of fit R2 of 0.9995, and a remarkable resolution of 0.057 m/s. The sensor weighs only 30 g. Furthermore, a cost-effective triboelectric signal processing system is devised for integrating the BOW-TENG into the UAV, as well as the optimal positioning for BOW-TENG on the UAV is identified through simulations. The relative wind direction can be calculated from signals of the BOW-TENGs on the four arms of the UAV. Ultimately, application experiments demonstrate the feasibility of employing BOW-TENG for wireless wind speed transmission from UAVs. This work incorporates bionics and proposes a practical application of triboelectric sensors for UAVs, as well as a solution for developing wind speed sensors in the field of meteorological UAV detection.

Self‐Powered Digital Angle Sensor Based on Triboelectric Signal for Variable Structure of Aircraft

AbstractThe rapid development of aircraft in recent years has attracted more attention, especially the issue of safe flight for aircraft. Some existing angle detection sensors are difficult to adapt to the development speed of the current aircraft due to the expensive price and large size, so there is an immediate need for new technology that can suit the current aircraft. Here, a self‐powered digital angle sensor that is compact, simple, and lightweight is introduced. This sensor eliminates the need for an external power supply and demonstrates highly sensitive signal detection at the volt level when the variable structure of the aircraft is working. The sensor is designed with a thickness of 7.3 mm, a volume of 16.6 cm3, and a weight of 9.85 g. Its lightweight and compact structure allows for seamless integration into aircraft without causing significant impact. The sensor not only provides real‐time monitoring the aircraft's variable structure deflection states, including deflection direction and angle but also alerts operators to any anomalies in deflection. Its small size and self‐powered capability make it an ideal solution for aircraft applications, enhancing safety and efficiency during flight.

A dual‐range Janus‐structure pressure sensor with broad detection range and high resolution combining triboelectricity and piezoelectricity

AbstractEnabling pressure sensors with high resolution and a broad detection range is of paramount importance yet challenging due to the limitations of each known sensing method. Overlying different sensing mechanisms to achieve complementary functions is a promising approach, but it often leads to increased device thickness, crosstalk signals and complex signal channel management. Herein, we present a dual‐functional conformable pressure sensor that adopts a Janus thin film layout, enabling simultaneous piezoelectric and triboelectric signal detection capabilities between just one electrode pair, showing a most compact device configuration. Notably, despite its thin thickness (~80 μm for a packaged device), it exhibits a broad‐range detection capability with high signal resolution and fast response time, demonstrating a distinct signal‐relay characteristic corresponding to piezoelectricity and triboelectricity. Despite the slimness and simple structure, it shows an impressive signal resolution of 0.93 V·kPa−1 in the range of 0.1–140 kPa and 0.05 V·kPa−1 in the range of 140–380 kPa. Moreover, the device fabrication can be combined with the kirigami method to improve fitting to joint surfaces. This work introduces an innovative paradigm for designing advanced pressure sensing mechanisms, enabling a single device that can meet diverse application scenarios through its simplicity, slim layout, conformable, and self‐powered characteristics to adapt to multiple scenarios.image

Influence of SiC and ZnO Doping on the Electrical Performance of Polylactic Acid-Based Triboelectric Nanogenerators.

Polylactic acid (PLA) is one of the most widely used materials for fused deposition modeling (FDM) 3D printing. It is a biodegradable thermoplastic polyester, derived from natural resources such as corn starch or sugarcane, with low environmental impact and good mechanical properties. One important feature of PLA is that its properties can be modulated by the inclusion of nanofillers. In this work, we investigate the influence of SiC and ZnO doping of PLA on the triboelectric performance of PLA-based tribogenerators. Our results show that the triboelectric signal in ZnO-doped PLA composites increases as the concentration of ZnO in PLA increases, with an enhancement in the output power of 741% when the ZnO concentration in PLA is 3 wt%. SiC-doped PLA behaves in a different manner. Initially the triboelectric signal increases, reaching a peak value with enhanced output power by 284% compared to undoped PLA, when the concentration of SiC in PLA is 1.5 wt%. As the concentration increases to 3 wt%, the triboelectric signal reduces significantly and is comparable to or less than that of the undoped PLA. Our results are consistent with recent data for PVDF doped with silicon carbide nanoparticles and are attributed to the reduction in the contact area between the triboelectric surfaces.

