Efficient Energy Harvesting Research Articles

A self-powered wireless monitoring system driven by ambient RF energy for switch rails

Purpose This study aims to develop a novel self-powered monitoring system that uses radio frequency (RF) energy harvesting and ultra-low-power management technologies for real-time condition monitoring of switch rails. Design/methodology/approach The system is designed for integration within the jump wire holes of switch rails, ensuring structural integrity and aesthetic appeal. It features a highly efficient energy harvesting mechanism combined with optimized power management for wireless sensor nodes. An on-board antenna captures ambient RF energy, managed by high-efficiency circuits to ensure stable wireless sensor operation. An ultra-low-power system-on-chip is used to acquire and transmit multimodal data on vibration and temperature from the switch rails. The data collection is enhanced through a two-threshold approach, adapting to harvested energy levels for self-energy balancing. Findings Testing revealed that the energy harvesting subsystem operated stably at distances up to 2.9 m from the RF source, charging a 200 µF capacitor to 4.2 V in just 220 s. The monitoring subsystem’s average power consumption is in the low microwatt range. Continuous operation over 30 days in real conditions resulted in only a 5 mV reduction in battery voltage, indicating successful self-powered operation and validating long-term reliability in unattended scenarios. Originality/value This research presents an innovative solution, integrating RF energy harvesting with ultra-low-power technology, which addresses the power and stability challenges faced by traditional monitoring systems.

A Dual‐Band Dual‐Polarized Rectenna for Efficient RF Energy Harvesting in Battery‐Less IoT Devices With Broad Power Range

ABSTRACTThe demand for maintenance‐free, battery‐less IoT devices, driven by sustainable Industry 4.0 practices, necessitates efficient RF energy harvesting solutions. Addressing the limitations of single‐frequency harvesting, a novel dual‐band, dual‐polarized rectenna operating at 3.6 GHz and 5.8 GHz is proposed. The antenna resonates at 3.6 GHz with linearly polarized (LP) characteristics and 5.8 GHz with circularly polarized (CP) characteristics with impedance bandwidth (IBW) of 2.2% and 5.63%, respectively, achieving a gain of 4.85 dBi and 6.75 dBic, respectively. A rectenna consists of an antenna at the front end and an RF‐DC rectifier at the backend. This approach maximizes power conversion efficiency by minimizing impedance mismatches and reflection losses and mitigates interference between the dual bands within the rectifier circuitry. The rectifier achieves peak efficiencies of 65.5% at 3.6 GHz with a 3 dBm input and 44% at 5.8 GHz with a −1 dBm input, both with 2KΩ load. Efficiency exceeds 30% at 3.6 GHz for an input range from −10 to 6.5 dBm and exceeds 20% at 5.8 GHz for an input range from −13 to 3 dBm. These design considerations enable reliable harvesting of ambient RF energy across a range of −20 to 20 dBm, enabling continuous IoT device operation. Our measurements confirm the design's effectiveness in converting low‐power RF signals into usable energy, supporting sustainable and autonomous IoT deployments at 3.6 and 5.8 GHz.

Advancements in framework materials for enhanced energy harvesting.

Energy harvesting, the process of capturing ambient energy from various sources and converting it into usable electrical power, has attracted a lot of attention due to its potential to provide long-term and self-sufficient energy solutions. This comprehensive review thoroughly explores the use of metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) for energy harvesting by piezoelectric and triboelectric nanogenerators (PENGs and TENGs). It begins by classifying and outlining the structural diversity of MOFs and COFs, which is key to understanding their importance in energy applications. Key characterization techniques are focused on emphasizing their importance in optimizing material properties for efficient energy conversion. The working mechanisms of PENGs and TENGs are discussed, focusing on their ability to transform mechanical energy into electrical energy and their advantages in operation. The use of MOFs and COFs in energy harvesting applications is then discussed, including synthesis procedures, unique characteristics relevant to electricity conversion, and various practical applications such as self-powered sensors and wearable electronics. Current challenges such as stability, scalability, and performance improvements are explored, as well as proposed future improvements to help advance current research. Finally, the study highlights the importance of framework materials for the development of energy harvesting systems, providing an invaluable resource for academics and engineers seeking to exploit the potential of these materials for renewable energy sources. The goal of this article is to stimulate further invention and implementation of efficient materials-based energy harvesting framework devices by integrating recent advances and mapping future possibilities.

