Search Results (315)

Wearable sensors are central to health-monitoring systems, but the limited capacity of compact batteries poses a challenge for long-term and maintenance-free operation. In this study, we investigated ambient electromagnetic wave (AEMW) energy harvesting using a human body antenna (HBA) as a means to supply power to wearable sensors. The power density and frequency distribution of AEMWs were measured in diverse indoor, outdoor, and basement environments. We designed and fabricated a flexible HBA–circuit interface electrode, optimized for broadband impedance matching when worn on the body. Experimental comparisons using a simulated AEMW source demonstrated that the HBA outperformed a conventional small whip antenna, particularly at frequencies below 300 MHz. Furthermore, the outdoor measurements indicated that the power harvested by the HBA was estimated to be −31.9 dBm (0.64 μW), which is sufficient for the intermittent operation of low-power wearable sensors and Bluetooth Low Energy modules. The electromagnetic safety was also evaluated through numerical analysis, and the specific absorption rate was confirmed to be well below the international safety limits. These findings indicate that HBA-based AEMW energy harvesting provides a practical and promising approach to achieving battery-maintenance-free wearable devices. Full article

Internet of Things (IoT) sensors designed for environmental and agricultural purposes can offer significant contributions to creating a sustainable and green environment. However, powering these sensors remains a challenge, and exploiting the temperature difference between air and soil appears to be a promising solution. For energy-harvesting technologies, accurate soil temperature profile data are needed. This study uses meteorological and soil temperature profile data collected in the Czech Republic to train machine learning models based on Polynomial Regression (PR), Support Vector Regression (SVR), and Long Short-Term Memory (LSTM) to predict the soil temperature profile. The results of the study indicate an error of 0.79 °C, which is approximately 10.9% lower than the temperature error reported in state-of-the-art studies. Beyond achieving a lower temperature prediction error, the proposed solution simplifies the input parameters of the model to only ambient temperature and solar irradiance. This improvement significantly reduces the computational costs associated with the regression model, offering a more efficient approach to predicting soil temperature for the purpose of optimizing energy harvesting in IoT sensors. Full article

This study presents an analytical and experimental approach to enhance cantilever-based piezoelectric energy harvesters by optimizing thickness distribution. Using a gradient projection algorithm within a state-space framework, the unimorph beam’s geometry is tailored while constraining the first natural frequency. The objective is to amplify axial strain within the piezoelectric layers, thereby increasing electric polarization and maximizing the conversion efficiency of mechanical vibrations into electrical energy. The steady-state response under harmonic base excitation at resonance was modeled to evaluate the harvester’s dynamic behavior against uniform-thickness counterparts. Results show that the optimized beam achieves significantly higher output voltage and energy harvesting efficiency. Simulations reveal effective strain concentration in regions of high piezoelectric sensitivity, enhancing power generation under resonant conditions. Two independent experimental setups were employed for empirical validation: a non-contact laser vibrometry system (Polytec 3D) and a first resonant base excitation setup. Eigenfrequencies matched within 5% using a Polytec multipath interferometry system, and constant excitation tests showed approximately 30% higher in optimal shapes electrical potential value generation. The outcome of this study highlights the efficacy of geometric tailoring—specifically, non-linear thickness shaping—as a key strategy in achieving enhanced energy output from piezoelectric harvesters operating at their fundamental frequency. This work establishes a practical route for optimizing unimorph structures in real-world applications requiring efficient energy capture from low-frequency ambient vibrations. Full article

The increasing demand for sustainable and renewable energy solutions has made radio frequency energy harvesting (RFEH) a promising technique for powering low-power electronic devices. RFEH captures ambient RF signals from wireless communication systems, such as mobile networks, Wi-Fi, and broadcasting stations, and converts them into usable electrical energy. This approach offers a viable alternative for battery-dependent and hard-to-recharge applications, including streetlights, outdoor night/security lighting, wireless sensor networks, and biomedical body sensor networks. This article provides a comprehensive review of the RFEH techniques, including state-of-the-art rectenna designs, energy conversion efficiency improvements, and multi-band harvesting systems. We present a detailed analysis of recent advancements in RFEH circuits, impedance matching techniques, and integration with emerging technologies such as the Internet of Things (IoT), 5G, and wireless power transfer (WPT). Additionally, this review identifies existing challenges, including low conversion efficiency, unpredictable energy availability, and design limitations for small-scale and embedded systems. A critical assessment of current research gaps is provided, highlighting areas where further development is required to enhance performance and scalability. Finally, constructive recommendations for future opportunities in RFEH are discussed, focusing on advanced materials, AI-driven adaptive harvesting systems, hybrid energy-harvesting techniques, and novel antenna–rectifier architectures. The insights from this study will serve as a valuable resource for researchers and engineers working towards the realization of self-sustaining, battery-free electronic systems. Full article