A novel self-powered triboelectric sensor for early waring of lubrication failure

In tribology, maintaining good lubrication of friction pairs is an important technical means to reduce wear and failure, which is very important but difficult to monitor the lubrication state of friction pairs. In this paper, when measuring the thickness and shape of the lubricating oil film by the ball-disk elastohydrodynamic oil film measuring instrument, a current amplifier is integrated to measure the electrical signal generated during the friction process. By monitoring the change of lubricating oil film, the change of ball-disk friction force, and the change of triboelectric signal during the friction process in real time, the relationship between the tribological behavior and the triboelectric behavior of the friction pair is explored. The experimental results show that under the conditions of limited oil supply, different rotational speeds and different lubricating oil viscosities, the time of the discharge phenomenon of the steel ball corresponds one-to-one with the time when the friction pair starts to wear under oil-scarce lubrication. The discharge occurs due to the electric charge breaking through the air in the micro-gap of the wear scar. The results demonstrate that the formation of the oil-depleted state has an important influence on the triboelectric process. Based on the relationship between the two, the state of the lubricating oil can be reflected in real time by using the triboelectric signal, which provides a reliable method for the real-time monitoring of the lubrication state.

Field-view model for triboelectric nanogenerator motion superposition analysis

The precise value of the triboelectric nanogenerators’ (TENGs) energy output is hard to predict under coupled three-dimensional spatial motions in practical situations. In addition, motion monitoring based on TENGs in engineering applications requires in-depth support from basic theories. Herein, we introduce the applied field-view motion superposition output model (MSOM) of TENGs to address these challenges. Firstly, a comprehensive model for the field portrait and output prediction of the TENG with spatial motions based on basic physical and electrical theory is established through superposed motion decoupling. Secondly, a triboelectric signal spectrum model is provided to reveal the mechanisms of the TENG’s self-powered spatial motion frequency monitoring. The model validation experiments indicate a high degree of uniformity in practical measurements of the proposed MSOM model predictions. Likewise, the spectrum analysis of the TENG’s signals is verified to be an effective method for frequency monitoring and confirms a reliable observing error, which is less than 1.8%. When the TENG is equipped with three-dimensional motion traits, the MSOM model dramatically expands its physical theories for output prediction, conversion efficiency calculation, and motion monitoring.

Monitoring Lubrication and Wear in-situ by triboelectrification Under Vacuum Conditions

Maintaining the condition of the friction pair is an important measure to reduce mechanical failure. This paper integrates a vacuum elastohydrodynamic oil film measurement device and a current amplifier to simultaneously observe the optical interference image, friction coefficient and triboelectric signal during the friction process. In a high vacuum environment, the discharge phenomenon of steel balls corresponds to the time when the friction pair wears. Changes in the friction state in high vacuum environments have a significant impact on triboelectricity. Based on the relationship between the two, a sensor for real-time monitoring of the friction and wear status of the friction pair is designed, which provides a reliable real-time monitoring method for friction pair monitoring in vacuum machinery.

A high-performance triboelectric nanogenerator with dual nanostructure for remote control of switching circuit.

Preparing nanostructured surfaces has been considered an effective method to improve the output of triboelectric nanogenerators (TENGs), but how to quickly prepare materials with a nanostructured surface for TENGs has always been a challenge. Here, polypropylene nanowires and electrospun nylon 11 nanofibers were successfully prepared through a simple and time-saving method with a high success rate. Compared with a flat TENG, the output performance of a dual nanostructured TENG is enhanced by more than 5 times. After 1H,1H,2H,2H-perfluorooctyl trichlorosilane was assembled on the surface of the polypropylene film, the dual nanostructured TENG achieved the maximum output with the short-circuit current, output voltage, and charge density of 63.3 μA, 1135 V and 161.5 μC m-2, respectively. Compared with a planar structured TENG, the short-circuit current and output voltage were enhanced by about 18 times, and the charge density was increased by about 36 times. In addition, the TENG showed good working stability with almost no decrease in output after continuous operation for 193 000 cycles. The electricity generated by this TENG can successfully light up 1280 LEDs and continuously power a multi-functional electronic watch. Finally, the triboelectric signal generated by this TENG was used to control an optocoupler switch, indicating good application prospects in a remote control switching circuit.

