External Power Source Research Articles

Real‐Time Wireless Detection of Heavy Metal Ions Using a Self‐Powered Triboelectric Nanosensor Integrated with an Autonomous Thermoelectric Generator‐Powered Robotic System

AbstractThe integration of the Internet of Things (IoT) with advanced sensing technologies is transforming environmental monitoring and public health protection. In this study, a fully self‐powered and automated chemical sensing system is developed and integrated with a robotic hand for “touch and sense” detection of toxic heavy metal ions (Pb2⁺, Cr⁶⁺, As3⁺) in aquatic environments. The system combines a self‐powered solid‐liquid triboelectric nanosensor (SL‐TENS) with a thermoelectric generator (TEG), which harnesses ambient heat to power the robotic hand, eliminating the need for external power sources. The robotic hand is controlled wirelessly via an exo‐hand, minimizing the risk of exposure during remote monitoring. The sensing component uses copper oxide nanowires (CuO NWs) coated with ion‐selective membranes (ISMs) to enhance triboelectric output and enable highly selective ion detection. The system demonstrates effective real‐time, on‐site detection in lake water and data transmitted wirelessly to the user. This innovative approach provides a highly safe and efficient method for detecting hazardous pollutants in difficult‐to‐access areas, offering significant potential for wireless and real‐time environmental monitoring and hazard prevention, thus contributing to the safeguarding of human health. This study presents a novel advancement in the field of IoT‐enabled environmental monitoring systems.

Wireless power supply near-infrared light drug-loaded microneedle system for the treatment of linear skin wounds

The healing of linear skin wounds is a complex biological process, and traditional treatment methods have certain limitations. This study proposes a wireless power supply near-infrared light drug-loaded microneedle system (NIR-LED-NG-R1-MN), which utilizes microneedles (MNs) to achieve targeted delivery of the active component of traditional Chinese medicine, Notoginsenoside R1 (NG-R1), and combines the biological regulatory effect of near-infrared light (NIR) to achieve efficient synergistic treatment for linear skin wounds. Experimental results show that the device can significantly promote the wound closure rate and reduce the levels of inflammatory factors and the risk of scar formation. By comparing the wound repair conditions of different treatment groups, it was found that the group treated with the NIR-LED-NG-R1-MN patch for NG-R1 and NIR synergistic treatment (MN@NG-R1@LED group) showed superior wound repair effects compared to other groups, thus confirming the synergistic therapeutic advantages of NG-R1 and NIR in skin wound healing. In addition, the application of wireless power supply technology used in this system eliminates the dependence on external power sources, enhancing the convenience of treatment. This study clearly demonstrates that the NIR-LED-NG-R1-MN has the potential to become a new clinical method for the treatment of linear skin wound healing.

A passive, flexible dual-function sensor for simultaneous pressure and sliding direction detection

Flexible pressure and omnidirectional slide sensors show significant potential in wearable devices and robotics. However, the integration of various sensor types to achieve multi-functionality introduces challenges. Complex structures and processing difficulties limit their miniaturization and flexibility, while dependence on external power sources further constrains their practical use. Here, we report a novel strategy that utilizes a piezoelectric-conductive nanoresistance network with edge electrodes to develop an advanced pressure sensor. This sensor is capable of simultaneously detecting pressure and sliding direction through multiple-channel pulses. We demonstrate its functionality using a polyacrylonitrile/polypyrrole nanofiber membrane (PAN/PPY NFM) configured with either two or three electrodes. By exploiting the signal transmission characteristics of the nanoresistance network, the sensor simultaneously responds to both force and sliding direction through amplitude-frequency analysis of the output signals from multiple channels. Additionally, the sensor operates without an external power supply. This streamlined approach simplifies sensor design and processing, providing a promising solution for advanced touch sensing applications.

