Energy Harvesting Opportunities Research Articles

Biomimetic Redox Capacitor To Control the Flow of Electrons.

In biological systems, electrons, energy, and information "flow" through the redox modality, and we ask, does biology have redox capacitor capabilities for storing electrons? We describe emerging evidence indicating that biological phenolic/catecholic materials possess such redox capacitor properties. We further describe results that show biomimetic catecholic materials are reversibly redox-active with redox potentials in the midphysiological range and can repeatedly accept electrons (from various reductants), store electrons, and donate electrons (to various oxidants). Importantly, catechol-containing films that are assembled onto electrode surfaces can enhance the flow of electrons, energy, and information. Further, catechol-containing films can serve as redox-based interactive materials capable of actuating biological responses by turning on gene expression from redox-responsive genetic circuits. Looking forward, we envision that the emerging capabilities for measuring dynamic redox processes and reversible redox states will provide new insights into redox biology and will also catalyze new technological opportunities for information processing and energy harvesting.

Enhanced near-field radiative heat transfer between borophene sheets on different substrates

Abstract Near-field radiative heat transfer (NFRHT) has the potential to exceed the blackbody limit by several orders of magnitude, offering significant opportunities for energy harvesting. In this study, we have examined the NFRHT between two borophene sheets through the calculation of heat transfer coefficient (HTC). Due to the tunneling of evanescent waves, borophene sheet allows for enhanced heat flux and adjustable NFRHT by varying its electron density and electron relaxation time. Additionally, the near field coupling is further examined when the borophene is deposited on dielectric or lossy substrates. The maximum HTC is closely related to the real part of the dielectric substrate. As a case study, the HTC on the lossy substrate of MoO3, ZnSe and SiC are calculated for comparison. Our results indicate that MoO3 is the optimal substrate to get the enhanced energy transfer coefficient. It results in a remarkable value of 1737 times higher than the blackbody limit owing to the enhanced photon tunneling probability. Thus, our study reveals the effect of substrate on the HTC between borophene sheets and provides a theoretical guidance for the design of near-field thermal radiation devices.

A space-adiabatic theorem for longitudinal and transversal wave motion analysis of graded metamaterials

The use of graded metamaterials is widespread in the fields of wave manipulation and energy harvesting. However, they have the drawback of causing energy scattering after a certain period due to wave reflection or trapping, known as the rainbow effect, in some cases. To address this issue, we extend the adiabatic theorem to the spatial modulation field to mitigate the impact of the rainbow effect, thereby enhancing transmission at the interface of graded metamaterials. Firstly, an analytical expression for the limiting gradient in the space-adiabatic theorem is derived. Then, it is applied to study the longitudinal wave motion in a spring-mass with graded resonators (SMGR) system and the transversal wave motion in a beam with graded resonators (BGR) system. The numerical study demonstrates that if the spatial gradient of system properties is small enough to satisfy the adiabatic theorem, wave scattering can almost be neglected, and transmission will experience a significant increase compared to the non-adiabatic case. Finally, the critical boundary between adiabatic and non-adiabatic cases is determined using the fitting method. This study introduces a design strategy for graded metamaterials, offering opportunities for communication, sensing, energy harvesting, and various other applications.

Si/InAs/Ag metamaterial for strong nonreciprocal thermal emitter with dual polarization under a 0.9 T magnetic field

The current nonreciprocal thermal emitter has been proven to completely violate the previous Kirchhoff's law. And the majority of related nonreciprocal devices operate under single polarization with few dual-polarization nonreciprocal designs. Therefore, dual-polarization nonreciprocal thermal radiation has great research prospects. In addition, many previous designs of nonreciprocal devices required external magnetic field energy of 3 T even higher, which is difficult to meet in practical applications. Therefore, this article investigates the strong nonreciprocal dual-polarization thermal radiation of cuboid arrays under lower external magnetic field. It is constructed by silicon, silver layer, InAs layer, and cuboid arrays. Finally, dual-polarization nonreciprocal radiation was achieved in a magnetic field of only 0.9 T, and the nonreciprocal efficiency has been significantly improved. The physical phenomenon of dual-polarization strong nonreciprocal radiation exhibited by the proposed device was explained by utilizing the electromagnetic field distribution at the resonant wavelength. It can also maintain good nonreciprocal properties under different structural parameters. Therefore, our proposed solution provides new opportunities for energy harvesting and thermal radiation control.