Self-powered slippery surface with photo-enhanced triboelectric signal for waterproof wearable sensor

Self-powered triboelectric nanogenerator (TENG) sensors have gained significant attention in recent years due to their ability to directly convert external stimuli into electrical signals. However, most triboelectric sensors are sensitive to humidity or liquid environments, with restricted working conditions, making it challenging to meet the accuracy of detection in complex practical environments. Inspired by natural nepenthes, to address this challenge, it is essential to design the triboelectric material with excellent anti-humidity and liquid repellence. In this study, we integrate a heterogeneous layered slippery surface (HLSS) into a photo-assisted TENG sensor, consisting of the energy-level matched ZnO, MoS2, and rGO. Based on photosensitive ZnO, the fabricated triboelectric sensor significantly improves the sensitivity of the TENG sensor under light. Further, due to superior liquid repellence and mechanical strength, HLSSs exhibit a stable photo-responsive electrical signal underwater or at low temperatures and high humidity (−20 °C, 95 RH%). In addition, by connecting LEDs to form a visualization system, the triboelectric sensor can visually distinguish external stimuli, even underwater. This work presents a promising slippery interface material with synergistic responses, offering great potential for use in self-powered sensors and visualization systems.

Ultra-Broadband Flexible Thin-Film Sensor for Sound Monitoring and Ultrasonic Diagnosis.

Small-scale and flexible acoustic probes are more desirable for exquisite objects like human bodies and complex-shaped components than conventional rigid ones. Herein, a thin-film flexible acoustic sensor (FA-TES) that can detect ultra-broadband acoustic signals in multiple applications is proposed. The device consists of two thin copper-coated polyvinyl chloride films, which are stimulated by acoustic waves and contact each other to generate the triboelectric signal. Interlocking nanocolumn arrays fabricated on the friction surfaces are regarded as a highly adaptive spacer enabling this device to respond to ultra-broadband acoustic signals (100Hz-4MHz) and enhance sensor sensitivity for film weak vibration. Benefiting from the characteristics of high shape adaptability and ultrawide response range, the FA-TES can precisely sense human physiological sounds and voice (≤10kHz) for laryngeal health monitoring and interaction in real-time. Moreover, the FA-TES flexibly arranged on a 3D-printed vertebra model can effectively and accurately diagnose the inner defect by ultrasonic testing (≥1MHz). It envisions that this work can provide new ideas for flexible acoustic sensor designs and optimize real-time acoustic detections of human bodies and complex components.

Harnessing highly efficient triboelectric sensors and machine learning for self-powered intelligent security applications

In the contemporary epoch, distinguished by a transition from the internet-of-things (IoT) to the artificial intelligence of things (AIoT), individual electronic appliances necessitate inherent power-generation, independence from internet connectivity, and an imbued degree of intellect. Devices governed by pressure or strain sensors particularly demand such attributes. Responding to this technological imperative, our study endeavored to conceive an intelligent door security apparatus grounded on the universally adopted numerical input system. Despite the commercialization of identification systems such as fingerprint, iris, or facial recognition, these mechanisms suffer from susceptibility to a variety of functional aberrations. Consequently, our investigation concentrated on a security system predicated on numerical input. This necessitated the formulation of a swift, self-powered pressure sensor characterized by sensitivity to minute pressure changes. As such, we engineered a triboelectric pressure sensor incorporating a composite of Ti3C2-based MXene and polydimethylsiloxane (PDMS) as the electronegative stratum, and Nylon functioning as the electropositive layer. Addressing the sensor's intrinsic deficiency in sensitivity to pressure, we augmented the MXene-PDMS composite's surface with an out-of-plane wavy structure, and utilized a Nylon stratum composed of nanofibers, thereby amplifying the contact area under pressurized conditions. This meticulously developed sensor displayed a sensitivity metric of 0.604 kPa−1 at 15 kPa, and notably, the swiftest response times recorded amongst triboelectric pressure sensors to date. Post attachment of the sensor to a numeric keypad (ranging from 0 to 9), we meticulously measured the signal alterations contingent on each key press, resulting in a comprehensive dataset. Employing a multitude of machine learning algorithms, we realized an exemplary degree of precision in both training and testing phases. The pragmatic implications of this work are noteworthy. Not only does our technology facilitate the unlocking of a door by entering the correct numerical code, but it is capable of recognizing distinct triboelectric signal patterns, corresponding to the specific manner of key entry by an authorized user, offering an additional dimension of security.

