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Harvesting Wireless Power: Survey of Energy-Harvester Conversion Efficiency in Far-Field, Wireless Power Transfer Systems

·2014·IEEE Microwave Magazine

Abstract

The idea of wireless power transfer (WPT) has been around since the inception of electricity. In the late 19th century, Nikola Tesla described the freedom to transfer energy between two points without the need for a physical connection to a power source as an "all-surpassing importance to man". A truly wireless device, capable of being remotely powered, not only allows the obvious freedom of movement but also enables devices to be more compact by removing the necessity of a large battery. Applications could leverage this reduction in size and weight to increase the feasibility of concepts such as paper-thin, flexible displays, contact-lens-based augmented reality, and smart dust, among traditional point-to-point power transfer applications. While several methods of wireless power have been introduced since Tesla's work, including near-field magnetic resonance and inductive coupling, laser-based optical power transmission, and far-field RF/microwave energy transmission, only RF/microwave and laser-based systems are truly long-range methods. While optical power transmission certainly has merit, its mechanisms are outside of the scope of this article and will not be discussed.

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Metadata

Venue
IEEE Microwave Magazine
Published
2014-06
Volume
15
Issue
4
Pages
108-120
ISSN
1527-3342 (ISSN-L)
OpenAlex
W1922569449
Cited by
857
References
0
FWCI
30.25
Type
journal article
Language
en
Open access
closed

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Harvesting Wireless Power: Survey of Energy-Harvester Conversion Efficiency in Far-Field, Wireless Power Transfer Systems. (2014). IEEE Microwave Magazine. https://doi.org/10.1109/mmm.2014.2309499

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.