Recent Progress in the Energy Harvesting Technology—From Self-Powered Sensors to Self-Sustained IoT, and New Applications

Ling, Liansheng; Guo, Xinzhuan; Liu, Weixin; Lee, Chengkuo

doi:10.3390/nano11112975

Cited by 90 publications

(53 citation statements)

References 321 publications

(423 reference statements)

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“…In recent years kinetic energy harvesting from the human body and machinery-induced vibration motion is in extensive research aimed at providing sustainable power for portable wearable electronics, healthcare sensors, IoT's, and self-powered sensor networks. [1][2][3][4][5] In kinetic energy technology has been verified. [27][28][29] However, the triboelectric property of siloxene and polymer composites is not revealed yet.…”

Section: Introductionmentioning

confidence: 93%

“…In recent years kinetic energy harvesting from the human body and machinery‐induced vibration motion is in extensive research aimed at providing sustainable power for portable wearable electronics, healthcare sensors, IoT's, and self‐powered sensor networks. [ 1–5 ] In kinetic energy harvesting research various transduction principles are practically/theoretically verified and demonstrated such as electromagnetic, [ 6,7 ] piezoelectric, [ 8,9 ] and triboelectric [ 9–26,36,37,42,43,47–61 ] methods. Among these methods, triboelectric nanogenerators (TENG) based on the basic principle of contact electrification and electrostatic induction are contrived as the highly efficient sustainable power alternatives and effective platforms for self‐powered sensing owing to the high voltage feature (at low frequency), low cost, lightweight, wearability, and boundless material choices.…”

Section: Introductionmentioning

confidence: 99%

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Siloxene/PVDF Composite Nanofibrous Membrane for High‐Performance Triboelectric Nanogenerator and Self‐Powered Static and Dynamic Pressure Sensing Applications

Bhatta

Sharma

Shrestha

et al. 2022

Adv Funct Materials

101

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Polymer nanofibers are widely adopted in energy harvesting and pressure sensing applications owing to the large contact area and inherent compressibility. Herein, a high-performance triboelectric nanogenerator (TENG) based on 2D siloxene-polyvinylidene fluoride (S-PVDF) composite nanofibrous membrane is newly evaluated. Through proper ratio optimization and facile electrospinning, the fabricated membrane shows significant improvement in dielectric property, electronegativity, and compressibility. The TENG comprising S-PVDF membrane and Nylon 6/6 can deliver an excellent power density of 13.25 W m −2 (f ≈ 5 Hz) and easily operates low-power electronics and Internet of things (IoTs). In addition, the excellent compressibility of membrane extends its applicability to self-powered simultaneous detection of dynamic and static pressure, which is investigated by developing a hybrid pressure sensor (HPS) through effective integration of TENG and a capacitive pressure sensor. The HPS shows an excellent dynamic (12.062 V kPa −1 at (<3 kPa) and 2.58 V kPa −1 at (3-25 kPa)) and static (25.07 mV kPa −1 at (<3 kPa) and 5.96 mV kPa −1 at (3-25 kPa)) pressure sensitivities, respectively. Furthermore, a 2 × 2 HPS array tested and analyzed for multiple users using artificial intelligence significantly improves the accuracy (98%). Remarkable energy harvesting performance and greater accuracy of the HPS manifests better preferences for future self-powered IoT and smart tactile-based user authentication systems.

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Section: Introductionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Siloxene/PVDF Composite Nanofibrous Membrane for High‐Performance Triboelectric Nanogenerator and Self‐Powered Static and Dynamic Pressure Sensing Applications

Bhatta

Sharma

Shrestha

et al. 2022

Adv Funct Materials

101

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“…Moreover, by adopting an energy-harvesting solution, the energy of the system can be kept available to carry out the assigned tasks in real time and continuously, which remains challenging for different applications, such as in the case of real-time and continuous pulse monitoring [79], motion tracking [80], exoskeleton manipulation [81] and the maintenance and monitoring of implantable devices [82]. To this end, providing continuous and efficient power supply to wearable and implantable devices presents a highly addressed challenge in recent research [83][84][85]. As part of this, integrating energy-harvesting technologies with taskoffloading approaches allows end devices to endure for a long time to support long-term task processing [86][87][88].…”