This work introduces a new type of water evaporation-driven nanogenerator (S-WEG) utilizing the natural mineral sepiolite, which capitalizes on its hierarchical nanoporous architecture and intrinsic hydrophilicity to harvest energy from ambient humidity through capillary-driven evaporation. The S-WEG, fabricated via a facile drop-coating drying method, demonstrates remarkable mechanical flexibility and sustained operational reliability. Our results demonstrate that by optimizing evaporation height and width, the S-WEG can generate a short-circuit current of ~0.6 μA and an open-circuit voltage of ~0.9 V. Through series and parallel configurations of multiple S-WEG units, the current and voltage outputs can be effectively amplified to power small-scale electronics. Full article

With the rapid rise in Internet of Things (IoT) and artificial intelligence (AI) technologies, there is an increasing need for portable, wearable, and self-powered flexible sensing devices. In such scenarios, self-powered nanogenerators have emerged as promising energy harvesters capable of converting ambient mechanical stimuli into electrical energy, enabling the development of autonomous flexible sensors and sustainable systems. This review highlights recent advances in nanogenerator technologies—particularly those based on piezoelectric and triboelectric effects—with a focus on soft, flexible, and gel-based polymer materials. Key mechanisms of energy conversion are discussed alongside strategies to enhance performance through material innovation, structural design, and device integration. Special attention is given to the role of gel-type composites, which offer unique advantages such as mechanical tunability, self-healing ability, and biocompatibility, making them highly suitable for next-generation wearable, biomedical, and environmental sensing applications. We also explore the evolving landscape of energy applications, from microscale sensors to large-area systems, and identify critical challenges and opportunities for future research. By synthesizing progress across materials, mechanisms, and application domains, this review aims to guide the rational design of high-performance, sustainable nanogenerators for the next era of energy technologies. Full article

The increasing demand for high-capacity, energy-efficient wireless networks poses significant challenges in maintaining spectral efficiency, minimizing interference, and ensuring sustainability. Traditional direct-link communication suffers from signal degradation due to path loss, multipath fading, and interference, limiting overall performance. To mitigate these challenges, this paper proposes a unified RIS framework that integrates passive and active Reconfigurable Intelligent Surfaces (RISs) for enhanced communication and ambient RF energy harvesting. Our methodology optimizes RIS-assisted beamforming using successive convex approximation (SCA) and adaptive phase shift tuning, maximizing desired signal reception while reducing interference. Passive RIS efficiently reflects signals without external power, whereas active RIS employs amplification-assisted reflection for superior performance. Evaluations using realistic urban macrocell and mmWave channel models reveal that, compared to direct links, passive RIS boosts SNR from 3.0 dB to 7.1 dB, and throughput from 2.6 Gbps to 4.6 Gbps, while active RIS further enhances the SNR to 10.0 dB and throughput to 6.8 Gbps. Energy efficiency increases from 0.44 to 0.67 (passive) and 0.82 (active), with latency reduced from 80 ms to 35 ms. These performance metrics validate the proposed approach and highlight its potential applications in urban 5G networks, IoT systems, high-mobility scenarios, and other next-generation wireless environments. Full article

The currently used electrical energy devices for portable applications are in limited life and need of frequent recharging, it is a big bottleneck for wireless and transportation systems. The scientific community is motivated to find innovative and efficient devices to convert environmental energy into useful forms. Nanogenerator can mitigate this issue by harvesting ambient energy of different forms into useful electrical energy. Particularly flexible nanogenerators can efficiently convert ambient mechanical energy into electrical energy which can be fruitfully used for self-powered sensors and electronic appliances. Zinc oxide is an interesting photosensitive and piezoelectric material that is expected to play a vital role in the synergetic harvesting of environmental thermal, sound, mechanical, and solar energies. As ZnO can be synthesized using easy methods and materials at low cost, the conversion efficiencies of solar and other energy forms can increase considerably. ZnO is a versatile material with interesting semiconducting, optical, and piezoelectric properties; it can be used advantageously to harvest more than one type of ambient energy. The coupled semiconducting and piezoelectric properties of ZnO are attractive for fabricating nanogenerators capable of harvesting both ambient optical and mechanical energies simultaneously. These nanolevel conversion devices are much required to power remote and implantable devices without the need for additional power sources. The present review briefly discusses the principles and mechanisms of different energy harvesting abilities of ZnO nanorods and their composites by consolidating available literature. In addition, the developments taking place in nanogenerators of different kinds—such as photovoltaic, piezoelectric, pyroelectric, and triboelectrics for self-powered technology—and their progress in hybrid energy harvesting application is reviewed. Full article