Development of an Ocean Wave Energy Harvester using an Array of Flexible Piezoelectric Sensors

The ocean offers vast opportunities for unprecedented energy harvesting where most studies had concentrated on large scale energy harvesting from the ocean waves. However, there were minimal studies on low-scale energy harvesting. This study focuses on ambient, low-scale energy harvesting which theoretically can be used to power low energy consumption electrical appliances. The inherent characteristic of piezoelectric materials which can convert mechanical energy to electrical energy has created an alternative to generate energy from renewable sources including ocean waves. Initially, this study started with preliminary work which consisted of the development and testing of a lab scale piezoelectric energy harvester (PEH-1) which was tested along the beach area of Kuala Nerus, east coast of Malaysia. Results from PEH-1 had shown that the high tide produced more power level compared to low tide experiments. The findings from the first phase of this study served as a foundation study towards the development of an upscaled version of the PEH-1 in relation of mechanical and electronics, which was termed as PEH-2. Testing for PEH-2 was conducted in the coastal area of Pulau Bidong Laut, Kuala Nerus. Results from the second part of the study had shown that approximately almost 80% of the power harvested correlated linearly with wind speed, however after reaching 0.7W the peak dips down which was probably due to the instability of PEH-2 to be used in harsh open seas environment. This study had shown the feasibility of utilizing piezoelectric material to harvest low-scale power, however, several in-house modifications needed to be made for it to be fully functionable.

Energy Harvesting Opportunities in Geoenvironmental Engineering

Geoenvironmental engineering involves defining solutions for complex problems, such as containment systems management, contaminant transport control, wastewater management, remediation of contaminated sites and valorization of geomaterials and wastes. In the last years, energy harvesting (EH)—or energy scavenging—methods and technologies have been developed to reduce the dependence on traditional energy sources, namely fossil fuels, and nuclear power, also responding to the increase in energy demands for human activities and to fulfill sustainable development goals. EH in geoenvironmental works and the surrounding soil and water environment includes a set of processes for capturing and accumulating energy from several sources considered wasted or unusable associated with soil dynamics; the stress and strain of geomaterials, hydraulic, vibrations, biochemical, light, heating and wind sources can be potential EH systems. Therefore, this work presents a review of the literature and critical analysis on the main opportunities for EH capturing, accumulating and use in geoenvironmental works, among basic electric concepts and mechanisms, analyzing these works in complex conditions involving biological-, chemical-, mechanical-, hydraulic- and thermal-coupled actions, concluding with the main investigation and challenges within geoenvironmental aspects for EH purposes.

Self-Starting Characteristics and Flow-Induced Rotation of Single- and Dual-Stage Vertical-Axis Wind Turbines

Despite offering promising opportunities for wind energy harvesting in urban environments, vertical axis wind turbines face limitations in terms of poor starting characteristics. In this study, we focus on analyzing improvements offered by dual-stage turbines for a range of wind velocities. Numerical simulations are performed for different phase angles between the rotors (a measure of relative angular positions of the blades in the two rotors) to quantify the response time for their starting behavior. These simulations rely on a through sliding mesh technique coupled with flow-induced rotations. We find that for U∞=4m/s, the phase angles of 30∘ and 90∘ substantially reduce starting time in comparison to a single-stage turbine. Dual-stage turbines with a phase angle of 90∘ exhibit similar or better starting behavior for other wind speeds. The phase angle of 0∘ in double-rotor turbines shows the poorest starting response. Moreover, it is revealed that stabilization of shear layers generated by the blades passing through the windward side of the turbine, vortex-entrapment by these rotating blades, and suppressing of flow structures in the middle of the wake enhance the capacity of VAWTs to achieve faster steady angular speed.

Opportunistic soaring by birds suggests new opportunities for atmospheric energy harvesting by flying robots.

The use of flying robots (drones) is increasing rapidly, but their utility is limited by high power demand, low specific energy storage and poor gust tolerance. By contrast, birds demonstrate long endurance, harvesting atmospheric energy in environments ranging from cluttered cityscapes to open landscapes, coasts and oceans. Here, we identify new opportunities for flying robots, drawing upon the soaring flight of birds. We evaluate mechanical energy transfer in soaring from first principles and review soaring strategies encompassing the use of updrafts (thermal or orographic) and wind gradients (spatial or temporal). We examine the extent to which state-of-the-art flying robots currently use each strategy and identify several untapped opportunities including slope soaring over built environments, thermal soaring over oceans and opportunistic gust soaring. In principle, the energetic benefits of soaring are accessible to flying robots of all kinds, given atmospherically aware sensor systems, guidance strategies and gust tolerance. Hence, while there is clear scope for specialist robots that soar like albatrosses, or which use persistent thermals like vultures, the greatest untapped potential may lie in non-specialist vehicles that make flexible use of atmospheric energy through path planning and flight control, as demonstrated by generalist flyers such as gulls, kites and crows.

