The ocean has an abundant reserve of wave energy, which is considered to be a clean, widely distributed and inexhaustible resource. Triboelectric nanogenerators (TENGs) have been regarded as a reliable technology for harvesting wave energy due to its robustness and efficiency in scavenging random mechanical energy. In this study, a wave energy harvesting multi-tunnel TENG (MT-TENG) has been proposed, which could be integrated easily with ocean buoys. The MT-TENG consists of polytetrafluoroethylene (PTFE) balls and a multi-tunnel frame, which could convert wave energy into electrical energy. The multi-tunnel design also avoids possible mutual obstruction of the PFTE balls during the movement. Compared with the flat type structure, the multi-tunnel structure could enhance output performance obviously. With an agitation frequency of 2 Hz and vibration amplitude of 130 mm, the MT-TENG has a peak power density of 8.3 W/m³, which is five times that of the flat type structure TENG. By integrating with a life buoy and floating pipe line, the MT-TENG could harvest wave energy to light LEDs continuously, which could provide a new solution for maritime rescue and night offshore oil delivery warning.

The human–machine interface plays an important role in the diversified interactions between humans and machines, especially by swaping information exchange between human and machine operations. Considering the high wearable compatibility and self-powered capability, triboelectric-based interfaces have attracted increasing attention. Herein, this work developed a minimalist and stable interacting patch with the function of sensing and robot controlling based on triboelectric nanogenerator. This robust and wearable patch is composed of several flexible materials, namely polytetrafluoroethylene (PTFE), nylon, hydrogels electrode, and silicone rubber substrate. A signal-processing circuit was used in this patch to convert the sensor signal into a more stable signal (the deviation within 0.1 V), which provides a more effective method for sensing and robot control in a wireless way. Thus, the device can be used to control the movement of robots in real-time and exhibits a good stable performance. A specific algorithm was used in this patch to convert the 1D serial number into a 2D coordinate system, so that the click of the finger can be converted into a sliding track, so as to achieve the trajectory generation of a robot in a wireless way. It is believed that the device-based human–machine interaction with minimalist design has great potential in applications for contact perception, 2D control, robotics, and wearable electronics.

This study presents the design and analysis of a thermal energy harvester that integrates a thermoacoustic engine (TAE) with a honeycomb-structured triboelectric nanogenerator (H-TENG), referred to as TAEH-TENG. This design is specifically developed to demonstrate the potential of thermal energy harvesting for low-power Internet of Things (IoT) applications. By leveraging the high energy conversion efficiency of TAEs and the exceptional robustness of H-TENGs, this harvester overcomes the limitations of traditional designs, which often involve complex or costly components. The experimental results revealed the oscillation characteristics of the TAEH-TENG: by utilizing a hot heat exchanger (HHE) with a length of 10 cm, the system can sustain oscillation over 150–350 °C. Furthermore, the harvester is capable of generating an open-circuit voltage of 25 V, an RMS current of 0.98 μA, and a peak power output of 0.48 mW, representing the highest power output achieved to date in comparison to previous studies. To further showcase the harvester's capability, an ultra-low-power IoT node was developed. Solely powered by the TAEH-TENG, the IoT node achieved cold-start, conducted in situ temperature measurement five times, and transmitted the data via Bluetooth within 120 s. This study not only showcases a fully self-powered IoT application but, more importantly, significantly advances the technology beyond the previous limitations faced by thermoacoustic and triboelectric integrations. By demonstrating the capability to power an ultra-low-power IoT node, this research highlights the TAEH-TENG's potential for practical, real-world energy solutions, marking a significant milestone in the deployment of heat-powered IoT applications.

In recent years, quasi-zero-stiffness (QZS) structures have been utilized in designing galloping piezoelectric energy harvesters (GPEHs) to produce large vibration responses and high output power. However, the QZS region is relatively narrow, leading to limited enhancement of QZS-GPEH at large displacement responses. To address this issue, this paper proposes a flat potential-well tuning method to design an improved QZS-GPEH (IQZS-GPEH) by significantly expanding the QZS region. First, the governing equations of the proposed IQZS-GPEH were derived, and a static analysis was conducted to compare the QZS region of the IQZS-GPEH with that of a conventional QZS-GPEH. The results reveal that the QZS property can be extended to accommodate large displacement responses, remarkably expanding the QZS region. Subsequently, the harmonic balance method was applied to derive approximate analytical solutions, and numerical simulations were performed to verify and study the dynamics and power performance of the GPEHs. Finally, wind tunnel experiments were conducted to validate the theoretical and numerical findings. The results show that the proposed method effectively enlarges the QZS region, substantially increasing dynamic responses and voltage outputs. Specifically, as the wind speed increased from 3.6 m s⁻¹ to 5.0 m s⁻¹, the power output improvement rose from 23.55% to 55.64%. Therefore, it can be concluded that broadening the QZS region is an effective approach to enhancing the performance of QZS-based galloping energy harvesters.