Clay-based anion-selective 2D nanofluidics boost natural osmotic power generation

Two-dimensional (2D) nanofluidics technology has shown great potential in efficient osmotic energy harvesting, while the lack of anion-selective 2D nanofluidics limits the development of full concentration cells towards real-world applications....

Laser surface processing technology for performance enhancement of TENG

<p>The triboelectric nanogenerator (TENG), as a new energy harvesting device, can efficiently harvest mechanical energy from the environment to provide continuous power for electronic devices, which has great potential for powering intelligent distributed network. Laser processing technology, which enables structural, phase, and property control at different scales, can quickly and easily complete the surface patterning of TENG and facilitate efficient energy harvesting. In this work, we outline the working modes and principles of TENG, review the research progress of laser surface processing technology for fabricating TENG in recent years, including laser-induced graphene (LIG), laser ablation, laser carbonization, laser-induced copper, etc., and perspectives on the challenges and future directions for development of laser surface processing for performance enhancement of TENG.</p>

Design and Optimization of Reconfigurable Intelligent Surfaces Structures

This research investigates the design and optimization of reconfigurable intelligent surfaces (RIS) structures to enhance simultaneous wireless information and power transfer (SWIPT) in cooperative relay networks. The integration of RIS technology with SWIPT offers promising opportunities to improve the energy efficiency and spectral efficiency of wireless communication systems. In this study, we propose novel RIS deployment strategies and optimization algorithms to maximize the performance of SWIPT-enabled cooperative relay networks. First, we analyze the fundamental principles of RIS-assisted SWIPT and cooperative relay networks, considering the unique characteristics and challenges of each component. We then formulate optimization problems to jointly optimize the placement of RIS elements, relay selection, transmit power allocation, and RIS phase configuration to achieve the desired trade-off between communication reliability, energy efficiency, and spectral efficiency. Furthermore, we develop efficient algorithms for channel estimation, feedback, and coordination among RIS, relays, and destination nodes to adapt to dynamic channel conditions and user requirements. We also investigate the impact of RIS deployment on the energy harvesting performance of SWIPT-enabled relay nodes, considering factors such as RIS reflection coefficients, relay-RIS distance, and incident signal power distribution. Moreover, we address security and privacy considerations in RIS-assisted SWIPT, including potential vulnerabilities, authentication mechanisms, and privacy-preserving communication techniques. Finally, we validate the proposed design and optimization techniques through comprehensive simulations and real-world experiments, considering practical constraints such as hardware implementation, energy harvesting efficiency, and deployment scenarios. Overall, this research contributes to advancing the understanding and practical implementation of RIS technology for SWIPT in cooperative relay networks, offering insights into the design, optimization, and performance evaluation of next-generation wireless communication systems.

Prototype of Implant for Nitric Oxide Release Controlled byInfrared Radiation in Therapeutic Window.

Local therapeutic action and targeted drug release are promising approaches compared to traditional systemic drug administration. This is especially relevant for nitric oxide (NO), as its effects change dramatically depending on concentration and cellular context. Materials capable of releasing NO in deep tissues in a controlled manner might open new therapeutic opportunities. Light-sensitive NO donors represent a fascinating class of compounds with significant potential for precise and controlled NO release. However, most of them are sensitive to visible light, with only a few examples absorbing in a near-infrared therapeutic window. Here, we present the proof-of-concept of soft implants consisting of the photon upconverting core and the outer shell loaded with visible-light triggered NO donor. The separation into two compartments results in efficient energy harvesting by the dye and effective NO release under 980 nm infrared irradiation. Such implants could be used in smart therapies implying well-controlled and localized NO release.