Limit cycles and chaos induced by a nonlinearity with memory

Inspired by the observation of a distributed time delay in the nonlinear response of an optical resonator, we investigate the effects of a similar delay on a noise-driven mechanical oscillator. For a delay time that is commensurate with the inverse dissipation rate, we find stable limit cycles. For longer delays, we discover a regime of chaotic dynamics associated with a double scroll attractor. We also analyze the effects of time delay on the spectrum and oscillation amplitude of the oscillator. Our results point to new opportunities for nonlinear energy harvesting, provided that a nonlinearity with distributed time delay can be implemented in mechanical systems.

Wearable Self‐Powered Electrochemical Devices for Continuous Health Management

AbstractThe wearable revolution is already present in society through numerous gadgets. However, the contest remains in fully deployable wearable (bio)chemical sensing. Its use is constrained by the energy consumption which is provided by miniaturized batteries, limiting the autonomy of the device. Hence, the combination of materials and engineering efforts to develop sustainable energy management is paramount in the next generation of wearable self‐powered electrochemical devices (WeSPEDs). In this direction, this review highlights for the first time the incorporation of innovative energy harvesting technologies with top‐notch wearable self‐powered sensors and low‐powered electrochemical sensors toward battery‐free and self‐sustainable devices for health and wellbeing management. First, current elements such as wearable designs, electrochemical sensors, energy harvesters and storage, and user interfaces that conform WeSPEDs are depicted. Importantly, the bottlenecks in the development of WeSPEDs from an analytical perspective, product side, and power needs are carefully addressed. Subsequently, energy harvesting opportunities to power wearable electrochemical sensors are discussed. Finally, key findings that will enable the next generation of wearable devices are proposed. Overall, this review aims to bring new strategies for an energy‐balanced deployment of WeSPEDs for successful monitoring of (bio)chemical parameters of the body toward personalized, predictive, and importantly, preventive healthcare.

From colloidal particles to photonic crystals: advances in self-assembly and their emerging applications.

Over the last three decades, photonic crystals (PhCs) have attracted intense interests thanks to their broad potential applications in optics and photonics. Generally, these structures can be fabricated via either "top-down" lithographic or "bottom-up" self-assembly approaches. The self-assembly approaches have attracted particular attention due to their low cost, simple fabrication processes, relative convenience of scaling up, and the ease of creating complex structures with nanometer precision. The self-assembled colloidal crystals (CCs), which are good candidates for PhCs, have offered unprecedented opportunities for photonics, optics, optoelectronics, sensing, energy harvesting, environmental remediation, pigments, and many other applications. The creation of high-quality CCs and their mass fabrication over large areas are the critical limiting factors for real-world applications. This paper reviews the state-of-the-art techniques in the self-assembly of colloidal particles for the fabrication of large-area high-quality CCs and CCs with unique symmetries. The first part of this review summarizes the types of defects commonly encountered in the fabrication process and their effects on the optical properties of the resultant CCs. Next, the mechanisms of the formation of cracks/defects are discussed, and a range of versatile fabrication methods to create large-area crack/defect-free two-dimensional and three-dimensional CCs are described. Meanwhile, we also shed light on both the advantages and limitations of these advanced approaches developed to fabricate high-quality CCs. The self-assembly routes and achievements in the fabrication of CCs with the ability to open a complete photonic bandgap, such as cubic diamond and pyrochlore structure CCs, are discussed as well. Then emerging applications of large-area high-quality CCs and unique photonic structures enabled by the advanced self-assembly methods are illustrated. At the end of this review, we outlook the future approaches in the fabrication of perfect CCs and highlight their novel real-world applications.

