Mechanoluminescent-Triboelectric Bimodal Sensors for Self-Powered Sensing and Intelligent Control

Self-powered flexible devices with skin-like multiple sensing ability have attracted great attentions due to their broad applications in the Internet of Things(IoT).Various methods have been proposed to enhance mechano-optic or electric performance of the flexible devices;however,it remains challenging to realize the display and accurate recognition of motion trajectories for intelligent control.Here,we present a fully self-powered mechanoluminescent-triboelectric bimodal sensor based on micronanostructured mechanoluminescent elastomer,which can patterned-display the force trajectories.The deformable liquid metals used as stretchable electrode make the stress transfer stable through overall device to achieve outstanding mechanoluminescence(with a gray value of 107 under a stimulus force as low as 0.3 N and more than 2000 cycles reproducibility).Moreover,a microstructured surface is constructed which endows the resulted composite with significantly improved triboelectric performances(voltage increases from 8 to 24 V).Based on the excellent bimodal sensing performances and durability of the obtained composite,a highly reliable intelligent control system by machine learning has been developed for controlling trolley,providing an approach for advanced visual interaction devices and smart wearable electronics in the future IoT era.

Wireless Self-Powered Vibration Sensor System for Intelligent Spindle Monitoring

In recent years,high-end equipment is widely used in industry and the accuracy requirements of the equipment have been risen year by year.During the machining process,the high-end equipment failure may have a great impact on the product quality.It is necessary to monitor the status of equipment and to predict fault diagnosis.At present,most of the condition monitoring devices for mechanical equipment have problems of large size,low precision and low energy utilization.A wireless self-powered intelligent spindle vibration acceleration sensor system based on piezoelectric energy harvesting is proposed.Based on rotor sensing technology,a sensor is made to mount on the tool holder and build the related circuit.Firstly,the energy management module collects the mechanical energy in the environment and converts the piezoelectric vibration energy into electric energy to provide 3.3 Vfor the subsequent circuit.The lithium battery supplies the system with additional power and monitors’the power of the energy storage circuit in real-time.Secondly,a three-axis acceleration sensor is used to collect,analyze and filter a series of signal processing operations of the vibration signal in the environment.The signal is sent to the upper computer by wireless transmission.The host computer outputs the corresponding X,Y,and Z channel waveforms and data under the condition of the spindle speed of 50∼2500 r/min with real-time monitoring.The KEIL5 platform is used to develop the system software.The small-size piezoelectric vibration sensor with high-speed,high-energy utilization,high accuracy,and easy installation is used for spindle monitoring.The experiment results show that the sensor system is available and practical.

Epidermal self-powered sweat sensors for glucose and lactate monitoring

Sweat could be a carrier of informative biomarkers for health status identification;therefore,wearable sweat sensors have attracted significant attention for research.An external power source is an important component of wearable sensors,however,the current power supplies,i.e.,batteries,limit further shrinking down the size of these devices and thus limit their application areas and scenarios.Herein,we report a stretchable self-powered biosensor with epidermal electronic format that enables the in situ detec-tion of lactate and glucose concentration in sweat.Enzymatic biofuel cells serve as self-powered sensing modules allowing the sweat sensor to exhibit a determination coefficient(R2)of 0.98 with a sensitivity of 2.48 mV/mM for lactate detection,and R2 of 0.96 with a sensitivity of 0.11 mV/μM for glucose detection.The microfluidic channels developed in an ultra-thin soft flexible polydimethylsiloxane layer not only enable the effective collection of sweat,but also provide excellent mechanical properties with stable performance output even under 30%stretching.The presented soft sweat sensors can be integrated at nearly any location of the body for the continuous monitoring of lactate and glucose changes during normal daily activities such as exercise.Our results provide a promising approach to develop next-generation sweat sensors for real-time and in situ sweat analysis.

Electrospinning of Flexible Poly(vinyl alcohol)/MXene Nanofiber-Based Humidity Sensor Self-Powered by Monolayer Molybdenum Diselenide Piezoelectric Nanogenerator