Performance-enhanced piezoelectric energy harvesting system induced by Karman vortex using concave pseudo-blunt body structure

Abstract In recent years, the technology of fluid-induced piezoelectric vibration energy harvesting for blunt body structures based on Karman vortex street effect has been widely studied. In order to further improve the efficiency of energy harvesting, a performance-enhanced method of Karman vortex street energy harvesting based on structural modification is proposed. Different pseudo-blunt bodies with concave surfaces are designed and combined with piezoelectric device to harvest energy. The finite element simulation results show that, compared with the cylindrical blunt body, the pseudo-blunt body with concave surface can enhance the turbulent action of the fluid and make the Karman vortex shedding more intense. Especially for the pseudo-blunt body with S-concave, the amplitude of Karman vortex street and the turbulent kinetic energy behind the pseudo-blunt is strongest. In addition, based on wind tunnel, the energy harvesting performance of Karman vortex behind a cylinder with different surface structures is experimentally studied. The experimental results show that the piezoelectric energy harvesting efficiency behind the cylindrical pseudo-blunt body with concave surface is better than that behind the cylindrical blunt body without concave surface. In particular, the S-concave pseudo-passivate has the best energy harvesting performance, with a peak output voltage of 23.6 V, an output voltage span of 31.2 V, a maximum current of up to 0.23mA, and a maximum power density of up to 6.64 W/m³, which are 136% and 81% higher than that of the ordinary cylindrical passivate, with an increase in the maximum current of 155% and an increase in the optimal power density of 532%, respectively. The above results show that the concave-based pseudo-blunt body structure can effectively improve the efficiency of vortex energy harvesting using piezoelectric mechanism, which lays an important foundation for the development and application of piezoelectric vortex energy harvesting theory.

A Triboelectric Nanogenerator Utilizing a Crank-Rocker Mechanism Combined with a Spring Cantilever Structure for Efficient Energy Harvesting and Self-Powered Sensing Applications

With the advancement of industrial automation, vibrational energy generated by machinery during operation is often underutilized. Developing efficient devices for vibration energy harvesting is thus essential. Triboelectric nanogenerators (TENGs) based on spring and cantilever beam structures show considerable potential for industrial vibration energy harvesting; however, traditional designs often fail to fully harness vibrational energy due to their structural limitations. This study proposes a triboelectric nanogenerator (TENG) based on a crank-rocker mechanism and a spring cantilever structure (CR-SC TENG), which combines a crank-rocker mechanism with a spring cantilever structure, designed for both energy harvesting and self-powered sensing. The CR-SC TENG incorporates a spring cantilever beam, a crank-rocker mechanism, and lever amplification principles, enabling it to respond sensitively to low-frequency, small-amplitude vibrations. Utilizing the crank-rocker and lever effects, this device significantly amplifies micro-amplitudes, enhancing energy capture efficiency and making it well suited for low-amplitude, complex industrial environments. Experimental results demonstrate that this design effectively amplifies micro-vibrations and markedly improves energy conversion efficiency within a frequency range of 1–35 Hz and an amplitude range of 1–3 mm. As a sensor, the CR-SC TENG’s dual-generation units produce output signals that precisely reflect vibration frequencies, making it suitable for the intelligent monitoring of industrial equipment. When placed on an air compressor operating at 25 Hz, the first-generation unit achieved an output voltage of 150 V and a current of 8 μA, while the second-generation unit produced an output voltage of 60 V and a current of 5 μA. These findings suggest that the CR-SC TENG, leveraging spring cantilever beams, crank-rocker mechanisms, and lever amplification, has significant potential for micro-amplitude energy harvesting and could play a key role in smart manufacturing, intelligent factories, and the Internet of Things.