Model-based design of a mechanically intelligent shape-morphing structure

Soft robotics has significant interest within the industrial applications due to its advantages in flexibility and adaptability. Nevertheless, its potential is challenged by low stiffness and limited deformability, particularly in large-scale application scenarios such as underwater and offshore engineering. The integration of smart materials and morphing structures presents a promising avenue for enhancing the capabilities of soft robotic systems, especially in large deformation and variations in stiffness. In this study, we propose a multiple smart materials based mechanically intelligent structure devised through a model-based design framework. Specifically, the intelligent structure incorporates smart hydrogel and shape memory polymer (SMP). Employing the finite element method (FEM), we simulated the complex interactions among smart material to analyze the performance characteristics of the intelligent structure. The results demonstrate that, utilizing smart hydrogel and shape memory polymer (SMP) can effectively attain large deformation and exhibit variable stiffness due to the shape memory effect. Besides, the shape-morphing structures exhibit customized behaviours including bending, curling, and elongation, all while reducing reliance on external power sources. In conclusion, utilizing multiple smart materials within the model-based design framework offers an efficient approach for developing mechanically intelligent structure capable of complex deformations and variable stiffness, thereby providing support for underwater or offshore engineering applications.

Templates-Built Structural Designs for Piezoelectrochemical Pressure Sensors.

Self-powered sensors, capable of detecting static and dynamic pressure without an external power source, are pivotal for advancements in human-computer interaction, health monitoring, and artificial intelligence. Current sensing technologies, however, often fall short of meeting the growing needs for precise and timely pressure monitoring. This article introduces a novel self-powered pressure sensor utilizing electrochemical reactions. The sensor's ion conduction path and internal resistance adjust in response to external stress across a broad range. Its three-dimensional structure, crafted by using a simple template on the electrolyte, enables the efficient and cost-effective detection of various mechanical stimuli. This device not only achieves an optimized power density of approximately 2.34 mW cm-2─surpassing most existing technologies─but also features excellent flexibility, quick response, and recovery times (0.15 and 0.19 s respectively); high durability (2000 cycles); and a broad sensing range (0.23-20 kPa). Moreover, it serves as an ionic touchpad, enhancing data collection and recognition, and integrates seamlessly with a mouthpiece for accurate, real-time monitoring of respiratory activities. This innovative sensor offers minimal cost and simple process requirements while providing multifunctional capabilities for energy harvesting and pressure sensing, marking a significant step forward in the design of next-generation sensors.

High-efficiency quad-band RF energy harvesting system with improved cross-coupled differential-drive rectifier

Abstract RF energy harvesting technology has garnered significant attention from researchers in recent years. This paper presents a high-efficiency quad-band RF energy harvesting (RFEH) system. It introduces an improved cross-coupled differential-drive rectifier designed for ambient wireless powering, capable of harnessing power from four distinct ambient RF sources: FM-100, DTV-600, GSM-1800, and WiFi-2400 frequency bands. The proposed RFEH system demonstrates notable advancements, achieving a high RF to DC conversion efficiency of over 80 % within an input power range of −5 dB m to +13 dB m, with a 5 kΩ resistance load. This power output is deemed sufficient for energizing low-power micro-devices autonomously, without reliance on external power sources. Notably, the DC output voltage of the proposed RFEH system exhibits a high level of stability against variations in input power, a characteristic not adequately addressed in existing systems.

Hybrid DC circuit breaker power supply system with load constant voltage self‐balancing design

AbstractPower electronic switches (PES) play a crucial role in transferring and clearing fault currents in hybrid DC circuit breakers. The PES encounters switching transients that require a dependable external power source. Usually, a power supply system utilizes an isolation transformer and many magnetic rings. However, the existence of inconsistent parameters might easily cause an imbalance in load power, which could potentially result in power supply failure for the loads. Therefore, to enhance the reliability of power supply, this study proposes a load constant voltage self‐balancing design approach that utilizes feedback circuits to achieve stability and balance in load voltage. At first, two feedback circuits are shown, and the analytical formulas for load active power and load voltage are derived. Moreover, a parameter design methodology is shown for the equivalent circuit of the magnetic rings in the power supply. Additionally, a power supply system is built with 24 V outputs. In conclusion, this study utilizes simulations and tests to assess the effectiveness of the proposed power supply system by analysing its performance during start‐up, load power‐off, and steady‐state operations.

