Advanced Photonics honors best papers published in 2020

The Editor-in-Chief Choice Award recognizes exceptional journal papers
11 October 2021
Advanced Photonics Editor-in-Chief Choice Awards image

BELLINGHAM, Washington, USA — Advanced Photonics, an open access journal published by SPIE, the international society for optics and photonics, and Chinese Laser Press, has presented its Editor-in-Chief Choice Awards for papers published in 2020.

The Advanced Photonics Editor-in-Chief Choice Award, established last year, recognizes exceptional papers, based on the importance of the work to the optics and photonics field. From Advanced Photonics articles published in 2020, two winners were selected by the journal's Co-Editor-in-Chief Xiao-Cong (Larry) Yuan, of Shenzhen University, and Co-Editor-in-Chief Anatoly Zayats of King's College London: an original research article and a review article.

Advanced Photonics is published online in the SPIE Digital Library. It is a highly selective, open access, international journal publishing innovative research in all areas of optics and photonics, including fundamental and applied research.

"This year we had very tough choices to make," notes Zayats of the award selections. "Every article published in 2020 deserved this award. In the end, we decided to acknowledge one review and one original research article, based on the level of attention these papers attracted from our readers. Not surprisingly, they reflect some of the recent trends in optics and photonics."

The winning research article is "Enhanced light-matter interactions in dielectric nanostructures via machine-learning approach," by Lei Xu, Yixuan Ma, Fu Deng, Yan Kei Chiang, Lujun Huang, and Andrey E. Miroshnichenko, all of School of Engineering and Information Technology, University of New South Wales, Canberra; Mohsen Rahmani, Daria A. Smirnova, Khosro Zangeneh Kamali, and Dragomir N. Neshev, Nonlinear Physics Centre, Research School of Physics, Australian National University, Canberra; Haoyang Zhang, School of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane; and Stephen Gould, College of Engineering and Computer Science, Australian National University, Canberra.

In the article, the authors demonstrate that machine-learning techniques can be used to enhance metasurfaces by optimizing them for nonlinear optics and optomechanics. The discovery has promising possibilities for the development of a wide range of photonic devices and applications including those involved in optical sensing, optoacoustic vibrations, and narrowband filtering.

"The use of machine learning has become ubiquitous, not only in image processing, but also in designing photonic structures with the required properties," says Zayats of the winning research article. "Machine learning offers completely counterintuitive designs within the parameter space, which would be difficult to predict otherwise. Optimization of the enhanced light-matter interactions with the dielectric nanostructures achieved using machine learning in the work led by Professor Miroshnichenko is a vivid example of this."

The winning review article is "Terahertz surface plasmonic waves: a review," by Xueqian Zhang, Quan Xu, Lingbo Xia, Yanfeng Li, Jianqiang Gu, Zhen Tian, Chunmei Ouyang, and Jiaguang Han, all of the Center for Terahertz Waves of Tianjin University, and Weili Zhang of Oklahoma State University. In the article, the authors review terahertz surface plasmonic waves on various types of supports and outline research directions for terahertz surface plasmonic waves.

"Terahertz wavelengths promise many cutting-edge applications," says Yuan. "And eventually, the terahertz chip will be the likely platform on which plasmonic waves will serve as the information carrier. The review article by Zhang and colleagues comprehensively summarizes recent advances on terahertz surface plasmonic waves in excellent detail. It could serve as a tutorial for researchers who are interested in this field and a reference for engineers who are developing next-generation optical prototypes and products."

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