A Review of Triboelectric Nanogenerators in Wind Energy Harvesting and Environmental Monitoring

With the growing demand for renewable energy and the development of portable electronic devices, there is an increasing need for self-powered systems. This paper reviews recent advancements in wind energy harvesting and environmental monitoring, with a particular focus on triboelectric nanogenerators (TENGs). TENG technology efficiently converts wind energy into electrical energy through the coupling of triboelectric effects and electrostatic induction, offering advantages such as simplicity, low cost, and high efficiency. The paper details the fundamental working principles of TENGs, their various operational modes, and the design of hybrid electromagnetic generators (TENG-EMG) that integrate TENGs with electromagnetic generators. It also discusses innovative devices such as the calliopsis biomimetic triboelectric nanogenerator (C-TENG), the polymer wind bead rolling triboelectric nanogenerator (WB-TENG), and the self-sustaining wind speed sensor system (SSWSSS). These devices not only enhance the efficiency of wind energy harvesting but also broaden the scope of wind speed and direction monitoring. Finally, the paper explores future research directions for TENG technology, including multifunctional integration, material innovation, intelligent management, and environmental impact assessment, aiming to further advance sustainable energy and environmental monitoring.

LSTM-Based MPPT Algorithm for Efficient Energy Harvesting of a Solar PV System Under Different Operating Conditions

Solar energy is one of the most favorable renewable energy sources and has undergone significant development in the past few years. This paper investigates a novel concept of harvesting the maximum power of a photovoltaic (PV) system using a long-short term memory (LSTM) to forecast the irradiance value and a feedforward neural network (FNN) to predict the maximum power point (MPP) voltage. This study paves a way to mitigate avoidable inefficiencies that hinder the optimal performance of a PV system, due to the intermittent nature of solar energy. MATLAB/Simulink software platform was used to validate the proposed algorithm with real irradiance data from different geographical and weather conditions. Furthermore, the maximum power point tracking (MPPT) algorithm was implemented in a laboratory setup. The simulation results portray the superiority of the proposed method in terms of tracking performance and dynamic response through a comprehensive case study conducted with five other state-of-the-art MPPT methods selected from conventional, AI based, and bio-inspired MPPT categories. In addition to that, faster response time and lesser oscillations around the MPP were observed, even during volatile weather conditions and partial shading.

Hybrid Microwave/Solar Energy Harvesting System Using 3D-Printed Metasurfaces.

In this study, a hybrid energy harvesting system based on a conventional solar cell combined with 3D-printed metasurface units is studied. Millimeter-scale metasurface units were fabricated via the stereolithography technique, and then they were covered with conductive silver paint, in order to achieve high electric conductivity. The performance of single, as well as two-unit metasurface harvesters, was thoroughly investigated. It was found that both of them produced voltage, which peaks at their resonance frequency, demonstrating efficient energy harvesting behavior in the microwave regime. Then, the metasurface units were connected with a commercially available photovoltaic panel and the performance of the hybrid system was examined under different environmental conditions, modifying the light intensity (i.e., light, dark and shadow). It was shown that the proposed hybrid harvesting system produces a sizable voltage output, which persists, even in the case when one of the components does not contribute. Furthermore, the performance of the hybrid harvester is found to be adequate enough, although optimization of the harvesting circuit is required in order to achieve high efficiency levels. All in all, the presented experimental evidence clearly indicates the realization of a rather promising hybrid energy harvesting system, exploiting two distinct ambient energy sources, namely light and microwaves.