Metasurface-enabled multifunctional single-frequency sensors without external power

IoT sensors are crucial for visualizing multidimensional and multimodal information and enabling future IT applications/services such as cyber-physical spaces, digital twins, autonomous driving, smart cities and virtual/augmented reality (VR or AR). However, IoT sensors need to be battery-free to realistically manage and maintain the growing number of available sensing devices. Here, we provide a novel sensor design approach that employs metasurfaces to enable multifunctional sensing without requiring an external power source. Importantly, unlike existing metasurface-based sensors, our metasurfaces can sense multiple physical parameters even at a fixed frequency by breaking classic harmonic oscillations in the time domain, making the proposed sensors viable for usage with limited frequency resources. Moreover, we provide a method for predicting physical parameters via the machine learning-based approach of random forest regression. The sensing performance was confirmed by estimating the temperature and light intensity, and excellent determination coefficients larger than 0.96 were achieved. Our study affords new opportunities for sensing multiple physical properties without relying on an external power source or requiring multiple frequencies, which markedly simplifies and facilitates the design of next-generation wireless communication systems.

Preparation of Self‐Driven Triboelectric Nanosensor Based on Chitosan‐Coated Ti Foil for Detecting Blood Glucose Concentration

The clinical diagnosis of diabetes mellitus typically depends on blood glucose measurements. Many laboratory studies have focused on enzyme–electrode biosensors that require an external power source. In this study, the potential of triboelectric nanogenerators (TENGs) as self‐driven sensors for glucose detection is investigated by utilizing the glucose specificity of glucose oxidase. When immersed in glucose solutions with concentrations ranging from 3.9 to 13.1 mmol L−1, the TENGs exhibit a linear relationship between the glucose concentration and current and voltage changes. These findings suggest that the TENGs developed in this study can effectively function as glucose sensors, providing a foundation for future human blood glucose monitoring applications and demonstrating a promising new approach for biomedical sensor technology.

Flexible Magnetoelectric Fiber for Self-Powered Human-Machine Interactive.

Flexible large strain sensors are an ideal choice for monitoring human motion, but the current use of flexible strain gauges is hindered by the need for external power sources and long-term operation requirements. Fiber-based sensors, due to their high flexibility, excellent breathability, and the ease with which they can be embedded into everyday clothing, have the potential to become a novel type of wearable electronic device. This paper proposes a flexible self-powered strain sensing material based on the electromagnetic induction effect, composed of a uniform mixture of Ecoflex and Nd2Fe14B, which has good skin-friendliness and high stretchability of over 100%. The voltage output of the magnetoelectric composite fiber remains stable over 5000 stretch-release cycles, reaching up to 969 μV. Based on this novel sensing material, a remote smart car control scheme for a human-machine interaction system was designed, enabling real-time gesture interaction.

Research on Highly Reliable Self-Powered Vibration Sensors for Geological Drilling

Vibration signals at the bottom of the drill string during geological drilling are crucial for lithological identification and drilling parameter optimization. However, existing downhole vibration sensors suffer from limitations in power supply and reliability. This study proposes a self-powered vibration sensor with high redundancy based on the triboelectric nanogenerator principle, which is capable of measuring both axial and transverse vibrations, thereby reducing the dependence on external power sources. The experimental results show that the sensor can measure axial vibration frequencies ranging from 0 to 11 Hz with an error of less than 4% and transverse vibration frequencies ranging from 0 to 5 Hz with an error of less than 5%. It can operate stably in temperatures from 0 to 180 °C and relative humidities from 0 to 95%. The sensor’s axial vibration measurement features six identical measurement structures, providing high redundancy and effectively enhancing its reliability. Furthermore, the sensor exhibits power generation capabilities. When an external load of 1 MΩ is applied to the axial measurement module and 10 MΩ to the transverse measurement module, the sensor achieves its maximum power output for both axial and transverse measurements, reaching 32.4 × 10−9 W and 2.1 × 10−9 W, respectively. Compared to traditional bottom-of-the-hole vibration sensors, this sensor possesses self-powering capabilities and high reliability, which can improve the operational efficiency and hold significant practical value for future applications.

