Abstract
Electric field energy harvesters (EFEHs) are reliable and sustainable power sources that may be used to power wireless sensor nodes (WSNs) in urban Internet of Things (IoT) networks, replacing traditional batteries. Despite the technology's effectiveness, large-scale deployments raise severe environmental concerns about fabrication material degradation and recycling. In this context, this work analyzes the performance of the natural green leaves as a replacement for standard electrodes in EFEH developments. To this end, different 10× 3 cm2 EFEHs were assembled with raw leaves from the following species Magnolia Obovata, Ravenala Madagascariensis, Acanthus Mollis, and Agapanthus Africanus. Each harvester was evaluated at different drying steps, concluding that natural leaves may collect electrostatic charges related to the urban electric field, which might power ultra-low-energy devices. Experimental results reveal that Agapanthus Africanus electrodes perform best, with an open-circuit voltage (VOC) of 111.88 V and a short-circuit current (ISC) of 229.09 nA. On the other hand, the VOC of Magnolia Obavata leaves achieved 76.76 V, and the ISC was 135.30 nA (the worst case). Although the performance for Ravenala Madagascariensis samples is less than Agapanthus Africanus ones, the size leaf is another critical parameter to design functional devices. Therefore, the experimental section also includes the conceptualization, design, and experimental testing of a functional EFEH prototype called Leaf-EFEH, which is assembled with Ravenala Madagascariensis leaves. Finally, numerous experiments have shown that the proposed Leaf-EFEH can power ultra-low-power devices.
Original language | English |
---|---|
Pages (from-to) | 158852-158861 |
Number of pages | 10 |
Journal | IEEE Access |
Volume | 9 |
DOIs | |
Publication status | Published - 23 Nov 2021 |
Keywords
- Capacitance transducers
- Electromagnetic coupling
- Electromagnetic induction
- Energy harvesting
- Home area network
ASJC Scopus subject areas
- General Computer Science
- General Materials Science
- General Engineering