Two-dimensional material has been widely investigated for potential applications in sensor and flexible electronics.In this work,a self-powered flexible humidity sensing device based on poly(vinyl alcohol)/Ti_(3)C_(2)Tx(PVA/MXene)nanofibers film and monolayer molybdenum diselenide(MoSe2)piezoelectric nanogenerator(PENG)was reported for the first time.The monolayer MoSe_(2)-based PENG was fabricated by atmospheric pressure chemical vapor deposition techniques,which can generate a peak output of 35 mV and a power density of42 mW m^(-2).The flexible PENG integrated on polyethylene terephthalate(PET)substrate can harvest energy generated by different parts of human body and exhibit great application prospects in wearable devices.The electrospinned PVA/MXene nanofiber-based humidity sensor with flexible PET substrate under the driven of monolayer MoSe_(2) PENG,shows high response of~40,fast response/recovery time of 0.9/6.3 s,low hysteresis of 1.8%and excellent repeatability.The self-powered flexible humidity sensor yields the capability of detecting human skin moisture and ambient humidity.This work provides a pathway to explore the high-performance humidity sensor integrated with PENG for the self-powered flexible electronic devices.

AUV-Aided Data Collection Considering Adaptive Ocean Currents for Underwater Wireless Sensor Networks

Autonomous underwater vehicle(AUV)-assisted data collection is an efficient approach to implementing smart ocean.However,the data collection in time-varying ocean currents is plagued by two critical issues:AUV yaw and sensor node movement.We propose an adaptive AUV-assisted data collection strategy for ocean currents to address these issues.First,we consider the energy consumption of an AUV in conjunction with the value of information(VoI)over the sensor nodes and formulate an optimization problem to maximize the VoI-energy ratio.The AUV yaw problem is then solved by deriving the AUV's reachable region in different ocean current environments and the optimal cruising direction to the target nodes.Finally,using the predicted VoI-energy ratio,we sequentially design a distributed path planning algorithm to select the next target node for AUV.The simulation results indicate that the proposed strategy can utilize ocean currents to aid AUV navigation,thereby reducing the AUV's energy consumption and ensuring timely data collection.

An intelligent self-powered life jacket system integrating multiple triboelectric fiber sensors for drowning rescue

The inherent unpredictability of the maritime environment leads to low rates of survival during accidents.Life jackets serve as a crucial safety measure in underwater environments.Nonetheless,most conventional life jackets lack the capability to monitor the wearer's underwater body movements,impeding their effectiveness in rescue operations.Here,we present an intelligent self-powered life jacket system(SPLJ)composed of a wireless body area sensing network,a set of deep learning analytics,and a human condition detection platform.Six coaxial core-shell structure triboelectric fiber sensors with high sensitivity,stretchability,and flexibility are integrated into this system.Addi-tionally,a portable integrated circuit module is incorporated into the SPLJ to facilitate real-time monitoring of the wearer's movement.Moreover,by leveraging the deep-learning-assisted data analytics and establishing a robust correlation between the wearer's movements and condition,we have developed a comprehensive system for monitoring drowning individuals,achieving an outstanding recognition accuracy of 100%.This groundbreaking work intro-duces a fresh approach to underwater intelligent survival devices,offering promising prospects for advancing underwater smart wearable devices in rescue operations and the development of ocean industry.

Self-Healing All-in-One Energy Storage for Flexible Self-Powering Ammonia Smartsensors

Self-healable and flexible all-in-one self-powering smartsensing devices have recently attracted great attention.Herein,a flexible all-in-one solid-state electronic system of polyvinyl alcohol(PVA)hydrogel-based supercapacitors for self-powering ammonia smartsensors has been fabricated.Self-healing supercapacitors are prepared by integrating polypyrrole(PPy)and boron crosslinked PVA/KCl hydrogel as a sandwich configuration,exhibiting large specific capacitance of 244.81 mF cm^(-2)at 0.47 mA cm^(-2),and good charging/discharging stability of 2000 cycles,while ammonia sensors are realized by a SnO_(2)/PPy-modified conductive PVA hydrogel film,demonstrating an excellent sensing behavior toward NH_(3) vapor under 50 ppb–500 ppm.As a result,selfhealing supercapacitors could well store energy and then self-power sensing unit for remotely real-time detection via a smartphone,acquiring high flexibility of energy-sensing system.With attractive biocompatibility and selfhealing performance toward various environment,this all-in-one flexible energy-smartsensor system would pave the way to novel fabrication process in realization of wearable self-healing smart devices.

