Publications

Air pollution becomes more and more serious with the rapid development of the society, and the haze caused by particulate matters (PMs) has become a global problem. Thus seeking an effective technology for removing the airborne PMs or other pollutants is much desirable for alleviating the air pollution. The newly invented triboelectric nanotechnology can realize efficient air filtering with obvious advantages over traditional fibrous filtering and electrostatic precipitation. Here, a review is provided for recent progress in air filter by utilizing the triboelectric nanotechnology, starting from the choices of triboelectric materials and main features of triboelectric nanotechnology. The mechanism of triboelectric air filtering technology was presented as the coupling of triboelectric filtering and mechanical filtering. Then the approaches of air filtering were summarized as the triboelectric nanogenerator (TENG)-driven air filtering, TENG-enhanced nanofiber air filtering, and self-powered triboelectric air filtering. The device structure, working principle and filtering performance were systematically discussed. Furthermore, the industry products which have been developed based on the triboelectric filtering technology were introduced.

Abstract The growing focus on health management and smart technology advancements have propelled the use of wearable sensors in healthcare and human body motion analysis, particularly in preventing work‐related upper limb musculoskeletal disorders (MSDs) through guided exercises. However, most available wearable medical sensors are rigid, bulky, and incapable of in situ recognition of the comprehensive motion of human body. Here, a conformal self‐powered inertial displacement sensor (CSIDS) with geometric optimization for in situ noninvasive inertial data acquisition is proposed. Leveraging template‐assisted processing and COMSOL simulation, the geometric configurations of tribo‐layer materials, specifically focusing on the curvature of semicylindrical protrusions is systematically altered. This enhancement significantly improves the detection accuracy of joint range of motion. The features of shoulder joint bending angles and linear accelerations of the humerus are accurately captured using a deep learning model based on multilayer perceptron (MLP) networks, resulting in an exceptional recognition accuracy of 99.38% and 99.58%. Compared to traditional TENG wearable sensors that can only identify single metrics, CSIDS achieves a more comprehensive health assessment through inertial data detection. This system provides early warning for shoulder joint diseases, prevents MSDs, and extends to smart wearables for comprehensive joint health and ergonomic monitoring.

Harvesting ambient mechanical energy is a green route in obtaining clean and sustainable electric energy. Here, we report an ultrarobust high-performance triboelectric nanogenerator (TENG) on the basis of charge replenishment by creatively introducing a rod rolling friction in the structure design. With a grating number of 30 and a free-standing gap of 0.5 mm, the fabricated TENG can deliver an output power of 250 mW/m(2) at a rotating rate of 1000 r/min. And it is capable of charging a 200 μF commercial capacitor to 120 V in 170 s, lighting up a G16 globe light as well as 16 spot lights connected in parallel. Moreover, the reported TENG holds an unprecedented robustness in harvesting rotational kinetic energy. After a continuous rotation of more than 14.4 million cycles, there is no observable electric output degradation. Given the superior output performance together with the unprecedented device robustness resulting from distinctive mechanism and novel structure design, the reported TENG renders an effective and sustainable technology for ambient mechanical energy harvesting. This work is a solid step in the development toward TENG-based self-sustained electronics and systems.

We demonstrate a mechanical−electrical trigger using a ZnO piezoelectric fine-wire (PFW) (microwire, nanowire). Once subjected to mechanical impact, a bent PFW creates a voltage drop across its width, with the tensile and compressive surfaces showing positive and negative voltages, respectively. The voltage and current created by the piezoelectric effect could trigger an external electronic system, thus, the impact force/pressure can be detected. The response time of the trigger/sensor is ∼10 ms. The piezoelectric potential across the PFW has a lifetime of ∼100 s, which is long enough for effectively "gating" the transport current along the wire; thus a piezoelectric field effect transistor is possible based on the piezotronic effect.

Abstract Tires are important parts in creating a great transportation system because they can significantly improve the overall system safety and fuel/power efficiency. The latter is especially important for the mileage of electric vehicles due to the limited electrical storage capacity. Here, green energy tires are designed by incorporating silica tread rubber with triboelectric nanogenerators (TENGs). On the one hand, the silica‐based tread compound sharply cuts off the rolling resistance, improves fuel efficiency and reduces CO 2 emissions, and provides all‐around traction without compromising braking. On the other hand, TENG converts frictional energy into electricity without changing the process of traditional tire production, which is able to be used for powering the electronics for automobile safety and automeasuring of tire pressure. The most important point lies in that TENG helps harness static electricity, which at present hinders the large‐scale application of silica‐filled green tires. Interestingly, it is also able to measure tire pressure and road condition from the changes in the output electrical signals, which thus leads to the smart applications of green energy tire in road/tire condition monitoring.

As a vastly available energy source in our daily life, acoustic vibrations are usually taken as noise pollution with little use as a power source. In this work, we have developed a triboelectrification-based thin-film nanogenerator for harvesting acoustic energy from ambient environment. Structured using a polytetrafluoroethylene thin film and a holey aluminum film electrode under carefully designed straining conditions, the nanogenerator is capable of converting acoustic energy into electric energy via triboelectric transduction. With an acoustic sensitivity of 9.54 V Pa–1 in a pressure range from 70 to 110 dB and a directivity angle of 52°, the nanogenerator produced a maximum electric power density of 60.2 mW m–2, which directly lit 17 commercial light-emitting diodes (LEDs). Furthermore, the nanogenerator can also act as a self-powered active sensor for automatically detecting the location of an acoustic source with an error less than 7 cm. In addition, an array of devices with varying resonance frequencies was employed to widen the overall bandwidth from 10 to 1700 Hz, so that the nanogenerator was used as a superior self-powered microphone for sound recording. Our approach presents an adaptable, mobile, and cost-effective technology for harvesting acoustic energy from ambient environment, with applications in infrastructure monitoring, sensor networks, military surveillance, and environmental noise reduction.