A Wide Color Gamut and Noniridescent Zinc-Anode Asymmetric Electrochromic Device for Self-Sustaining Color-Adaptive Bio-Camouflage System.

Inspired by camouflage-colored organisms, the development of bio-camouflage systems using electrochromic (EC) technology has gained significant interest. However, existing EC systems struggle with achieving a wide color gamut, noniridescent colors, and self-sustainability. Herein, a self-sustainable color-adaptive bio-camouflage system integrating EC and nanogenerator (NG) technologies, enabling environmental color adaptation, and thermal regulation without an external power source is proposed. The system is based on a zinc-anode EC device (ZECD) with an asymmetric structure, incorporating flexible tungsten oxide and vanadium oxide electrodes. During the EC process, tungsten oxide shifts between blue and transparent, allowing near-infrared thermal modulation, while the vanadium oxide transitions from yellow to transparent. This design enables reversible near-infrared modulation and noniridescent color conversion among black, blue, green, yellow, and transparent. For the self-sustainability of the system, an electromagnetic and triboelectric hybrid NG that collects biomechanical energy is developed. In a typical driven cycle, the integrated system transitions colors and achieves significant near-infrared spectral modulation, demonstrating environmental adaptability and thermal regulation. Experiments on human skin and simulated chameleon color changes further confirm the system's effectiveness. This work highlights the potential of integrating EC and NG technologies to advance color-adaptive camouflage systems, opening new an avenue for bio-camouflage design.

Application of Biomass-Based Triboelectrification for Particulate Matter Removal

Electrostatic fields are crucial for achieving the highly efficient filtration of airborne pollutants. However, the dissipation of static charges over time, especially under humid conditions, limits their practical application. In this study, we present a self-charging air filter (SAF) powered by a triboelectric nanogenerator (TENG). This SAF is integrated into a commercial mask, termed SAFM, which can effectively capture and degrade airborne pollutants without requiring an external power source. By leveraging the triboelectric effect during breathing, the TENG within the SAFM continuously replenishes static charges, maintaining the triboelectric field. The system employs a cellulose aerogel/Ti3C2Tx composite as the electron donor and an esterified cellulose-based electrospun nanofiber as the electron acceptor. Remarkably, the triboelectric field significantly enhances filtration performance, with the SAF achieving up to 95.7% filtration efficiency for particulate matter as small as 0.3 μm. This work underscores the potential of TENG-powered triboelectric fields in the development of multifunctional, human-machine interactive facemasks.

Fluid mediated communication among flexible micro-posts in chemically reactive solutions.

Communication in biological systems typically involves enzymatic reactions that occur within fluids confined between the soft, elastic walls of bio-channels and chambers. Through the inherent transformation of chemical to mechanical energy, the fluids can be driven to flow within the confined domains. Through fluid-structure interactions, the confining walls in turn are deformed by and affect this fluid flow. Imbuing synthetic materials with analogous feedback among chemo-mechanical, hydrodynamic and fluid-structure interactions could enable materials to perform self-driven communication and self-regulation. Herein, we develop computational models to determine how chemo-hydro-mechanical feedback affects interactions in biomimetic arrays of chemically active and passive micro-posts anchored in fluid-filled chambers. Once activated, the enzymatic reactions trigger the latter feedback, which generates a surprising variety of long-range, cooperative motion, including self-oscillations and non-reciprocal interactions, which are vital for propagating coherent, directional signals over net distances in fluids. In particular, the array propagates a distinct message; each post interprets the message; and the system responds with a specific mode of organized, collective behavior. This level of autonomous remote control is relatively rare in synthetic systems, particularly as this system operates without external electronics or power sources and only requires the addition of chemical reactants to function.