Self-powered sensor based on compressible ionic gel electrolyte for simultaneous determination of temperature and pressure

The simultaneous detection of multiple stimuli,such as pressure and temperature,has long been a persistent challenge for developing electronic skin(eskin)to emulate the functionality of human skin.Meanwhile,the demand for integrated power supply units is an additional pressing concern to achieve its lightweightness and flexibility.Herein,we propose a self-powered dual temperature–pressure(SPDM)sensor,which utilizes a compressible ionic gel electrolyte driven by the potential difference between MXene and Al electrodes.The SPDM sensor exhibits a rapid and timely response to changes in pressure-induced deformation,while exhibiting a slow and hysteretic response to temperature variations.These distinct response characteristics enable the differentiation of current signals generated by different stimuli through machine learning,resulting in an impressive accuracy rate of 99.1%.Furthermore,the developed SPDM sensor exhibits a wide pressure detection range of 0–800 kPa and a broad temperature detection range of 5–75C,encompassing the environmental conditions encountered in daily human life.The dual-mode coupled strategy by machine learning provides an effective approach for temperature and pressure detection and discrimination,showcasing its potential applications in wearable electronics,intelligent robots,human–machine interactions,and so on.

Three-Dimensional Ocean Sensor Networks:A Survey

The past decade has seen a growing interest in ocean sensor networks because of their wide applications in marine research,oceanography,ocean monitoring,offshore exploration,and defense or homeland security.Ocean sensor networks are generally formed with various ocean sensors,autonomous underwater vehicles,surface stations,and research vessels.To make ocean sensor network applications viable,efficient communication among all devices and components is crucial.Due to the unique characteristics of underwater acoustic channels and the complex deployment environment in three dimensional(3D) ocean spaces,new efficient and reliable communication and networking protocols are needed in design of ocean sensor networks.In this paper,we aim to provide an overview of the most recent advances in network design principles for 3D ocean sensor networks,with focuses on deployment,localization,topology design,and position-based routing in 3D ocean spaces.

A Self‑Powered,Highly Embedded and Sensitive Tribo‑Label‑Sensor for the Fast and Stable Label Printer

Label-sensor is an essential component of the label printer which is becoming a most significant tool for the development of Internet of Things(IoT).However,some drawbacks of the traditional infrared label-sensor make the printer fail to realize the high-speed recognition of labels as well as stable printing.Herein,we propose a selfpowered and highly sensitive tribo-label-sensor(TLS)for accurate label identification,positioning and counting by embedding triboelectric nanogenerator into the indispensable roller structure of a label printer.The sensing mechanism,device parameters and deep comparison with infrared sensor are systematically studied both in theory and experiment.As the results,TLS delivers 6 times higher signal magnitude than traditional one.Moreover,TLS is immune to label jitter and temperature variation during fast printing and can also be used for transparent label directly and shows long-term robustness.This work may provide an alternative toolkit with outstanding advantages to improve current label printer and further promote the development of IoT.

Organic bulk heterojunction enabled with nanocapsules of hydrate vanadium pentaoxide layer for high responsivity self-powered photodetector

This article demonstrates the fabrication of organic-based devices using a low-cost solution-processable technique.A blended heterojunction of chlorine substituted 2D-conjugated polymer PBDB-T-2Cl,and PC71BM supported nanocapsules hy-drate vanadium penta oxides(HVO)as hole transport layer(HTL)based photodetector fabricated on an ITO coated glass sub-strate under ambient condition.The device forms an excellent organic junction diode with a good rectification ratio of~200.The device has also shown excellent photodetection properties under photoconductive mode(at reverse bias)and zero bias for green light wavelength.A very high responsivity of~6500 mA/W and high external quantum efficiency(EQE)of 1400%have been reported in the article.The proposed organic photodetector exhibits an excellent response and recovery time of~30 and~40 ms,respectively.

Progress in self-powered sensors—Moving toward artificial intelligent and neuromorphic system

Wearable and flexible electronics are shaping our life with their unique advantages of light weight,good compliance,and desirable comfortability.With marching into the era of Internet of Things(IoT),numerous sensor nodes are distributed throughout networks to capture,process,and transmit diverse sensory information,which gives rise to the demand on self-powered sensors to reduce the power consumption.Meanwhile,the rapid development of artificial intelligence(AI)and fifth-generation(5G)technologies provides an opportunity to enable smart-decision making and instantaneous data transmission in IoT systems.Due to continuously increased sensor and dataset number,conventional computing based on von Neumann architecture cannot meet the needs of brain-like high-efficient sensing and computing applications anymore.Neuromorphic electronics,drawing inspiration from the human brain,provide an alternative approach for efficient and low-power-consumption information processing.Hence,this review presents the general technology roadmap of self-powered sensors with detail discussion on their diversified applications in healthcare,human machine interactions,smart homes,etc.Via leveraging AI and virtual reality/augmented reality(VR/AR)techniques,the development of single sensors to intelligent integrated systems is reviewed in terms of step-by-step system integration and algorithm improvement.In order to realize efficient sensing and computing,brain-inspired neuromorphic electronics are next briefly discussed.Last,it concludes and highlights both challenges and opportunities from the aspects of materials,minimization,integration,multimodal information fusion,and artificial sensory system.