A Coaxial Triboelectric Fiber Sensor for Human Motion Recognition and Rehabilitation via Machine Learning

This work presents the fabrication of a coaxial fiber triboelectric sensor (CFTES) designed for efficient energy harvesting and gesture detection in wearable electronics. The CFTES was fabricated using a facile one-step wet-spinning approach, with PVDF-HFP/CNTs/Carbon black as the conductive electrode and PVDF-HFP/MoS2 as the triboelectric layer. The incorporation of 1T phase MoS2 into the PVDF-HFP matrix significantly improves the sensor’s output owing to its electron capture capabilities. The sensor’s performance was carefully optimized by varying the weight percentage of MoS2, the thickness of the fiber core, and the CNT ratio. The optimized CFTES, with a core thickness of 156 µm and 0.6 wt% MoS2, achieved a stable output voltage of ~8.2 V at a frequency of 4 Hz and 10 N applied force, exhibiting remarkable robustness over 3600 s. Furthermore, the CFTES effectively detects human finger gestures, with machine learning algorithms further enhancing its accuracy. This innovative sensor offers a sustainable solution for energy transformation and has promising applications in smart portable power sources and wearable electronic devices.

STONEHENGE – A toolbox for nonlinear vibration energy harvesting

In this work, we present STONEHENGE - Suite for nonlinear analysis of energy harvesting systems, a comprehensive toolbox engineered to study nonlinear piezoelectric vibration energy harvesters. These harvesters can harness kinetic energy from the environment and convert it into electricity using the piezoelectric effect. By introducing nonlinearity through strategically placed magnets, their efficiency is enhanced across a wide frequency spectrum. However, it comes at the cost of increasing complexity in system dynamics. To investigate this complexity and comprehend the potential of nonlinear energy harvesting, the STONEHENGE library was created. It is tailored to analyze the harvesting performance and dynamic behavior of these systems and allows users to explore and characterize system dynamics across a diverse range of physical parameters and excitation conditions using advanced numerical simulations. The toolbox encompasses six key modules, (i) initial value problem, analysis of system behavior from initial conditions; (ii) dynamic animation: which provides visual representations of system dynamics, aiding in intuitive understanding and interpretation; (iii) nonlinear tools: equips users with tools to dissect and comprehend the nonlinear aspects of vibration harvesting systems, essential for comprehensive analysis; (iv) sensitivity analysis: facilitates the assessment of how system behavior responds to variations in parameters, offering insights into its robustness and performance under different conditions; (v) stochastic simulation: allows for the exploration of system behavior under stochastic excitation, crucial for understanding real-world operating conditions; (vi) chaos control: offers methods for mitigating chaotic behavior within the system, enhancing predictability and stability. Utilizing a bistable oscillator as a benchmark, STONEHENGE aims to serve as a valuable resource for the development and refinement of both existing and emerging nonlinear vibration-based energy harvesting systems. By providing a comprehensive toolkit for analysis and characterization, STONEHENGE seeks to catalyze advancements in this field, ushering in an era of more efficient and sustainable energy harvesting technologies. Moreover, this library was developed to be easily adaptable to different dynamic systems and can contribute to different application fields.

Numerical analysis and data-driven optimization of energy harvesting efficiency from wake-induced vibration in a multi-cylinder configuration

Wake-induced vibrations (WIV) in multi-cylinder configurations have demonstrated greater energy harvesting efficiency in hydrokinetic applications compared to conventional vortex-induced vibrations (VIV) of a single cylinder. However, the complex fluid-structure interactions make it challenging to identify optimal configurations for maximum power output, as extensive simulations across numerous parameter combinations lead to substantial computational costs with traditional computational fluid dynamics (CFD) methods. To address this challenge, we developed a data-driven model using automated machine learning (AutoML) techniques, focusing on four key parameters: spacing, diameter, damping, and reduced velocity. Trained on comprehensive datasets from validated CFD simulations, this model integrates multiple algorithms to predict the power efficiency of WIV systems with high accuracy. Our approach enables rapid and precise evaluations of power efficiency across a broad range of configurations, significantly reducing the computational burden compared to traditional CFD approaches. The results indicate that optimal configurations, characterized by larger upstream cylinder diameters, higher damping ratios, and ideal spacing ratios, can achieve power generation efficiencies of up to 59.15%. Further analysis of vorticity contours reveals that synchronized interactions between upstream vortex shedding and downstream structure motions enhance WIV, thereby improving energy harvesting efficiency.

