Asymmetric parametric generation of images with nonlinear dielectric metasurfaces

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Asymmetric parametric generation of images with nonlinear dielectric metasurfaces
Asymmetric parametric generation of images with nonlinear dielectric metasurfaces
Journal Title:
Nature Photonics
Publication Date:
20 June 2022
Kruk, S. S., Wang, L., Sain, B., Dong, Z., Yang, J., Zentgraf, T., & Kivshar, Y. (2022). Asymmetric parametric generation of images with nonlinear dielectric metasurfaces. Nature Photonics, 16(8), 561–565.
Subwavelength dielectric resonators assembled into metasurfaces have become a versatile tool for miniaturizing optical components approaching the nanoscale1,2,3. An important class of metasurface functionalities is associated with asymmetry in both the generation and transmission of light with respect to reversals of the positions of emitters and receivers4,5,6. The nonlinear light–matter interaction in metasurfaces7,8,9 offers a promising pathway towards miniaturization of the asymmetric control of light. Here we demonstrate asymmetric parametric generation of light in nonlinear metasurfaces. We assemble dissimilar nonlinear dielectric resonators into translucent metasurfaces that produce images in the visible spectral range on being illuminated by infrared radiation. By design, the metasurfaces produce different and completely independent images for the reversed direction of illumination, that is, when the positions of the infrared emitter and the visible light receiver are exchanged. Nonlinearity-enabled asymmetric control of light by subwavelength resonators paves the way towards novel nanophotonic components via dense integration of large quantities of nonlinear resonators into compact metasurface designs.
License type:
Publisher Copyright
Funding Info:
Overseas Funding:- 1) Alexander von Humboldt Foundation, the Australian Research Council (DE210100679), 2) EU Horizon 2020 research and innovation program (grant 896735). 3) European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement No. 724306) 4) Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – TRR142 – No. 231447078 – project B09 5) National Key R&D Program of China (2020YFB1806603) 6) National Natural Science Foundation of China (Grant No. 62101127) 7) Natural Science Foundation of Jiangsu Province of China (BK20200393) 8) Jiangsu Province (JSSCBS20210116) 9) Fundamental Research Funds for the Central Universities (2242022R10025) 10) Strategic Fund of the Australian National University, the Australian Research Council (grant DP210101292) 11) US Army International Office (grant FA520921P0034
This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at:
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