Study on the influence of the subsurface buoy＇s vibration on the vector sensor due to ocean current

Subsurface buoy systems,especially equipped with the vector sensor,have more and more extensive applications in military and civilian regions.However,their acoustic performances are constrained by the vibration resulting from the unavoidable ocean current in some degree.The influence of such vibrations is quantitatively analyzed by means of modeling the simplified models of two deployment configurations involving the positive buoyant buoy and neutral buoy system.The corresponding formulas are deduced respectively for the deployment configuration buoy systems in the motion state firstly.Then the simulation software is developed and some numerical simulations are put up via the Runge-Kutta method.The simulation results and theoretical analysis indicate that the neutral buoy will be an excellent design protocol in engineering application in comparison with the positive buoyant buoy.

我国海洋观测装备“卡脖子”问题的破解对策建议

该文中“卡脖子”问题是指我国海洋观测装备在发展过程中遇到的瓶颈和限制,阻碍了海洋科学研究和海洋资源利用。该文对我国海洋观测装备的发展进行需求分析,从海洋观测平台和海洋传感器的发展两个方面介绍我国海洋观测装备发展的现状;从创新能力、成果转化能力、国产化应用、技术标准和测试试验等方面分析“卡脖子”问题出现的原因,针对这些问题提出加强海洋仪器设备应用的调研和评估、提升设备的精准度和可靠性、进行海洋仪器设备攻关加快研发和推广、完善海洋标准和试验测试体系等一系列措施建议。有助于提高我国海洋观测装备的整体技术水平,促进海洋科技的进步,推动我国在海洋观测领域的可持续发展。

Triboelectric gait sensing analysis system for self-powered IoT-based human motion monitoring

Quantitative analysis of gait parameters,such as stride frequency and step speed,is essential for optimizing physical exercise for the human body.However,the current electronic sensors used in human motion monitoring remain constrained by factors such as battery life and accuracy.This study developed a self-powered gait analysis system(SGAS)based on a triboelectric nanogenerator(TENG)fabricated electrospun composite nanofibers for motion monitoring and gait analysis for regulating exercise programs.The SGAS consists of a sensing module,a charging module,a data acquisition and processing module,and an Internet of Things(IoT)platform.Within the sensing module,two specialized sensing units,TENG-S1 and TENG-S2,are positioned at the forefoot and heel to generate synchronized signals in tandem with the user's footsteps.These signals are instrumental for real-time step count and step speed monitoring.The output of the two TENG units is significantly improved by systematically investigating and optimizing the electrospun composite nanofibers'composition,strength,and wear resistance.Additionally,a charge amplifier circuit is implemented to process the raw voltage signal,consequently bolstering the reliability of the sensing signal.This refined data is then ready for further reading and calculation by the micro-controller unit(MCU)during the signal transmission process.Finally,the well-conditioned signals are wirelessly transmitted to the IoT platform for data analysis,storage,and visualization,enhancing human motion monitoring.

船载微型Ga-In共晶固定点的现场复现方法研究

将温标固定点技术应用于船载现场是实现温度量值扁平化,提升海洋温度测量水平的重要手段。为了弥补ITS90温标在海洋温区(-5~35℃)范围内固定点数目不足,不能对NTC热敏电阻进行有效校准的缺陷,研制了微型Ga-In共晶固定点,开展了船载控温箱微型Ga-In固定点温坪复现研究,同时探索了环境温度条件下微型Ga-In共晶固定点的复现。采用切线交点法和三次多项式拟合法对微型Ga-In固定点进行了评估和分析。结果表明:微型Ga-In共晶固定点重复性优于1 mK;微型Ga-In共晶固定点应该在固态并低于熔点的环境下保存。采用切线交点法赋值得到微型Ga-In共晶固定点相变温度为15.6549℃,扩展不确定度为1.54 mK(k=2)。

A triboelectric nanogenerator-based self-powered long-distance wireless sensing platform for industries and environment monitoring

