Nanoscale Light Manipulation with Multifunctional Optical Metamaterials

#Metamaterials # #Meta #Surfaces #Multifunctional #Manipulation #Light #nanoscale #Amplitude #Polarization #Jones #Matrix #Nanotechnology #application
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Over the past decade, we have witnessed tremendous progress and success of optical metamaterials. By tailoring the geometry of the nanoscale building blocks of optical metamaterials and engineering their spatial distribution, we can control the amplitude, polarization state, phase, and trajectory of light in almost any desired manner.1 For practical applications such as high-capacity optical display, information encryption, and data storage, it is crucial to encode distinct functions into a single meta-device and increase the information channels. I will present our recent work aimed at manipulating light at the nanoscale and pushing the multiplexing limits in optical metamaterials, using both physics-guided and data-driven approaches.

First, I will show how we can surpass the fundamental limit of polarization multiplexing capacity in 2D metamaterials, known as metasurfaces, by introducing the engineered noise to the precise solution of Jones matrix elements.2 We experimentally demonstrate up to 11 independent holographic images using a single metasurface illuminated by visible light with varying polarizations. To the best of our knowledge, it is the highest capacity reported for polarization multiplexing. Next, I will discuss the development of multiplexed metasurfaces with high efficiency, accuracy and fidelity by using deep learning.3-4 After training, the deep learning models can evaluate the optical responses of metasurfaces and perform inverse design in less than a second. We can embed deep learning models in both gradient-based and nongradient optimization loops for the automatic design of complex metasurfaces. This enables full exploitation of the design space and helps to push the multiplexing limit, as demonstrated by multichannel  focusing lenses, holograms, and image sensors based on metasurfaces.5-6

References:

[1]  N. Yu and F. Capasso, Nature Materials 13 (2), 139-150, 2014.

[2]  B. Xiong et al., Science 379 (6629), 294-299, 2023.

[3]  W. Ma, Z. Liu, Z. A. Kudyshev, A. Boltasseva, W. Cai, and Y. Liu, Nature Photonics 15, 77-90, 2021.

[4]  Y. Xu, B. Xiong, W. Ma, and Y. Liu, Progress in Quantum Electronics, 89, 100469, 2023.

[5]  W. Ma et al., Advanced Materials 34 (16), 2110022, 2022.

[6]  B. Xiong, Y. Xu, W. Li, W. Ma, T. Chu, and Y. Liu, Advanced Optical Materials 12 (10), 2302200, 2024.



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  • Co-sponsored by Electron Deices Society ( ED15)
  • Starts 26 June 2025 04:00 PM UTC
  • Ends 17 July 2025 04:00 AM UTC
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  Speakers

Prof. Yongmin Liu

Topic:

Nanoscale Light Manipulation with Multifunctional Optical Metamaterials

 

Over the past decade, we have witnessed tremendous progress and success of optical metamaterials. By tailoring the geometry of the nanoscale building blocks of optical metamaterials and engineering their spatial distribution, we can control the amplitude, polarization state, phase, and trajectory of light in almost any desired manner.1 For practical applications such as high-capacity optical display, information encryption, and data storage, it is crucial to encode distinct functions into a single meta-device and increase the information channels. I will present our recent work aimed at manipulating light at the nanoscale and pushing the multiplexing limits in optical metamaterials, using both physics-guided and data-driven approaches.

First, I will show how we can surpass the fundamental limit of polarization multiplexing capacity in 2D metamaterials, known as metasurfaces, by introducing the engineered noise to the precise solution of Jones matrix elements.2 We experimentally demonstrate up to 11 independent holographic images using a single metasurface illuminated by visible light with varying polarizations. To the best of our knowledge, it is the highest capacity reported for polarization multiplexing. Next, I will discuss the development of multiplexed metasurfaces with high efficiency, accuracy and fidelity by using deep learning.3-4 After training, the deep learning models can evaluate the optical responses of metasurfaces and perform inverse design in less than a second. We can embed deep learning models in both gradient-based and nongradient optimization loops for the automatic design of complex metasurfaces. This enables full exploitation of the design space and helps to push the multiplexing limit, as demonstrated by multichannel  focusing lenses, holograms, and image sensors based on metasurfaces.5-6

Biography:

Biography: Prof. Yongmin Liu obtained his Ph.D. from the University of California, Berkeley, in 2009. He joined the faculty of Northeastern University in Boston in the fall of 2012, and currently he is a full professor in the Department of Mechanical & Industrial Engineering and the Department of Electrical & Computer Engineering. Prof. Liu’s research interests include nano optics, nanoscale materials and engineering, plasmonics, metamaterials, biophotonics, and artificial intelligence. He has authored and co-authored more than 130 journal papers, including Science, Nature, Nature Photonics, Nature Nanotechnology, Advanced Materials, Physical Review Letters, and Nano Letters. Prof. Liu was a recipient of the Søren Buus Outstanding Research Award at Northeastern University (2024), the Faculty Fellow of College of Engineering at Northeastern University (2019), NSF CAREER Award (2017), Office of Naval Research Young Investigator Award (2016), SPIE DCS Rising Researcher Award (2016),  and 3M Non-Tenured Faculty Award (2016). He has served as an editorial board member for Nano Convergence, PhotoniX, EPJ Applied Metamaterials, and Scientific Reports. He is a fellow of Optica (formerly OSA) and SPIE.

Email:

Address:Department of Mechanical and Industrial Engineering, Department of Electrical and Computer Engineering, Northeastern University, Boston, United States, 02115





Agenda

Introduction: 6:30 pm

Presentation: 6:35 pm - 7:30 pm

Q&A: 7:30 pm - 7:45 pm