Improving the wind energy harvesting performance with double upstream fractal bluff bodies

Fossil energy sources are not renewable and the technology to harness wind energy has gained considerable interest. This work proposes a wake galloping energy harvester with upstream fractal structures to promote the efficiency of wind energy harvesting. The dynamic response and energy harvesting performance of a conventional galloping energy harvester (GEH), a vortex-induced vibration energy harvester (VIVEH), a traditional wake galloping energy harvester with single or double upstream cuboids (WGEH-SC, WGEH-DC), and a wake galloping energy harvester with single or double fractal upstream structures (WGEH-SF, WGEH-DF) are evaluated numerically and experimentally. At a wind speed of 5.0 m/s, WGEH-DF increases the maximum root mean square (RMS) voltage from 19.36 V to 39.25 V, indicating an improvement of 102.7% compared to the VIVEH. Meanwhile, the effects of the positions and windward angles of the upstream bluff bodies are discussed, and the WGEH-DF reaches its maximum average RMS voltage at an angle of 75° and x=2 cm. It is found that when two fractal bluff bodies are placed upstream, the pressure difference increases on both sides of the downstream bluff body and the structural vibration becomes more violent. By comparing the pressure behind the two cuboids and two fractal bluff bodies, it is demonstrated that the negative pressure behind the fractal bluff bodies is increased. The flow field analysis further explains the aerodynamic mechanism that the fractal bluff bodies placed upstream improve energy harvesting performance.

Efficient Photocatalytic Energy Harvesting for Air Purification and Electrical Generation

Efficient Photocatalytic Energy Harvesting for Air Purification and Electrical Generation

A Review of Energy Harvesting Techniques for Self-Powered IoT Devices

The Internet of Things (IoT) manages a vast network of interconnected smart devices that collect, transmit, and analyze data from their environment using embedded components like processors, sensors, and communication equipment. These devices, which require efficient power sources, often rely on batteries that limit their operational lifespan and increase environmental impact. This paper provides a comprehensive review of energy harvesting techniques aimed at enhancing the longevity and sustainability of IoT devices. The methodology involves a comparative analysis of various energy harvesting sources such as solar, thermal, RF, and mechanical energy focusing on their efficiency, applicability, and integration within wireless sensor networks (WSNs). Key contributions include the identification of current limitations in energy harvesting technologies, such as low energy conversion efficiency and intermittency, and the proposal of solutions to optimize energy capture and storage. The results demonstrate that integrating multiple energy sources can significantly improve power availability and reduce dependence on conventional batteries. This review concludes by outlining the ongoing challenges and future research directions needed to develop efficient, reliable, and cost-effective energy harvesting systems for IoT applications.

Research on multi-input self-powered piezoelectric energy harvesting interface circuit based on synchronous inversion and charge extraction

Aiming at the problem of low conversion efficiency of piezoelectric harvesting energy system, this study proposes a self-powered-synchronous inversion and charge extraction (SP-SICE) circuit on the basis of synchronous inversion charge extraction (SICE) circuit. The output voltage of the SP-SICE circuit is 63.6% higher than that of the SICE circuit through simulation comparison, and the feasibility and correctness of the circuit are verified through comparison of experiment and simulation. To address the limited energy harvesting efficiency of a single piezoelectric element, in this study, multiple SP-SICE circuits are connected in series to obtain a multi-input self-powered synchronous inversion charge extraction (MSP-SICE) piezoelectric energy harvesting circuit for a multimodal piezoelectric energy trap. Both experimental and simulation results show that the output voltage of the MSP-SICE circuit is 172% of the output voltage of the SP-SICE circuit with the same input source.

Optimization of the geometric parameters and structural design of a flexible thermoelectric generator for efficient energy harvesting to power wearable electronics

Optimization of the geometric parameters and structural design of a flexible thermoelectric generator for efficient energy harvesting to power wearable electronics