Mobile edge computing (MEC) systems empowered by energy harvesting (EH) significantly enhance sustainable computing capabilities for mobile devices (MDs). This paper investigates a multi-user multi-server MEC network, in which energy-constrained users dynamically harvest ambient energy to flexibly allocate resources among local computation, task offloading, or intentional task discarding. We formulate a stochastic optimization problem aiming to minimize the time-averaged weighted sum of execution delay, energy consumption, and task discard penalty. To address the energy causality constraints and temporal coupling effects, we develop a Lyapunov optimization-based drift-plus-penalty framework that decomposes the long-term optimization into sequential per-time-slot subproblems. Furthermore, to overcome the curse of dimensionality in high-dimensional action, we propose hierarchical deep reinforcement learning (DRL) solutions incorporating both Q-learning with experience replay and asynchronous advantage actor–critic (A3C) architectures. Extensive simulations demonstrate that our DRL-driven approach achieves lower costs compared with conventional model predictive control methods, while maintaining robust performance under stochastic energy arrivals and channel variations. Full article

Energy harvesting from ambient vibrations has received significant attention as an alternative renewable, clean energy source for microelectronic devices in diverse applications such as wearables and environmental monitoring. However, typical vibrations in remote environments exhibit ultra-low frequencies with variations and uncertainty leading to operation away from resonance and severe underperformance in terms of power output. Pendulum-based energy harvesters offer a promising solution to these issues, particularly when designed for parametric resonant response to driven displacement of the pendulum pivot. Parametric excitation has been shown to trigger fast rotational motion of the pendulum VEH that is beneficial for energy generation and the necessary space utilization. Nevertheless, low-frequency ambient vibrations typically come at very weak amplitudes, a fact that establishes significant design barriers when traditional gravitational pendula are used for rotary energy harvesting. In this paper, we propose a novel concept that utilizes permanent magnet arrays to establish pendulum dynamics. Extensive investigation of the restoring torque of the proposed magnetic pendulum concept is conducted with analytical tools and FEA verification. The resulting oscillator exhibits frequency tuning that is decoupled from gravity and adjustable via the circularly arranged magnetic fields, leading to increased flexibility in the concurrently necessary amplitude tuning. Numerical integration of the nondimensional equation of motion is performed in the system’s parameter space to identify the impact on the regions triggering rotational response to parametric excitation. Finally, a theoretical case study is numerically investigated with the device space constrained within 20 cm³, showing a multi-fold improvement in the achieved power density of over 600 μW/cm³/g²/Hz over a broad range of frequencies and driving amplitudes as low as 1.1 Hz at 0.2 g. Full article

Hybrid photovoltaic (PV) and thermoelectric generator (TEG) systems combine heat and light energy harvesting in a single module by utilizing the entire solar spectrum. This work analyzed the feasibility and performance of a hybrid photovoltaic–thermoelectric generator system with efficient thermal management by integrating heat pipe (HP), radiative cooling (RC), and heat sink (HS) systems. The proposed system effectively reduces the PV operation temperature by evacuating the residual heat used in the TEG system to generate an additional amount of electricity. The remaining heat is evacuated from the TEG’s cold side to the atmosphere using RC and HS systems. This study also analyzed the inclusion of two TEG arrays on both sides of the HP condenser section. This numerical analysis was performed using COMSOL Multiphysics 5.5 software and was validated by previous analysis. The performance was evaluated through an energy and exergy analysis of the TEG and PV systems. Enhancing the thermal management of the hybrid PV-TEG system can increase energy production by 2.4% compared to a PV system operating under the same ambient and solar radiation conditions. Furthermore, if the proposed system includes a second array of TEG modules, the energy production increases by 5.8% compared to the PV system. The exergy analysis shows that the enhancement in the thermal management of the PV operating temperature decreases the thermal exergy efficiency of the proposed system but increases the electricity exergy efficiency. Including TEG modules on both sides of the condenser section of the HP shows the system’s best thermal and electrical performance. These results may be helpful for the optimal design of realistic solar-driven hybrid systems for globally deserted locations. Full article

