IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-29374-6.html
   My bibliography  Save this article

Electrically driven reprogrammable phase-change metasurface reaching 80% efficiency

Author

Listed:
  • Sajjad Abdollahramezani

    (Georgia Institute of Technology)

  • Omid Hemmatyar

    (Georgia Institute of Technology)

  • Mohammad Taghinejad

    (Georgia Institute of Technology)

  • Hossein Taghinejad

    (Georgia Institute of Technology)

  • Alex Krasnok

    (Photonics Initiative, Advanced Science Research Center, City University of New York
    Florida International University)

  • Ali A. Eftekhar

    (Georgia Institute of Technology)

  • Christian Teichrib

    (Physikalisches Institut IA, RWTH Aachen)

  • Sanchit Deshmukh

    (Department of Electrical Engineering)

  • Mostafa A. El-Sayed

    (Laser Dynamics Laboratory, School of Chemistry and Biochemistry, Georgia Institute of Technology)

  • Eric Pop

    (Department of Electrical Engineering
    Stanford University
    Precourt Institute for Energy, Stanford University)

  • Matthias Wuttig

    (Physikalisches Institut IA, RWTH Aachen)

  • Andrea Alù

    (Photonics Initiative, Advanced Science Research Center, City University of New York
    Physics Program, Graduate Center, City University of New York)

  • Wenshan Cai

    (Georgia Institute of Technology
    School of Materials Science and Engineering, Georgia Institute of Technology)

  • Ali Adibi

    (Georgia Institute of Technology)

Abstract

Phase-change materials (PCMs) offer a compelling platform for active metaoptics, owing to their large index contrast and fast yet stable phase transition attributes. Despite recent advances in phase-change metasurfaces, a fully integrable solution that combines pronounced tuning measures, i.e., efficiency, dynamic range, speed, and power consumption, is still elusive. Here, we demonstrate an in situ electrically driven tunable metasurface by harnessing the full potential of a PCM alloy, Ge2Sb2Te5 (GST), to realize non-volatile, reversible, multilevel, fast, and remarkable optical modulation in the near-infrared spectral range. Such a reprogrammable platform presents a record eleven-fold change in the reflectance (absolute reflectance contrast reaching 80%), unprecedented quasi-continuous spectral tuning over 250 nm, and switching speed that can potentially reach a few kHz. Our scalable heterostructure architecture capitalizes on the integration of a robust resistive microheater decoupled from an optically smart metasurface enabling good modal overlap with an ultrathin layer of the largest index contrast PCM to sustain high scattering efficiency even after several reversible phase transitions. We further experimentally demonstrate an electrically reconfigurable phase-change gradient metasurface capable of steering an incident light beam into different diffraction orders. This work represents a critical advance towards the development of fully integrable dynamic metasurfaces and their potential for beamforming applications.

Suggested Citation

  • 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.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-29374-6
    DOI: 10.1038/s41467-022-29374-6
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-29374-6
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-022-29374-6?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
    ---><---