(Invited) advantageous Utilization of Triboelectricity Based Electric Signals for Energy Harvesting and Self-Powered Sensing

Triboelectric signal generation, which is originated from sequential contact and separation of two different materials including liquid, is highlighted as a novel mechanism for development of various types of energy harvesters as well as self-powered sensors. Unlike most of the regarding research as materials and chemistry oriented approaches, the role of the classical mechanics in aforementioned triboelectric signal generation is introduced. By adopting the ordinary power transmission unit into the triboelectricity based energy harvester, called triboelectric nanogenerator (TENG), the output performance can be significantly increased and such remarkable increase allows us to use the triboelectric signal generation mechanism more practically. As one of the representative examples, the effective biomechanical energy harvesting via triboelectric signal generation is introduced. Along with it, the advantageous effect of the triboelectric signal generation on the operation of the classical mechanical elements, which are frequently employed for direct power transmission, is proposed. In this regard, the self-triggered mechanical sensors, which enable us to inform various characteristics of the machine components, are proposed. Since the electric signal can be generated without any other external power sources, the present sensor can be considered as self-triggered. Gear and brake are one of the most ordinary and effective components for transmitting mechanical power as a core component of machines. Given that the operation of the gear and brake in power transmission is based on sequential contact and separation between two separated components, the simple modification of the outermost surface of the conventional machine components enables us to spontaneously generate triboelectric signal during ordinary power transmission. The present approach to utilize state-of-the-art triboelectric signal generating mechanism could open new application fields by converging it with the classical mechanics.

Scalable micropatterned epoxy vitrimer films by thermo-triggered bond exchange for repairable and recyclable triboelectric nanogenerators

Triboelectric nanogenerators are believed to be a promising solution to energy crisis by mechanical-to-electrical energy conversion through the contact electrification between constituent tribo-materials. However, most of the current tribo-materials are difficult to be repaired if damaged, and recycled for their reuse or disposal, limiting the development for reusable and sustainable energy-harvesting devices. Therefore, we explore the development of durable, repairable and recyclable triboelectric nanogenerators based on an epoxy-derived vitrimer (EV) with thermo-reversible cross-linked networks. Rather than polymerizing the EVs by adding thermoplastic components, they are generated by a solvent-free, quasi-thermoforming and scalable process. Thanks to the flowability of cross-linked networks realized by thermo-triggered hydroxyl/ester bond-exchange reactions, surface-micropatterned EV film based tribo-materials are successfully fabricated by a thermal micro-imprinting process, showing 3D shape-adaptive thermoforming ability. The EV films exhibit excellent flexibility and ductility with the smaller elastic hysteresis under external deformations, whose molecular origin is revealed to be the achievable macromolecular segment relaxation and energy dissipation of networks. The favorable mechanical robustness and recoverability endow the EV-based nanogenerators (EV-TENG) with significantly durable electricity-generating performances under repeated compressions (≥10,000 cycles) and larger mechanical loads. More importantly, by taking the triboelectric signal as a probe for network evolution, repairability and recyclability of EV-TENGs are further evaluated quantitively. Interestingly, the introduction of EVs makes the device self-repairable simply by heating treatment with a higher healing efficiency of 98%. Moreover, the device could be recycled by both physical and chemical approaches, without losing the original triboelectric performance and structural integrity. Our results demonstrate the potential applications of vitrimers derived from industrial raw materials in developing repairable, recyclable and scalable energy-harvesting electronics with prolonged lifetimes and environmental sustainability.