In recent years, with the growing interest in the Internet of Things (IoT) and decarbonization, energy harvesting has been attracting attention. Energy harvesting is a technology that converts ambient energy such as light, heat, and vibration into electrical power, and it is also known as environmental power generation. A triboelectric nanogenerator is a type of energy harvesting device that converts mechanical energy, such as vibration, into electrical energy using the triboelectric effect and electrostatic induction. The advantages of this device include low cost and high durability. Due to the principle of triboelectric nanogenerators, a stable output voltage cannot be obtained, so auxiliary circuits such as DC–DC converters are required to obtain the desired voltage. In this paper, a DC–DC converter is utilized, controlled by a system based on operator theory, with a filter incorporated to enhance tracking performance, ensuring that the output voltage follows the target value. Full article

As the energy crisis is leading to energy shortages and constant increases in prices, green energy and renewable energy sources are trending as a viable solution to this problem. One of the most rapidly expanding green energy methods is RF (RadioFrequency) energy harvesting, as RF energy and its corresponding technologies are constantly progressing, due to the introduction of 5G and high-speed telecommunications. The usual system for RF energy harvesting is called a rectenna, and one of its main components is an antenna, responsible for collecting ambient RF energy. In this paper, the optimization process of an ultra-wideband antenna for RF energy harvesting applications was studied, with the main goal of broadening the antenna’s operational bandwidth to include 5G New Radio. For this purpose, the Bezier Search Differential Evolution Algorithm (BeSD) was used along with a novel CST-Matlab API, to manipulate the degrees of freedom of the antenna, while searching for the optimal result, which would satisfy all the necessary dependencies to make it capable of harvesting RF energy in the target frequency band. The BeSD algorithm was first tested with benchmark functions and compared to other widely used algorithms, which it successfully outperformed, and hence, it was selected as the optimizer for this research. All in all, the optimization process was successful by producing an ultra-wideband optimal antenna operating from 1.4 GHz to 3.9 GHz, which includes all vastly used telecommunication technologies, like GSM (1.8 GHz), UMTS (2.1 GHz), Wi-Fi (2.4 GHz), LTE (2.6 GHz), and 5G NR (3.5 GHz). Its ultra-wideband properties and the rest of the characteristics that make this design suitable for RF energy harvesting are proven by its $S_{11}$ response graph, its impedance response graph, its efficiency on the targeted technologies, and its omnidirectionality across its band of operation. Full article

The authors present an in-depth theoretical study of two nonlinear circuits capable of transient thermal energy harvesting at one temperature. The first circuit has a storage capacitor and diode connected in series. The second circuit has three storage capacitors, and two diodes arranged for full wave rectification. The authors solve both Ito–Langevin and Fokker–Planck equations for both circuits using a large parameter space including capacitance values and diode quality. Surprisingly, using diodes one can harvest thermal energy at a single temperature by charging capacitors. However, this is a transient phenomenon. In equilibrium, the capacitor charge is zero, and this solution alone satisfies the second law of thermodynamics. The authors found that higher quality diodes provide more stored charge and longer lifetimes. Harvesting thermal energy from the ambient environment using diode nonlinearity requires capacitors to be charged but then disconnected from the circuit before they have time to discharge. Full article

While vibration harvesting shows promise for powering sensors, effectively harvesting low-frequency, multidirectional ambient vibrations remains challenging. This article presents a novel electromagnetic vibration energy harvesting device (EVEHD) with three key innovations: a dual-mode mass-pendulum configuration—dual-mass coupling (series mode) amplifies induced voltage, and dual-mass uncoupled (parallel) mode enables multifrequency harvesting—spring-position-based frequency tuning (4.5–16.7 Hz in series mode; dual-band 3.7–9.3/5–13.3 Hz in parallel mode), and an optimized energy conversion structure, boosting output by 85.2%. The findings were validated through theoretical modeling, FEM simulations, and shaker tests, the EVEHD generating a maximum voltage of 2 V and a power of 769.2 mW under a base excitation amplitude of 0.5 g at 16.7 Hz. This work reveals the potential of this multidirectional EVEHD for power generation and application in self-powered systems. Full article