Intelligent Ubiquitous Network Accessibility for Wireless-Powered MEC in UAV-Assisted B5G

Providing the ubiquitous network accessibility is the key goal for 5G and Beyond 5G (B5G) networks. As the number of devices and data increase, ensuring the Quality of Service(QoS) by the existing network with a singular focus could be challenging. Meanwhile, it always is of the utmost importance to perform the computation-intensive or delay-sensitive tasks welland provide long-term services for the B5G networks. To tackle these challenges, we present an air-ground integrated network in B5G wireless communications, where an UAV is deployed as an aerial radio access platform to formulate system strategy intelligently, as well as provide task offloading and energy harvesting opportunities for terrestrial devices. To get more insight of it, we propose an intelligent charging-offloading scheme and formulate the joint multi-taskcharging-offloading scheduling as an optimization problem aiming to minimizing the system servicelatency of all devices by jointly optimizing the task offloading decisions, connection scheduling, charging and computation resources allocation of UAV. However, the formulated optimization problem is a Mixed-Integer Nonlinear Programming (MINLP) problem which is challenging to solve in general. Therefore, we decompose it into multiple convex sub-problems based on Block-Coordinate Descent (BCD) method and develop an improved greedy algorithm to obtain a feasible optimal solution. To validate the proposed algorithm, it is comprehensively compared with several existing schemes. Performance evaluation demonstrates that our scheme outperforms the benchmarks in terms of the system service latency of all UDs. Moreover, we represent the system working process and the paradigm of industrial applications.

Self-sensing piezoelectric bistable laminates for morphing structures

Bistable laminates offer opportunities for shape morphing, energy harvesting, and flow control devices. Smart materials such as piezoelectric macrofiber composites and shape memory alloys have been embedded in bistable laminates to actuate or harvest energy. However, sensor systems capable of measuring bistable shapes and snap-through events are lacking. In this paper, we present curved bistable laminates layered with piezoelectric PVDF films that can sense smooth shape changes as well as abrupt snap-through transitions. Near-static measurement is facilitated by a drift compensated charge amplifier with a large time constant that converts the sensor’s charge output into a measurable voltage with minimal drift error. The sensing function is demonstrated on mechanically-prestressed bistable laminates. The laminated composites include two sensor layers such that one measures the changes in curvature and the other measures snap-through events. An analytical model is presented in which strains and curvatures calculated using a laminated-plate model are fed into a linear piezoelectric model to calculate voltage. Shapes measured by the sensors correlate well with shapes measured using a 3D motion capture system. A model-based analysis is performed to understand the laminates’ design space.

The Road to Practical E-Textiles Is Smooth as Silk

The work of Zhang et al. describes a method for 3D-printing a triboelectric generator composed of silk fibroin (SF) and a conductive core of carbon nanotubes (CNT). The resulting SF@CNT fibers offer a roadmap toward energy harvesting fabrics within E-textiles.

Multi-Dimensional Sparse-Coded Ambient Backscatter Communication for Massive IoT Networks

In this paper, we propose a multi-dimensional sparse-coded ambient backscatter communication (MSC-AmBC) system for long-range and high-rate massive Internet of things (IoT) networks. We utilize the characteristics of the ambient sources employing orthogonal frequency division multiplexing (OFDM) modulation to mitigate strong direct-link interference and improve signal detection of AmBC at the reader. Also, utilization of the sparsity originated from the duty-cycling operation of batteryless RF tags is proposed to increase the dimension of signal space of backscatter signals to achieve either diversity or multiplexing gains in AmBC. We propose optimal constellation mapping and reflection coefficient projection and expansion methods to effectively construct multi-dimensional constellation for high-order backscatter modulation while guaranteeing sufficient energy harvesting opportunities at these tags. Simulation results confirm the feasibility of the long-range and high-rate AmBC in massive IoT networks where a huge number of active ambient sources and passive RF tags coexist.

Internet of Hybrid Energy Harvesting Things

Internet of Things (IoT) is a perfect candidate to realize efficient observation and management for Smart City concept. This requires deployment of large number of wireless devices. However, replenishing batteries of thousands, maybe millions of devices may be hard or even impossible. In order to solve this problem, Internet of Energy Harvesting Things (IoEHT) is proposed. Although the first studies on IoEHT focused on energy harvesting (EH) as an auxiliary power provisioning method, now completely battery-free and self-sufficient systems are envisioned. Taking advantage of diverse sources that the concept of Smart City offers helps us to fully appreciate the capacity of EH. In this way, we address the primary shortcomings of IoEHT; availability, unreliability, and insufficiency by the Internet of Hybrid EH Things (IoHEHT). In this paper, we survey the various EH opportunities, propose an hybrid EH system, and discuss energy and data management issues for battery-free operation. We mathematically prove advantages of hybrid EH compared to single source harvesting as well. We also point out to hardware requirements and present the open research directions for different network layers specific to IoHEHT for Smart City concept.