Smart conveyor roller system for self-powered product size identification in electrically off-grid condition via hybridization of triboelectric-electromagnetic generators

With the advent of Industry 4.0, the automation and digitalization of product transportation in factories have attracted much attention. In this paper, a fully stand-alone smart conveyor system based on the integration of triboelectric sensor (TES) and electromagnetic generator (EMG) for self-powered real-time monitoring and identification, called an IoTE conveyor system (Integration of TES and EMG assisted conveyor system), is proposed. In this system, the roller acts as the TES by simply modifying its surface. The roller with TES can generate the triboelectric signal, which contains relevant information about the transported product such as material, size, and movement speed. The generated triboelectric signal is collected, analyzed, and transmitted to the user device by the MCU, which includes a Bluetooth module. The EMG and mechanical power transmission elements are designed to harvest the rotational kinetic energy of the roller and supply the electric power required to operate the MCU. The product information is wirelessly transmitted to the smartphone of users by the Bluetooth module and is visually displayed in real-time. The potential of the proposed IoTE conveyor system in sensing, analyzing, and transmitting product information without the need for additional electric power supply is expected to serve as a cornerstone for the manufacturing industry to realize the development of net-zero smart factories.

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.

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.

Influence of interface liquid lubrication on triboelectrification of point contact friction pair

Triboelectrification typically occurs in the friction process. In this study, we investigated the effect of liquid lubricants of various polarities on triboelectrification in a friction pair consisting of a steel ball and polyvinylidene fluoride blocks. The results revealed that alkanes and alkenes enhanced triboelectrification. On addition of PAO 4, the friction coefficient reduced considerably, and the short-circuit current could be output stably for a long time. With the increase in the viscosity of PAO, the triboelectric signal gradually decreased. This study revealed that the appropriate lubricant and the quantity of liquid can increase the size of the triboelectric signal to achieve a stable output for a long time.

Toward Enhanced Humidity Stability of Triboelectric Mechanical Sensors via Atomic Layer Deposition.

Humid conditions can disrupt the triboelectric signal generation and reduce the accuracy of triboelectric mechanical sensors. This study demonstrates a novel design approach using atomic layer deposition (ALD) to enhance the humidity resistance of triboelectric mechanical sensors. Titanium oxide (TiOx) was deposited on polytetrafluoroethylene (PTFE) film as a moisture passivation layer. To determine the effective ALD process cycle, the TiOx layer was deposited with 100 to 2000 process cycles. The triboelectric behavior and surface chemical bonding states were analyzed before and after moisture exposure. The ALD-TiOx-deposited PTFE showed three times greater humidity stability than pristine PTFE film. Based on the characterization of TiOx on PTFE film, the passivation mechanism was proposed, and it was related to the role of the oxygen-deficient sites in the TiOx layer. This study could provide a novel way to design stable triboelectric mechanical sensors in highly humid environments.

Patch-Type Vibration Visualization (PVV) Sensor System Based on Triboelectric Effect.

Self-powered wireless sensor systems have emerged as an important topic for condition monitoring in nuclear power plants. However, commercial wireless sensor systems still cannot be fully self-sustainable due to the high power consumption caused by excessive signal processing in a mini-electronic computing system. In this sense, it is essential not only to integrate the sensor system with energy-harvesting devices but also to develop simple data processing methods for low power schemes. In this paper, we report a patch-type vibration visualization (PVV) sensor system based on the triboelectric effect and a visualization technique for self-sustainable operation. The PVV sensor system composed of a polyethylene terephthalate (PET)/Al/LCD screen directly converts the triboelectric signal into an informative black pattern on the LCD screen without excessive signal processing, enabling extremely low power operation. In addition, a proposed image processing method reconverts the black patterns to frequency and acceleration values through a remote-control camera. With these simple signal-to-pattern conversion and pattern-to-data reconversion techniques, a vibration visualization sensor network has successfully been demonstrated.