IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v6y2015i1d10.1038_ncomms8069.html
   My bibliography  Save this article

Subwavelength-thick lenses with high numerical apertures and large efficiency based on high-contrast transmitarrays

Author

Listed:
  • Amir Arbabi

    (T. J. Watson Laboratory of Applied Physics, California Institute of Technology)

  • Yu Horie

    (T. J. Watson Laboratory of Applied Physics, California Institute of Technology)

  • Alexander J. Ball

    (T. J. Watson Laboratory of Applied Physics, California Institute of Technology)

  • Mahmood Bagheri

    (Jet Propulsion Laboratory, California Institute of Technology)

  • Andrei Faraon

    (T. J. Watson Laboratory of Applied Physics, California Institute of Technology)

Abstract

Flat optical devices thinner than a wavelength promise to replace conventional free-space components for wavefront and polarization control. Transmissive flat lenses are particularly interesting for applications in imaging and on-chip optoelectronic integration. Several designs based on plasmonic metasurfaces, high-contrast transmitarrays and gratings have been recently implemented but have not provided a performance comparable to conventional curved lenses. Here we report polarization-insensitive, micron-thick, high-contrast transmitarray micro-lenses with focal spots as small as 0.57 λ. The measured focusing efficiency is up to 82%. A rigorous method for ultrathin lens design, and the trade-off between high efficiency and small spot size (or large numerical aperture) are discussed. The micro-lenses, composed of silicon nano-posts on glass, are fabricated in one lithographic step that could be performed with high-throughput photo or nanoimprint lithography, thus enabling widespread adoption.

Suggested Citation

  • Amir Arbabi & Yu Horie & Alexander J. Ball & Mahmood Bagheri & Andrei Faraon, 2015. "Subwavelength-thick lenses with high numerical apertures and large efficiency based on high-contrast transmitarrays," Nature Communications, Nature, vol. 6(1), pages 1-6, November.
  • Handle: RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms8069
    DOI: 10.1038/ncomms8069
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/ncomms8069
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/ncomms8069?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sajjad Abdollahramezani & Omid Hemmatyar & Mohammad Taghinejad & Hossein Taghinejad & Alex Krasnok & Ali A. Eftekhar & Christian Teichrib & Sanchit Deshmukh & Mostafa A. El-Sayed & Eric Pop & Matthias, 2022. "Electrically driven reprogrammable phase-change metasurface reaching 80% efficiency," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    2. Claudio U. Hail & Morgan Foley & Ruzan Sokhoyan & Lior Michaeli & Harry A. Atwater, 2023. "High quality factor metasurfaces for two-dimensional wavefront manipulation," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    3. Ruixuan Zheng & Ruhao Pan & Guangzhou Geng & Qiang Jiang & Shuo Du & Lingling Huang & Changzhi Gu & Junjie Li, 2022. "Active multiband varifocal metalenses based on orbital angular momentum division multiplexing," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    4. Dongwoo Lee & Beomseok Oh & Jeonghoon Park & Seong-Won Moon & Kilsoo Shin & Sea-Moon Kim & Junsuk Rho, 2024. "Wide field-of-hearing metalens for aberration-free sound capture," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
    5. Wei, PengCheng & He, Fangcheng, 2019. "Research on security trust measure model based on fuzzy mathematics," Chaos, Solitons & Fractals, Elsevier, vol. 128(C), pages 139-143.
    6. Minkyung Kim & Dasol Lee & Younghwan Yang & Yeseul Kim & Junsuk Rho, 2022. "Reaching the highest efficiency of spin Hall effect of light in the near-infrared using all-dielectric metasurfaces," Nature Communications, Nature, vol. 13(1), pages 1-7, December.
    7. Luocheng Huang & Zheyi Han & Anna Wirth-Singh & Vishwanath Saragadam & Saswata Mukherjee & Johannes E. Fröch & Quentin A. A. Tanguy & Joshua Rollag & Ricky Gibson & Joshua R. Hendrickson & Philip W. C, 2024. "Broadband thermal imaging using meta-optics," Nature Communications, Nature, vol. 15(1), pages 1-8, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms8069. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.