Publications

Metal–semiconductor sliding tribovoltaic nanogenerators (MS-TVNGs) represent a promising energy harvesting technology that converts mechanical energy into direct current through dynamic Schottky junction. Although p–n junction-based TVNGs have been investigated in prior studies, metal–semiconductor configurations still lack a complete theoretical foundation. Herin, a comprehensive theoretical model is developed for MS-TVNGs, demonstrating their mechanical-to-electrical energy conversion mechanism due to tribovoltaic effect. The proposed framework unifies semiconductor and circuit principles, which elucidates that synergistic tribovoltaic-contact effects at the interface create electron–hole pairs that are swept by the built-in field to generate current unaffected by sliding direction. Additionally, theoretical results reveal that wide-bandgap semiconductors yield higher voltages, whereas increased doping and generation rates boost current, establishing clear design principles for maximizing power density. COMSOL multi-physics simulations incorporating semiconductor transport, circuit coupling, and moving mesh enable performance optimization through material selection, geometry design, and mechanical excitation. This work provides fundamental principles and practical guidelines for the development of high-efficiency tribovoltaic energy harvesting systems.

Abstract Water disinfection at the point of use (POU) has enormous social and economic significance, especially for rural areas or catastrophes. To tackle the requirements of power independence and cost control in such applications, the concept of TriboPump is proposed, which is a low‐cost, hand‐powered water disinfection system. The system consists of three functional parts: a tubular coaxial‐electrode copper ionization cell (CECIC) as the disinfection device, a disk triboelectric nanogenerator (D‐TENG) as the power source, and a coaxial mechanical structure including the water pump. The adoption of D‐TENG can make the system adaptive to varying system resistances without additional power management circuits. Moreover, the integration of CECIC and TENG can successfully turn their intrinsic limitations into advantages and a synergic effect is achieved. With the integrated design, the system can effectively disinfect the water while pumping it solely by hand power. The cost estimate of the whole system can be as low as $10 for a 2‐year service. It is believed that the whole system design provides a feasible one‐stop and cost‐efficient solution for POU water pumping and disinfection, which will ideally be suitable the rural areas or sudden‐onset catastrophes.

Abstract Water wave energy is regarded to be a promising renewable energy source to relieve the pressure of fossil energy shortage and achieve a sustainable future. A cylindrical wave‐driven linkage mechanism triboelectric nanogenerator (WLM‐TENG) with unidirectional rotation is designed and fabricated to effectively harvest water wave energy. The enormous force generated by water waves, which is up to 424.3 N m −2 , is used to drive the TENG through its simple and smart mechanical structure. This force allows the rotor to overcome the large resistance caused by the full contact between rabbit furs and electrodes. The output current can reach about 30 µA and the output power arrives at 50 mW. Moreover, self‐powered applications powered by the WLM‐TENG are successfully demonstrated, including indicating light‐emitting diodes (LEDs), multifunctional barometer, portable anemometer, and multifunctional water quality detection pen. This work renders an effective approach to harness the enormous force generated by the water waves, enhancing the water wave energy harvesting ability of the TENG, toward practical applications of marine environment monitoring.

Abstract With the advancement of intelligent and refined manufacturing, the demand for vibration sensors in smart equipment has surged. Traditional commercial vibration sensors and triboelectric nanogenerator (TENG)‐based sensors are limited to basic amplitude and frequency recognition, failing to address both self‐powering and diagnostic needs due to inherent design constraints. To overcome these limitations, this study introduces a novel mechanism combining interface dipole energy and vacuum level optimization in triboelectric materials to explain charge generation and separation under vibration. A TENG device with polydimethylsiloxane (PDMS)‐encapsulated metal electrode is designed and developed, enabling the precise recognition of equipment operating status through vibration waveform analysis. By optimizing interface contact area and electron transfer capacity, the device achieves enhanced signal clarity and the introduction of subtler characteristics in the signal waveform. Furthermore, the integration of a deep learning algorithm enables high‐resolution classification of vibration states with an accuracy of 98.3% approximately, achieving effective monitoring of the operating status of the jaw crusher and vibrating screen. This work not only verifies the feasibility of designing a self‐powered vibration sensor but also demonstrates its potential for real‐time monitoring and diagnostic applications in smart equipment.

With the challenges of monitoring marine environmental pollution, developing in-situ energy harvesting technologies for self-powered marine sensing nodes has become increasingly urgent for effective environmental protection. As an effective approach...

Quantifying the mechanical properties of nanomaterials is challenged by its small size, difficulty of manipulation, lack of reliable measurement techniques, and grossly varying measurement conditions and environment. A recently proposed approach is to estimate the elastic modulus from a force-deflection physical model based on the continuous bridged-deformation of a nanobelt/nanowire using an atomic force microscope tip under different contact forces. However, the nanobelt may have some initial bending, surface roughness and imperfect physical boundary conditions during measurement, leading to large systematic errors and uncertainty in data quantification. In this article, a statistical modeling technique, sequential profile adjustment by regression (SPAR), is proposed to account for and eliminate the various experimental errors and artifacts. SPAR can automatically detect and remove the systematic errors and therefore gives more precise estimation of the elastic modulus. This research presents an innovative approach that can potentially have a broad impact in quantitative nanomechanics and nanoelectronics.

Utilizing the coupled piezoelectric and semiconducting dual properties of ZnO, we demonstrate a piezoelectric field effect transistor (PE-FET) that is composed of a ZnO nanowire (NW) (or nanobelt) bridging across two Ohmic contacts, in which the source to drain current is controlled by the bending of the NW. A possible mechanism for the PE-FET is suggested to be associated with the carrier trapping effect and the creation of a charge depletion zone under elastic deformatioin. This PE-FET has been applied as a force/pressure sensor for measuring forces in the nanonewton range and even smaller with the use of smaller NWs. An almost linear relationship between the bending force and the conductance was found at small bending regions, demonstrating the principle of nanowire-based nanoforce and nanopressure sensors.