Real-time in-situ coatings corrosion monitoring using machine learning-enhanced triboelectric nanogenerator

Current methods for monitoring coating corrosion are limited by their inability to provide real-time data and dependence on external power sources. This study presents a novel in-situ corrosion monitoring system using a solid-liquid triboelectric nanogenerator (TENG) that converts mechanical energy into electrical signals for self-powered sensing. TENG signals and electrochemical impedance spectra were measured on a dopamine-modified lignin-polydimethylsiloxane coating on steel in 1 M NaCl solution under no corrosion, indentation, pitting, and broken conditions, respectively. We extract time-frequency features from the TENG signals to predict the coating’s corrosion condition by applying a customised convolutional neural network (CNN). By extracting time-frequency features from the TENG signals and applying a custom CNN, a prediction accuracy of 99 % for corrosion classification was achieved. Furthermore, the CNN regression model predicted coating impedance values with a high coefficient of determination (R² = 0.98), demonstrating its effectiveness in tracking corrosion progression. The developed TENG also facilitates defect localisation via a matrix electrode beneath the coating. Our approach introduces a promising real-time technology for in-situ corrosion monitoring.

The Biomimetic Electrical Stimulation System Inducing Osteogenic Differentiations of BMSCs.

Electrical stimulation has been used clinically as an adjunct therapy to accelerate the healing of bone defects, and its mechanism requires further investigations. The complexity of the physiological microenvironment makes it challenging to study the effect of electrical signal on cells alone. Therefore, an artificial system mimicking cell microenvironment in vitro was developed to address this issue. In this work, a novel electrical stimulation system was constructed based on polypyrrole nanowires (ppyNWs) with a high aspect ratio. Synthesized ppyNWs formed a conductive network in the composited hydrogel which contained modified gelatin with methacrylate, providing a conductive cell culture matrix for bone marrow mesenchymal stem cells. The dual-network conductive hydrogel had improved mechanical, electrical, and hydrophilic properties. It was able to imitate the three-dimensional structure of the cell microenvironment and allowed adjustable electrical stimulations in the following system. This hydrogel was integrated with cell culture plates, platinum electrodes, copper wires, and external power sources to construct the artificial electrical stimulation system. The optimum voltage of the electrical stimulation system was determined to be 2 V, which exhibited remarkable biocompatibility. Moreover, this system had significant promotion in cell spreading, osteogenic makers, and bone-related gene expression of stem cells. RNA-seq analysis revealed that osteogenesis was correlated to Notch, BMP/Smad, and calcium signal pathways. It was proven that this biomimetic system could regulate the osteogenesis procedure, and it provided further information about how the electrical signal regulates osteogenic differentiations.

Feasibility Assessment of Rapid Response EEG in the Identification of Nonconvulsive Seizures During Military Medical Air Transport.

Traumatic brain injury often requires neurologic care and specialized equipment, not often found downrange. Nonconvulsive seizures (NCSs) and nonconvulsive status epilepticus (NCSE) occur in up to 30% of patients with moderate or severe traumatic brain injury and is associated with a 39% morbidity and an 18% mortality. It remains difficult to identify at bedside because of the heterogeneous clinical manifestations. The primary diagnostic tool is an electroencephalogram (EEG) which is large, requires an external power source, and requires a specialized technician and neurologist to collect and interpret the data. Rapid response EEG (rr-EEG) is an FDA-approved device that is pocket sized and battery powered and uses a disposable 10-electrode headset. Prior studies have demonstrated the noninferiority of rr-EEG in the identification of NCSE and NCS as compared to conventional EEG in hospitals. An unanswered question is whether rr-EEG could be used in the identification of NCSE and NCS by medics. In conjunction with the Critical Care Air Transport (CCAT) team, a simulation was created and implemented on a CCAT training mission. The simulation team included a neurology resident, who oversaw the simulation, a pulmonary critical care fellow, an intensive care unit nurse, and a respiratory therapy. A survey was provided before and after the simulation. The team was expected to review the rr-EEG to make clinical decisions during ground transport, takeoff, and landing. The neurology resident monitored and recorded the team's ability to distinguish between NCS and a normal EEG. In between, the neurology resident monitored the quality of the EEG for potential interference and loss of quality. The CCAT team was able to efficiently set up the rr-EEG on a patient manikin, correctly identify visual EEG wave forms of a patient in NCS, and utilize the proprietary audio program of a simulated patient in NCS. The team reported that the device was easily set up in the environment, and the data were interpretable despite vibration, aircraft auditory and electrical noise, and the ergonomics of the aircraft medical section. This pilot study has validated a potentially revolutionary technology in medical transport. The rr-EEG technology is measurably user-friendly and will improve patient outcomes. This device and simulation can reduce time to an EEG by hours to days allowing for immediate treatment and intervention, which can significantly reduce morbidity and mortality.