Traffic-Aware Optimal Spectral Access in Wireless Powered Cognitive Radio Networks

Traffic patterns associated with different primary users (PUs) might provide different spectral access and energy harvesting opportunities to secondary users (SUs) in wireless powered cognitive radio networks (WP-CRNs). Since the traffic applications have their own distinctive patterns, spectral access and energy harvesting opportunities are also expected to be distinctive. In this paper, we propose a novel approach to identify the PU traffic patterns and estimate the energy harvested from each traffic pattern so that SU can maximize its capacity accordingly. More specifically, we propose a theoretical framework based on a variational inference algorithm to cluster various traffic patterns and design a threshold-based SU transmission strategy by taking into account the spectral access and energy harvesting opportunities for each traffic pattern, so as to optimize SU transmission. Through simulations, we demonstrate the effectiveness of the proposed scheme in terms of throughput gains and show the transmission thresholds under various traffic applications (patterns). Further, we illustrate the effects of different collision costs on throughput for different traffic applications using real wireless traces.

Dynamic threshold-setting for RF-powered cognitive radio networks in non-Gaussian noise

The increasing demand for spectral and energy efficient communication networks has drawn an upsurge of interest in frequency (RF) energy harvesting (EH) cognitive radio networks (CRNs), and the spectrum analyzer is the brain to provide different spectral access and energy harvesting opportunities in wireless-powered cognitive radio networks (WP-CRNs). The performance of detecting the existence of primary signals will be more crucial for the EH node. However, to the best of our knowledge, no dynamic threshold-setting method to achieve target detection performance, particularly in the practical non-Gaussian noise, is reported in the literature. Traditional assumption of additive white Gaussian noise (AWGN) fails to model the behavior of certain types of noise found in practice.In this paper we give a dynamic threshold-setting method to detect the existence of primary signals for the energy harvesting node in non-Gaussian noise background. Combined with the fractional lower order statistics (FLOS), we propose a weighting factor for dynamic threshold-setting to exploit the existence of the PU to harvest RF energy, namely weighting factor based fractional lower order moment (WF-FLOM) detector. Numerical simulation results verify that the proposed method is effective for the EH node, when the signal-to-noise ratio is low or the back ground noise varies.

Bimodal phase separated block copolymer/homopolymer blends self-assembly for hierarchical porous metal nanomesh electrodes.

Transparent conducting electrodes (TCEs) are essential components in various optoelectronic devices. Nanostructured metallic thin film is one of the promising candidates to complement current metal oxide films, such as ITO, where high cost rare earth elements have been a longstanding issue. Herein, we present that multiscale porous metal nanomesh thin films prepared by bimodal self-assembly of block copolymer (BCP)/homopolymer blends may offer a new opportunity for TCE. This hierarchical concurrent self-assembly consists of macrophase separation between BCP and homopolymer as well as microphase separation of BCP, and thus provides a straightforward spontaneous production of a highly porous multiscale pattern over an arbitrary large area. Employing a conventional pattern transfer process, we successfully demonstrated a multiscale highly porous metallic thin film with reasonable optical transparency, electro-conductance, and large-area uniformity, taking advantage of low loss light penetration through microscale pores and significant suppression of light reflection at the nanoporous structures. This well-defined controllable bimodal self-assembly can offer valuable opportunities for many different applications, including optoelectronics, energy harvesting, and membranes.

Energy-Arrival-Aware Detection Threshold in Wireless-Powered Cognitive Radio Networks

Traffic patterns associated with different primary user (PU) channels may provide different spectral access and energy harvesting opportunities in wireless-powered cognitive radio networks (WP-CRNs). Considering this, we propose traffic-specific optimal spectrum sensing policy such that the expected transmission rate of secondary user (SU) is maximized under the energy causality and PU collision constraints in orthogonal frequency-division multiple access (OFDMA)-based WP-CRN. Toward this, we cluster $N$ subcarriers (subchannels) into $K$ clusters (where $K \leq N$ ) and derive an optimal energy detection threshold for the SU under each traffic pattern. Using traffic features, we propose an unsupervised and nonparametric classification technique to determine the number of unique traffic patterns $K$ over all subchannels. Then, the traffic patterns are used to predict the idle/busy period statistics for subchannels, based upon which SU identifies harvest and transmit PU subchannels for energy harvesting and data transmission, respectively. We derive an optimal detection threshold based on the harvested energy such that it maximizes the expected transmission rate of SU while protecting PU from collision. We demonstrate the effectiveness of the proposed scheme in terms of rate gains under design constraints and show the optimal detection threshold under various energy arrival rates.