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Nano Research 2023, 16(7): 10018-10025 https://doi.org/10.1007/s12274-023-5669-z
Research Article | Open Access | Issue | Published: 25 May 2023

Longwave infrared multispectral image sensor system using aluminum-germanium plasmonic filter arrays

Show Author's Information Noor E Karishma Shaik1( ),  Bryce Widdicombe1,  Dechuan Sun1,  Sam E John2,  Dongryeol Ryu3,  Ampalavanapillai Nirmalathas1,  Ranjith R Unnithan1( )
Department of Electrical and Electronic Engineering, University of Melbourne, Parkville, VIC 3010, Australia
Department of Biomedical Engineering, University of Melbourne, Parkville, VIC 3010, Australia
Department of Infrastructure Engineering, University of Melbourne, Parkville, VIC 3010, Australia
Keywords:
infrared plasmonics, thermal optics, germanium (Ge), aluminum (Al), longwave infrared (LWIR) multispectral system
Topics:
Imaging techniqueInfrared imagingNanosensors Plasmonics
Cite this article:
Karishma Shaik NE, Widdicombe B, Sun D, et al. Longwave infrared multispectral image sensor system using aluminum-germanium plasmonic filter arrays. Nano Research, 2023, 16(7): 10018-10025. https://doi.org/10.1007/s12274-023-5669-z
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Abstract Full text Electronic supplementary material About this article

A multispectral camera records image data in various wavelengths across the electromagnetic spectrum to acquire additional information that a conventional camera fails to capture. With the advent of high-resolution image sensors and color filter technologies, multispectral imagers in the visible wavelengths have become popular with increasing commercial viability in the last decade. However, multispectral imaging in longwave infrared (LWIR, 8–14 µm) is still an emerging area due to the limited availability of optical materials, filter technologies, and high-resolution sensors. Images from LWIR multispectral cameras can capture emission spectra of objects to extract additional information that a human eye fails to capture and thus have important applications in precision agriculture, forestry, medicine, and object identification. In this work, we experimentally demonstrate an LWIR multispectral image sensor with three wavelength bands using optical elements made of an aluminum (Al)-based plasmonic filter array sandwiched in germanium (Ge). To realize the multispectral sensor, the filter arrays are then integrated into a three-dimensional (3D) printed wheel stacked on a low-resolution monochrome thermal sensor. Our prototype device is calibrated using a blackbody and its thermal output has been enhanced with computer vision methods. By applying a state-of-the-art deep learning method, we have also reconstructed multispectral images to a better spatial resolution. Scientifically, our work demonstrates a versatile spectral thermography technique for detecting target signatures in the LWIR range and other advanced spectral analyses.


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Electronic supplementary material
About this article

Longwave infrared multispectral image sensor system using aluminum-germanium plasmonic filter arrays

Show Author's information Noor E Karishma Shaik1( ), Bryce Widdicombe1, Dechuan Sun1, Sam E John2, Dongryeol Ryu3, Ampalavanapillai Nirmalathas1, Ranjith R Unnithan1( )
Department of Electrical and Electronic Engineering, University of Melbourne, Parkville, VIC 3010, Australia
Department of Biomedical Engineering, University of Melbourne, Parkville, VIC 3010, Australia
Department of Infrastructure Engineering, University of Melbourne, Parkville, VIC 3010, Australia

Abstract

A multispectral camera records image data in various wavelengths across the electromagnetic spectrum to acquire additional information that a conventional camera fails to capture. With the advent of high-resolution image sensors and color filter technologies, multispectral imagers in the visible wavelengths have become popular with increasing commercial viability in the last decade. However, multispectral imaging in longwave infrared (LWIR, 8–14 µm) is still an emerging area due to the limited availability of optical materials, filter technologies, and high-resolution sensors. Images from LWIR multispectral cameras can capture emission spectra of objects to extract additional information that a human eye fails to capture and thus have important applications in precision agriculture, forestry, medicine, and object identification. In this work, we experimentally demonstrate an LWIR multispectral image sensor with three wavelength bands using optical elements made of an aluminum (Al)-based plasmonic filter array sandwiched in germanium (Ge). To realize the multispectral sensor, the filter arrays are then integrated into a three-dimensional (3D) printed wheel stacked on a low-resolution monochrome thermal sensor. Our prototype device is calibrated using a blackbody and its thermal output has been enhanced with computer vision methods. By applying a state-of-the-art deep learning method, we have also reconstructed multispectral images to a better spatial resolution. Scientifically, our work demonstrates a versatile spectral thermography technique for detecting target signatures in the LWIR range and other advanced spectral analyses.

Keywords: infrared plasmonics, thermal optics, germanium (Ge), aluminum (Al), longwave infrared (LWIR) multispectral system

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Publication history

Received: 26 September 2022
Revised: 13 March 2023
Accepted: 14 March 2023
Published: 25 May 2023
Issue date: July 2023

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© The author(s) 2023

Acknowledgements

Acknowledgements

The numerical simulations were undertaken in the NCI National Facility in Canberra, Australia, which is supported by the Australian Commonwealth Government. This work was performed in part at the Melbourne Centre for Nanofabrication (MCN) in the Victorian Node of the Australian National Fabrication Facility (ANFF). This project received funding from the Linkage Grant from Australian Research Council (No. LP160101475). The authors thank Dr. Nandakishor Desai, Mr. Luke Weston and Assoc. Prof. Karim Seghouane for helpful discussions. NKS would like to additionally acknowledge the financial support provided by Melbourne Research Scholarship during PhD.

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Copyright: © 2023 by the author(s). This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.

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