Tribo-Induced Color Tuner toward Smart Lighting and Self-Powered Wireless Sensing

A Fully Self-Powered Ocean Wave Observation System Empowered by Natural Light Modulated by a Friction-Driven Polymer Network Liquid Crystal

Conventional ocean wave observation instruments are powered by batteries, limiting the continuous observation time. Besides, the waste of batteries brings environmental contaminations. Triboelectric nanogenerators (TENGs) can reveal ocean wave information through their electrical output, taking the triboelectric charge as the information carrier. However, charge amplification is necessary, consuming additional energy. Herein, taking the photons rather than electrons as the information carrier, we developed a fully self-powered natural light-enabled sensing system for ocean wave monitoring by coupling two rotary-freestanding sliding TENGs (RFS-TENGs) and a polymer network liquid crystal (PNLC)-triggered optical system. The natural light is modulated by the PNLC driven by ocean wave-induced friction. With the assistance of a one-way bearing, the rise and fall of the wave will trigger different RFS-TENGs to power the PNLC in different voltage drops, leading to different transmitted natural light intensities. The wave height information can be obtained through the number of pulse signals with the same trough light intensity, while the wave period can be obtained through the duration between the same two sets of pulse signals. The effectiveness of the developed sensing paradigm in practical applications was verified by flume-based experiments, with the highest accuracies of 90.7% in wave height and 99.8% in wave period.

Passive Internet of Events Enabled by Broadly Compatible Self-Powered Visualized Platform Toward Real-Time Surveillance

Surveillance is an intricate challenge worldwide especially in those complicated environments such as nuclear plants, banks, crowded areas, barns, etc. Deploying self-powered wireless sensor nodes can increase the system's event detection capabilities by collecting environmental changes, while the incompatibility among components (energy harvesters, sensors, and wireless modules) limits their application. Here, a broadly compatible self-powered visualized platform (SPVP) is reported to construct a passive internet of events (IoE) network for surveillance systems. By encoding electric signals into reference and working LEDs, SPVP can visualize resistance change generated by commercial resistive sensors with a broad working range (<107  Ω) and the transmission distance is up to 30 meters. Visible light signals are captured by surveillance cameras and processed by the cloud to achieve real-time event monitoring and identification, which forms the passive IoE network. It is demonstrated that the passive-IoE-based surveillance system can detect intrusion, theft, fire alarm, and distress signals quickly (30 ms) for 106 cycles. Moreover, the confidential information can be encrypted by SPVPs and accessed through a phone application. This universal scheme may have huge potential for the construction of safe and smart cities.

Fully Wireless and Self-Powered Ocean Wave Observation System Empowered by the Friction-Driven Polymer Network Liquid Crystal-Based Smart Reflector

Current ocean wave observation is achieved by separate battery-powered sensing and signal transmission modules. Owing to the limited electrical supply and information channel space, the long-time span observation is restricted and only wave height and period information rather than the whole wave profile are sent back to the receiver. In this work, a self-powered ocean wave observation system was achieved by a developed polymer network liquid crystal (PNLC)-based smart reflector powered by a tailored triboelectric nanogenerator embedded with one-way overrunning clutches. The off-shore smart reflector modulated the on-shore emitted laser light, where ocean wave motion information can be revealed from the remotely detected reflected laser light without cable connections. The ocean wave rise and fall are distinguished by the developed one-way overrunning clutch, which selects the TENG to power the PNLC. Through the developed paradigm, ocean wave sensing and signal transmission can be achieved simultaneously, which is fully self-powered and free-of-cable. The flume-based self-powered ocean observation was performed with demonstrated wave height and period sensing accuracies of 92.66 and 97.32%, respectively.

0.5 m Triboelectric Nanogenerator for Efficient Blue Energy Harvesting of All-Sea Areas

Triboelectric nanogenerators (TENGs) to harvest ocean wave blue energy is flourishing, yet the research horizon has been limited to centimeter-level TENG. Here, for the first time, a TENG shell is advanced for ocean energy harvesting to 0.5 m and an excellent frictional areal density of 1.03 cm^-1 and economies of scale are obtained. The unique structure of the multi-arch shape is adopted to untie the difficulty of fully getting the extensive friction layer contact. An inside steel plate is vertically placed in the center of every TENG block, which can activate the TENG to achieve complete contact even at a tilt angle of 7 degrees. The proposed half-meter TENG (HM-TENG) has a broad response band from 0.1 to 2 Hz, a total transferred charge quantity up to 67.2 µC, and one single TENG can deliver an open-circuit voltage of 368 V. Coupled with the self-stabilizing and susceptible features the ellipsoid shell brings, the HM-TENG can readily accommodate itself to the all-weather, all-sea wave energy harvesting. Muchmore, the HM-TENG is also applied to RF signal transmitters. This work takes the first step toward near-meter-scale enclosures and provides a new direction for large-scale wave energy harvesting.

Self-Powered Non-Contact Motion Vector Sensor for Multifunctional Human-Machine Interface

Sensors as the significant units of the Internet of Things play an important role in the field of information interaction. Non-contact sensors have the advantages of flexible manipulation and a longer lifespan but it is constrained in motion detection due to their relative single detection function. Herein, a self-powered non-contact motion vector sensor (NMVS) for the multifunctional human-machine interface is reported. Based on the electrostatic induction effect, the motion vector is measured according to the output electrical signals from the non-contact triboelectric nanogenerator (NC-TENG). By simulation analysis and experimental validation, the output characteristics of NC-TENG dependence on structural and motion parameters are investigated in detail. On this basis, the resolution of NMVS is improved and exhibits for non-contact micro-vibration monitoring, rehabilitation gait detection, contactless smart lock, and the non-contact limit alarm. This work not only proposes an ingenious strategy for non-contact motion vector detection but also demonstrates the promising prospects of a multifunctional human-machine interface in intelligent electronics, health rehabilitation, and industrial inspection.