Piezoelectric Scaffolds as Smart Materials for Bone Tissue Engineering.

Bone repair and regeneration require physiological cues, including mechanical, electrical, and biochemical activity. Many biomaterials have been investigated as bioactive scaffolds with excellent electrical properties. Amongst biomaterials, piezoelectric materials (PMs) are gaining attention in biomedicine, power harvesting, biomedical devices, and structural health monitoring. PMs have unique properties, such as the ability to affect physiological movements and deliver electrical stimuli to damaged bone or cells without an external power source. The crucial bone property is its piezoelectricity. Bones can generate electrical charges and potential in response to mechanical stimuli, as they influence bone growth and regeneration. Piezoelectric materials respond to human microenvironment stimuli and are an important factor in bone regeneration and repair. This manuscript is an overview of the fundamentals of the materials generating the piezoelectric effect and their influence on bone repair and regeneration. This paper focuses on the state of the art of piezoelectric materials, such as polymers, ceramics, and composites, and their application in bone tissue engineering. We present important information from the point of view of bone tissue engineering. We highlight promising upcoming approaches and new generations of piezoelectric materials.

Continuous Health Monitoring of Reinforced Concrete Bridge Deck based on Traffic Load-induced Acoustic Emission

This paper presents continuous bridge deck monitoring based on b-value obtained from traffic load-induced acoustic emission (AE) signals. Using the self powered AE system that we developed, we have observed traffic load-induced AE on an actual bridge for five years. The developed self-powered AE system demonstrated that long-term traffic load-induced AE measurements over five years could be performed without an external power source. Traffic load-induced AEs measured irregularly by event-driven measurement were accumulated, and b-values were calculated. We used an additive regression model that accounts for piecewise linear trends and seasonality to extract long-term trends accurately. Over the past five years, the bridge has deteriorated. In addition, repairs were made during the period. As a result of this monitoring, we determined the relationship between the damage condition of the bridge and the b-value trend obtained from the traffic load-induced AEs. The results confirmed that the b-value based on traffic load-induced AE corresponds well with the damage conditions on the underside of the deck slab or in a shallow area inside it.

Wireless LED controller IC for smart contact lens system

AbstractThis letter presents a wirelessly powered LED driving circuit for a smart contact lens system. Since photobiomodulation has been investigated for ocular disease treatment by irradiating light with a specific wavelength, a smart contact lens equipped with a µLED and its controller IC can be utilized as a phototherapy system. The proposed circuit design facilitates constant‐current generation to drive the LED and incorporates a wirelessly powered system. The system can be turned on and off in synchronization with an external wireless power source, providing controllability for the LED's irradiation period and intensity. The IC is fabricated in the 180‐nm CMOS process with a die area of 1.0 mm2 and integrated into the smart contact lens with an external loop antenna and a far red/NIR LED. The measurement demonstrates the irradiation period of the LED is successfully controlled by the external source, with current levels from 0.53 mA to 1.4 mA, thereby confirming the feasibility of the phototherapy system.