Section: Energy Consumption Of Wireless Nodesmentioning

confidence: 99%

Requirements for Energy-Harvesting-Driven Edge Devices Using Task-Offloading Approaches

et al. 2022

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Energy limitations remain a key concern in the development of Internet of Medical Things (IoMT) devices since most of them have limited energy sources, mainly from batteries. Therefore, providing a sustainable and autonomous power supply is essential as it allows continuous energy sensing, flexible positioning, less human intervention, and easy maintenance. In the last few years, extensive investigations have been conducted to develop energy-autonomous systems for the IoMT by implementing energy-harvesting (EH) technologies as a feasible and economically practical alternative to batteries. To this end, various EH-solutions have been developed for wearables to enhance power extraction efficiency, such as integrating resonant energy extraction circuits such as SSHI, S-SSHI, and P-SSHI connected to common energy-storage units to maintain a stable output for charge loads. These circuits enable an increase in the harvested power by 174% compared to the SEH circuit. Although IoMT devices are becoming increasingly powerful and more affordable, some tasks, such as machine-learning algorithms, still require intensive computational resources, leading to higher energy consumption. Offloading computing-intensive tasks from resource-limited user devices to resource-rich fog or cloud layers can effectively address these issues and manage energy consumption. Reinforcement learning, in particular, employs the Q-algorithm, which is an efficient technique for hardware implementation, as well as offloading tasks from wearables to edge devices. For example, the lowest reported power consumption using FPGA technology is 37 mW. Furthermore, the communication cost from wearables to fog devices should not offset the energy savings gained from task migration. This paper provides a comprehensive review of joint energy-harvesting technologies and computation-offloading strategies for the IoMT. Moreover, power supply strategies for wearables, energy-storage techniques, and hardware implementation of the task migration were provided.

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“…Therefore, several efforts have been made by the scientific community over the past decades by exploring sustainable, renewable, and green energy sources to fulfill the future demand of energy in an effective and environment-friendly way. Besides this, with the forthcoming Internet of things(IoT) and artificial intelligence era, the need for smart electronics with multiple functionalities, portable, flexible, and miniaturization concepts are highly desirable ( Liu et al., 2019 , 2021a , 2021b ). Till now, most of the energy requirements in the electronic devices are fulfilled by the batteries even though it endows several drawbacks due to their short life span, durability, short charging/discharging, heavyweight, rigid, bulky, and overheating nature ( Armand and Tarascon, 2008 ; Van Noorden, 2014 ).…”

Section: Introductionmentioning

confidence: 99%

Recent trends in 2D materials and their polymer composites for effectively harnessing mechanical energy

Rana

Singh

2022

iScience

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Summary Self-powered wearable devices, with the energy harvester as a source of energy that can scavenge the energy from ambient sources present in our surroundings to cater to the energy needs of portable wearable electronics, are becoming more widespread because of their miniaturization and multifunctional characteristics. Triboelectric and piezoelectric nanogenerators are being explored to harvest electrical energy from the mechanical vibrations. Integration of these two effects to fabricate a hybrid nanogenerator can further enhance the output efficiency of the nanogenerator. Here, we have discussed the importance of 2D materials which plays an important role in the fabrication of nanogenerators because of their distinct characteristics, such as, flexibility, mechanical stability, nontoxicity, and biodegradability. This review mainly emphasizes the piezoelectric, triboelectric, and hybrid nanogenerator based on the 2D materials and their van der Waals heterostructure, as well as the effect of polymer-2D composite on the output performance of the nanogenerator.

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Recent Progress in the Energy Harvesting Technology—From Self-Powered Sensors to Self-Sustained IoT, and New Applications

Cited by 90 publications

References 321 publications

Siloxene/PVDF Composite Nanofibrous Membrane for High‐Performance Triboelectric Nanogenerator and Self‐Powered Static and Dynamic Pressure Sensing Applications

Siloxene/PVDF Composite Nanofibrous Membrane for High‐Performance Triboelectric Nanogenerator and Self‐Powered Static and Dynamic Pressure Sensing Applications

Requirements for Energy-Harvesting-Driven Edge Devices Using Task-Offloading Approaches

Recent trends in 2D materials and their polymer composites for effectively harnessing mechanical energy

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