Self-powered wireless sensing system is particularly suitable for applications in intelligent manufacturing, smart healthcare etc. as it does not require an external power source. Triboelectric nanogenerator (TENG) is an emerging energy harvester that can be used to power self-powered wireless sensors. The latest achievement in this area is the instantaneous self-powered wireless sensor, where the electric energy generated by the TENG is injected directly into the inductor-capacitor (LC) resonator to generate a decaying oscillating signal with encoded sensing information. However, the frequency is lower (typically 【5 MHz) and the signal transmission distance is short (【3 m) limited by the near-field magnetic coupling, restricting its widespread applications. In this research, we propose a self-powered long-distance wireless sensing platform which utilizes a surface acoustic wave (SAW) resonator based radio-frequency oscillator to convert TENG energy into a high frequency signal with sensing information encoded. With this system, the sensing signal can be easily transmitted through the antenna for long distance. An optimized system is designed and conditional influences are fully investigated. Results show this self-powered wireless sensor system can perform wireless sensing for force, temperature and vibration at a distance up to 50 m.

Compliant Iontronic Triboelectric Gels with Phase-Locked Structure Enabled by Competitive Hydrogen Bonding

Rapid advancements in flexible electronics technology propel soft tactile sensing devices toward high-level biointegration,even attaining tactile perception capabilities surpassing human skin.However,the inherent mechanical mismatch resulting from deficient biomimetic mechanical properties of sensing materials poses a challenge to the application of wearable tactile sensing devices in human-machine interaction.Inspired by the innate biphasic structure of human subcutaneous tissue,this study discloses a skin-compliant wearable iontronic triboelectric gel via phase separation induced by competitive hydrogen bonding.Solvent-nonsolvent interactions are used to construct competitive hydrogen bonding systems to trigger phase separation,and the resulting soft-hard alternating phase-locked structure confers the iontronic triboelectric gel with Young’s modulus(6.8-281.9 kPa)and high tensile properties(880%)compatible with human skin.The abundance of reactive hydroxyl groups gives the gel excellent tribopositive and self-adhesive properties(peel strength>70 N m^(−1)).The self-powered tactile sensing skin based on this gel maintains favorable interface and mechanical stability with the working object,which greatly ensures the high fidelity and reliability of soft tactile sensing signals.This strategy,enabling skin-compliant design and broad dynamic tunability of the mechanical properties of sensing materials,presents a universal platform for broad applications from soft robots to wearable electronics.

Advances in Graphene‑Based Electrode for Triboelectric Nanogenerator

With the continuous development of wearable electronics,wireless sensor networks and other micro-electronic devices,there is an increasingly urgent need for miniature,flexible and efficient nanopower generation technology.Triboelectric nanogenerator(TENG)technology can convert small mechanical energy into electricity,which is expected to address this problem.As the core component of TENG,the choice of electrode materials significantly affects its performance.Traditional metal electrode materials often suffer from problems such as durability,which limits the further application of TENG.Graphene,as a novel electrode material,shows excellent prospects for application in TENG owing to its unique structure and excellent electrical properties.This review systematically summarizes the recent research progress and application prospects of TENGs based on graphene electrodes.Various precision processing methods of graphene electrodes are introduced,and the applications of graphene electrode-based TENGs in various scenarios as well as the enhancement of graphene electrodes for TENG performance are discussed.In addition,the future development of graphene electrode-based TENGs is also prospectively discussed,aiming to promote the continuous advancement of graphene electrode-based TENGs.

Rational design of natural leather-based water evaporator for electricity generation and functional applications

In recent years,water evaporation-induced electricity has attracted a great deal of attention as an emerging green and renewable energy harvesting technology.Although abundant materials have been developed to fabricate hydrovoltaic devices,the limitations of high costs,inconvenient storage and transport,low environmental benefits,and unadaptable shape have restricted their wide applications.Here,an electricity generator driven by water evaporation has been engineered based on natural biomass leather with inherent properties of good moisture permeability,excellent wettability,physicochemical stability,flexibility,and biocompatibility.Including numerous nano/microchannels together with rich oxygen-bearing functional groups,the natural leather-based water evaporator,Leather_(Emblic-NPs-SA/CB),could continuously produce electricity even staying outside,achieving a maximum output voltage of∼3 V with six-series connection.Furthermore,the leather-based water evaporator has enormous potential for use as a flexible self-powered electronic floor and seawater demineralizer due to its sensitive pressure sensing ability as well as its excellent photothermal conversion efficiency(96.3%)and thus fast water evaporation rate(2.65 kg m^(−2)h^(−1)).This work offers a new and functional material for the construction of hydrovoltaic devices to harvest the sustained green energy from water evaporation in arbitrary ambient environments,which shows great promise in their widespread applications.