The Principle and Application of Photonic Metasurfaces

A special issue of Photonics (ISSN 2304-6732). This special issue belongs to the section "Optical Interaction Science".

Deadline for manuscript submissions: 15 May 2026 | Viewed by 1285

Special Issue Editor


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Guest Editor
College of Electronic Information, Micro-Nano technology College, Qingdao University, Qingdao 266071, China
Interests: semiconductor, integrated circuit and sensing technology; optoelectronic technology and system; intelligent electronic information technology; biomedicine, environment and energy

Special Issue Information

Dear Colleagues,

The development of photonics has made great progress in various photonics design, manufacturing and application scenarios, including wavelengths from X-rays to microwaves. They can be applied in semiconductors, metals, and even dielectric materials. It is widely used in many fields, such as biomedicine, physics, the environment, energy, engineering, and even humanities. With the development of technology, research on new theories, technologies, phenomena and engineering aspects of photonics has become more and more urgent. Novel theoretical calculations, simulations or experimental verifications are of particular interest. For this Special Issue, we encourage the submission of theoretical, numerical and experimental papers.

Aim: This Special Issue focuses on exploring the fundamental principles behind photonic metasurfaces and their applications. It aims to gather advanced research that deepens our understanding of these structures and promotes innovation in the related fields.

Scope: The scope of this Special Issue encompasses theoretical investigations of photonic metasurface properties, design and fabrication techniques, as well as their applications in areas such as imaging, sensing, light manipulation, and communication. Both experimental and computational studies are welcome.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Photonic metasurfaces;
  • Photonic principle;
  • Photonic application;
  • Light manipulation;
  • Photonics medicine;
  • Related electromagnetic research;
  • Optoelectronic technology;
  • Photonics/optical imaging;
  • Photonics/optical sensing;
  • Photonics/optical communication;
  • Photonics/optical design;
  • Photonics/optical fabrication;
  • Photonics/optical devices and system;
  • Photonics/optical technology with AI.

We look forward to receiving your contributions.

Dr. Bin Wang
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Photonics is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

  • photonic metasurfaces
  • principle
  • application
  • light manipulation
  • imaging
  • sensing
  • communication
  • design
  • fabrication
  • photonics medicine
  • optical/photonics devices and system
  • AI technology

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Published Papers (1 paper)

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Research

10 pages, 7224 KiB  
Article
On-Chip Photonic Convolutional Processing Lights Up Fourier Neural Operator
by Zilong Tao, Hao Ouyang, Qiuquan Yan, Shiyin Du, Hao Hao, Jun Zhang and Jie You
Photonics 2025, 12(3), 253; https://doi.org/10.3390/photonics12030253 - 12 Mar 2025
Viewed by 914
Abstract
Fourier Neural Operators (FNOs) have gained increasing attention for their effectiveness in extracting frequencydomain features and efficiently approximating functions, making them wellsuited for classification tasks. However, the absence of specialized photonic hardware has limited the acceleration of FNO inference. In this study, we [...] Read more.
Fourier Neural Operators (FNOs) have gained increasing attention for their effectiveness in extracting frequencydomain features and efficiently approximating functions, making them wellsuited for classification tasks. However, the absence of specialized photonic hardware has limited the acceleration of FNO inference. In this study, we introduce what we believe is the first photonic hardware framework dedicated to speeding up the Fourier layer of an FNO. Our approach employs a frequency domain convolutional photonic chip and a micro-ring array chip, achieving 5-bit quantization precision in the inference process. On the Radio ML 2016.10b dataset, our Fourier convolutional neural network achieves a peak identification accuracy of 95.50%, outperforming standard convolution-based networks. These findings highlight the transformative potential of co-designing software and hardware, demonstrating how photonic computing can deliver specialized acceleration for critical AI components and substantially improve inference efficiency. Ultimately, this work lays a foundation for integrating photonic technologies into next-generation AI accelerators, pointing to a promising direction for further research and development in optoelectronic hybrid computing. Full article
(This article belongs to the Special Issue The Principle and Application of Photonic Metasurfaces)
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