    References listed on IDEAS

    as
    1. Ehsan Arbabi & Amir Arbabi & Seyedeh Mahsa Kamali & Yu Horie & MohammadSadegh Faraji-Dana & Andrei Faraon, 2018. "MEMS-tunable dielectric metasurface lens," Nature Communications, Nature, vol. 9(1), pages 1-9, December.
    2. Yifei Zhang & Jeffrey B. Chou & Junying Li & Huashan Li & Qingyang Du & Anupama Yadav & Si Zhou & Mikhail Y. Shalaginov & Zhuoran Fang & Huikai Zhong & Christopher Roberts & Paul Robinson & Bridget Bo, 2019. "Broadband transparent optical phase change materials for high-performance nonvolatile photonics," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    3. Jingyi Tian & Hao Luo & Yuanqing Yang & Fei Ding & Yurui Qu & Ding Zhao & Min Qiu & Sergey I. Bozhevolnyi, 2019. "Active control of anapole states by structuring the phase-change alloy Ge2Sb2Te5," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    4. Maxim R. Shcherbakov & Sheng Liu & Varvara V. Zubyuk & Aleksandr Vaskin & Polina P. Vabishchevich & Gordon Keeler & Thomas Pertsch & Tatyana V. Dolgova & Isabelle Staude & Igal Brener & Andrey A. Fedy, 2017. "Ultrafast all-optical tuning of direct-gap semiconductor metasurfaces," Nature Communications, Nature, vol. 8(1), pages 1-6, December.
    5. J. Feldmann & N. Youngblood & C. D. Wright & H. Bhaskaran & W. H. P. Pernice, 2019. "All-optical spiking neurosynaptic networks with self-learning capabilities," Nature, Nature, vol. 569(7755), pages 208-214, May.
    6. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Joel Siegel & Shinho Kim & Margaret Fortman & Chenghao Wan & Mikhail A. Kats & Philip W. C. Hon & Luke Sweatlock & Min Seok Jang & Victor Watson Brar, 2024. "Electrostatic steering of thermal emission with active metasurface control of delocalized modes," Nature Communications, Nature, vol. 15(1), pages 1-7, December.
    2. Michele Cotrufo & Shaban B. Sulejman & Lukas Wesemann & Md. Ataur Rahman & Madhu Bhaskaran & Ann Roberts & Andrea Alù, 2024. "Reconfigurable image processing metasurfaces with phase-change materials," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    3. Kandammathe Valiyaveedu Sreekanth & Jayakumar Perumal & U. S. Dinish & Patinharekandy Prabhathan & Yuanda Liu & Ranjan Singh & Malini Olivo & Jinghua Teng, 2023. "Tunable Tamm plasmon cavity as a scalable biosensing platform for surface enhanced resonance Raman spectroscopy," Nature Communications, Nature, vol. 14(1), pages 1-9, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Geng-Bo Wu & Jun Yan Dai & Kam Man Shum & Ka Fai Chan & Qiang Cheng & Tie Jun Cui & Chi Hou Chan, 2023. "A universal metasurface antenna to manipulate all fundamental characteristics of electromagnetic waves," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    2. Soham Saha & Benjamin T. Diroll & Mustafa Goksu Ozlu & Sarah N. Chowdhury & Samuel Peana & Zhaxylyk Kudyshev & Richard D. Schaller & Zubin Jacob & Vladimir M. Shalaev & Alexander V. Kildishev & Alexan, 2023. "Engineering the temporal dynamics of all-optical switching with fast and slow materials," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    3. Fuhuan Shen & Zhenghe Zhang & Yaoqiang Zhou & Jingwen Ma & Kun Chen & Huanjun Chen & Shaojun Wang & Jianbin Xu & Zefeng Chen, 2022. "Transition metal dichalcogenide metaphotonic and self-coupled polaritonic platform grown by chemical vapor deposition," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    4. Ui Yeon Won & Quoc An Vu & Sung Bum Park & Mi Hyang Park & Van Dam Do & Hyun Jun Park & Heejun Yang & Young Hee Lee & Woo Jong Yu, 2023. "Multi-neuron connection using multi-terminal floating–gate memristor for unsupervised learning," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    5. 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.
    6. 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.
    7. Minati, Ludovico & Mancinelli, Mattia & Frasca, Mattia & Bettotti, Paolo & Pavesi, Lorenzo, 2021. "An analog electronic emulator of non-linear dynamics in optical microring resonators," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).
    8. Yuyin Xi & Fan Zhang & Yuanchi Ma & Vivek M. Prabhu & Yun Liu, 2022. "Finely tunable dynamical coloration using bicontinuous micrometer-domains," Nature Communications, Nature, vol. 13(1), pages 1-7, December.
    9. Junwei Cheng & Chaoran Huang & Jialong Zhang & Bo Wu & Wenkai Zhang & Xinyu Liu & Jiahui Zhang & Yiyi Tang & Hailong Zhou & Qiming Zhang & Min Gu & Jianji Dong & Xinliang Zhang, 2024. "Multimodal deep learning using on-chip diffractive optics with in situ training capability," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    10. Xiaoyun Yuan & Yong Wang & Zhihao Xu & Tiankuang Zhou & Lu Fang, 2023. "Training large-scale optoelectronic neural networks with dual-neuron optical-artificial learning," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    11. Zhiyao Ma & Tian Tian & Yuxuan Liao & Xue Feng & Yongzhuo Li & Kaiyu Cui & Fang Liu & Hao Sun & Wei Zhang & Yidong Huang, 2024. "Electrically switchable 2N-channel wave-front control for certain functionalities with N cascaded polarization-dependent metasurfaces," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
    12. 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.
    13. Xiangyan Meng & Guojie Zhang & Nuannuan Shi & Guangyi Li & José Azaña & José Capmany & Jianping Yao & Yichen Shen & Wei Li & Ninghua Zhu & Ming Li, 2023. "Compact optical convolution processing unit based on multimode interference," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    14. Jin Zhao & Wen-Xiong Song & Tianjiao Xin & Zhitang Song, 2021. "Rules of hierarchical melt and coordinate bond to design crystallization in doped phase change materials," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    15. Artem Sinelnik & Shiu Hei Lam & Filippo Coviello & Sebastian Klimmer & Giuseppe Valle & Duk-Yong Choi & Thomas Pertsch & Giancarlo Soavi & Isabelle Staude, 2024. "Ultrafast all-optical second harmonic wavefront shaping," Nature Communications, Nature, vol. 15(1), pages 1-7, December.
    16. Kiumars Aryana & Yifei Zhang & John A. Tomko & Md Shafkat Bin Hoque & Eric R. Hoglund & David H. Olson & Joyeeta Nag & John C. Read & Carlos Ríos & Juejun Hu & Patrick E. Hopkins, 2021. "Suppressed electronic contribution in thermal conductivity of Ge2Sb2Se4Te," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    17. 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.
    18. Elena Goi & Steffen Schoenhardt & Min Gu, 2022. "Direct retrieval of Zernike-based pupil functions using integrated diffractive deep neural networks," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    19. Pengzhan Li & Mingzhen Zhang & Qingli Zhou & Qinghua Zhang & Donggang Xie & Ge Li & Zhuohui Liu & Zheng Wang & Erjia Guo & Meng He & Can Wang & Lin Gu & Guozhen Yang & Kuijuan Jin & Chen Ge, 2024. "Reconfigurable optoelectronic transistors for multimodal recognition," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    20. 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.

    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:13:y:2022:i:1:d:10.1038_s41467-022-29374-6. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.