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Cited by 5,576

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Wireless Power Transfer via Strongly Coupled Magnetic Resonances

Kurs, André, Karalis, Aristeidis, Moffatt, Robert, Joannopoulos, J. D., Fisher, Peter, Soljačić, Marin·2007·Science

Abstract

Using self-resonant coils in a strongly coupled regime, we experimentally demonstrated efficient nonradiative power transfer over distances up to 8 times the radius of the coils. We were able to transfer 60 watts with ∼40% efficiency over distances in excess of 2 meters. We present a quantitative model describing the power transfer, which matches the experimental results to within 5%. We discuss the practical applicability of this system and suggest directions for further study.

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Research works printed but not linked: 9

  1. 10.1109/28.90341 · DOI · Paper page
  2. 10.1109/63.817358 · DOI
  3. 10.1016/j.aop.2007.04.017 · DOI · Paper page
  4. 10.1038/nature05147 · DOI · Paper page
  5. K. O'Brien G. Scheible H. Gueldner in IECON'03 29th Annual Conference of the IEEE (http://ieeexplore.ieee.org/xpl/RecentCon.jsp?punumber=9011) (2003).
  6. S. Sensiper thesis Massachusetts Institute of Technology (1951).
  7. W. A. Edson Vacuum-Tube Oscillators (Wiley New York 1953).
  8. IEEE Std C95.1—2005 IEEE Standard for Safety Levels with Respect to Human Exposure to Radio Frequency Electromagnetic Fields 3 kHz to 300 GHz (IEEE Piscataway NJ 2006).
  9. 10.1126/science.1104467 · DOI · Paper page

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Metadata

Authors
Kurs, A., Karalis, A., Moffatt, R., Joannopoulos, J. D., Fisher, P., & Soljačić, M.
Venue
Science
Published
2007-07-06
Volume
317
Issue
5834
Pages
83-86
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W1985705155
Cited by
5,576
References
0
FWCI
54.18
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Wireless Power Transfer via Strongly Coupled Magnetic Resonances. https://app.cochat.ai/papers/10.1126/science.1143254
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Kurs, A., Karalis, A., Moffatt, R., Joannopoulos, J. D., Fisher, P., & Soljačić, M. (2007). Wireless Power Transfer via Strongly Coupled Magnetic Resonances. Science. https://doi.org/10.1126/science.1143254

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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.