Literature DB >> 31667481

Full color generation with Fano-type resonant HfO2 nanopillars designed by a deep-learning approach.

Omid Hemmatyar1, Sajjad Abdollahramezani1, Yashar Kiarashinejad1, Mohammadreza Zandehshahvar1, Ali Adibi1.   

Abstract

In contrast to lossy plasmonic metasurfaces (MSs), wideband dielectric MSs comprising subwavelength nanostructures supporting Mie resonances are of great interest in the visible wavelength range. Here, for the first time to our knowledge, we experimentally demonstrate a reflective MS consisting of a square-lattice array of hafnia (HfO2) nanopillars to generate a wide color gamut. To design and optimize these MSs, we use a deep-learning algorithm based on a dimensionality reduction technique. Good agreement is observed between simulation and experimental results in yielding vivid and high-quality colors. We envision that these structures not only empower the high-resolution digital displays and sensitive colorimetric biosensors but also can be applied to on-demand applications of beaming in a wide wavelength range down to deep ultraviolet.

Entities:  

Year:  2019        PMID: 31667481     DOI: 10.1039/c9nr07408b

Source DB:  PubMed          Journal:  Nanoscale        ISSN: 2040-3364            Impact factor:   7.790


  3 in total

Review 1.  Deep learning: a new tool for photonic nanostructure design.

Authors:  Ravi S Hegde
Journal:  Nanoscale Adv       Date:  2020-02-12

2.  Temporal phase unwrapping using deep learning.

Authors:  Wei Yin; Qian Chen; Shijie Feng; Tianyang Tao; Lei Huang; Maciej Trusiak; Anand Asundi; Chao Zuo
Journal:  Sci Rep       Date:  2019-12-27       Impact factor: 4.379

3.  Prediction and Inverse Design of Structural Colors of Nanoparticle Systems via Deep Neural Network.

Authors:  Lanxin Ma; Kaixiang Hu; Chengchao Wang; Jia-Yue Yang; Linhua Liu
Journal:  Nanomaterials (Basel)       Date:  2021-12-08       Impact factor: 5.076

  3 in total

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