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Wind sensors have always played an irreplaceable role in environmental information monitoring and are expected to operate with lower power consumption to extend service lifetime. Here, we propose a breeze wake-up anemometer (B-WA) based on a rolling-bearing triboelectric nanogenerator (RB-TENG) with extremely low static power. The B-WA consists of two RB-TENGs, a self-waking-up module (SWM), a signal processing module (SPM), and a wireless transmission unit. The two RB-TENGs are employed for system activation and wind-speed sensing. Once the ambient wind-speed exceeds 2 m/s, the wake TENG (W-TENG) and the SWM can wake up the system within 0.96 s. At the same time, the SPM starts to calculate the signal frequency from the measured TENG (M-TENG) to monitor the wind speed with a sensitivity of 9.45 Hz/(m/s). After the wind stops, the SWM can switch off the B-WA within 0.52 s to decrease the system energy loss. In quiescent on-duty mode, the operating power of the B-WA is less than 30 nW, which can greatly extend the service lifetime of the B-WA. By integrating triboelectric devices and rolling bearings, this work has realized an ultralow quiescent power and self-waked-up wireless wind-speed monitoring system, which has foreseeable applications in remote weather monitoring, IoT nodes, and so on. [ABSTRACT FROM AUTHOR]

Highlights: A flexible tribotronic artificial synapse with bioinspired neurosensory behaviour was demonstrated, which establishes an active interaction mechanism with the environment. The device can well exhibit tuneable synaptic behaviours by changing the mechanical input modes, including excitatory postsynaptic current, paired-pulse facilitation, and the hierarchical memorial process. The device has excellent mechanical flexibility that can exhibit stable synaptic functions even under strain conditions with a bending radius of 20 mm after 1000 bending cycles. As key components of artificial afferent nervous systems, synaptic devices can mimic the physiological synaptic behaviors, which have attracted extensive attentions. Here, a flexible tribotronic artificial synapse (TAS) with bioinspired neurosensory behavior is developed. The triboelectric potential generated by the external contact electrification is used as the ion-gel-gate voltage of the organic thin film transistor, which can tune the carriers transport through the migration/accumulation of ions. The TAS successfully demonstrates a series of synaptic behaviors by external stimuli, such as excitatory postsynaptic current, paired-pulse facilitation, and the hierarchical memory process from sensory memory to short-term memory and long-term memory. Moreover, the synaptic behaviors remained stable under the strain condition with a bending radius of 20 mm, and the TAS still exhibits excellent durability after 1000 bending cycles. Finally, Pavlovian conditioning has been successfully mimicked by applying force and vibration as food and bell, respectively. This work demonstrates a bioinspired flexible artificial synapse that will help to facilitate the development of artificial afferent nervous systems, which is great significance to the practical application of artificial limbs, robotics, and bionics in future. [ABSTRACT FROM AUTHOR]

Triboelectric nanogenerators (TENGs) can directly harvest energy via solid–liquid interface contact electrification, making them very suitable for harvesting raindrop energy and as active rainfall sensors. This technology is promising for realizing a fully self-powered system for autonomous rainfall monitoring combined with energy harvesting/sensing. Here, we report a raindrop energy-powered autonomous rainfall monitoring and wireless transmission system (R-RMS), in which a raindrop-TENG (R-TENG) array simultaneously serves as a raindrop energy harvester and rainfall sensor. At a rainfall intensity of 71 mm/min, the R-TENG array can generate an average short-circuit current, open-circuit voltage, and maximum output power of 15 μA, 1800 V, and 325 μW, respectively. The collected energy can be adjusted to act as a stable 2.5 V direct-current source for the whole system by a power management circuit. Meanwhile, the R-TENG array acts as a rainfall sensor, in which the output signal can be monitored and the measured data are wirelessly transmitted. Under a rainfall intensity of 71 mm/min, the R-RMS can be continuously powered and autonomously transmit rainfall data once every 4 min. This work has paved the way for raindrop energy-powered wireless hyetometers, which have exhibited broad prospects in unattended weather monitoring, field surveys, and the Internet of Things. [ABSTRACT FROM AUTHOR]

The development of triboelectric nanogenerator (TENG) technology which can directly convert ambient mechanical energy into electric energy may affect areas from green energy harvesting to emerging wearing electronics. And, the material of triboelectric layer is critical to the mechanical robustness and electrical output characteristics of the TENGs. Herein, a MXene enhanced electret polytetrafluoroethylene (PTFE) film with a high mechanical property and surface charge density is developed. The MXene/PTFE composite film was synthesized by spraying and annealing treatment. With the doping of MXene, the crystallinity of composite film could be tuned, leading to an enhancement in the tensile property of 450% and reducing the wear volume about 80% in the friction test. Furthermore, the as-fabricated TENG with this composite film outputs 397 V of open-circuit voltage, 21 µA of short-circuit current, and 232 nC of transfer charge quantity, which are 4, 6, and 6 times higher than that of the TENG made by pure PTFE film, respectively. Therefore, this work provides a creative strategy to simultaneously improve the mechanical property and electrical performance of the TENGs, which have great potential in improving device stability under a complex mechanical environment. [ABSTRACT FROM AUTHOR]

The delegating computation has become an irreversible trend, together comes the pressing need for fairness and efficiency issues. To solve this problem, we leverage game theory to propose a smart contract-based solution. First, according to the behavioral preferences of the participants, we design an incentive contract to describe the motivation of the participants. Next, to satisfy the fairness of the rational delegating computation, we propose a rational delegating computation protocol based on reputation and smart contract. More specifically, rational participants are to gain the maximum utility and reach the Nash equilibrium in the protocol. Besides, we design a reputation mechanism with a reputation certificate, which measures the reputation from multiple dimensions. The reputation is used to assure the client's trust in the computing party to improve the efficiency of the protocol. Then, we conduct a comprehensive experiment to evaluate the proposed protocol. The simulation and analysis results show that the proposed protocol solves the complex traditional verification problem. We also conduct a feasibility study that involves implementing the contracts in Solidity and running them on the official Ethereum network. Meanwhile, we prove the fairness and correctness of the protocol. [ABSTRACT FROM AUTHOR]