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Graphene metamaterial, AI shrink spectrometer chip

Technology News |
By Nick Flaherty


European researchers have shrunk the size of spectrometers by using a combination of layered 2D metamaterial sensor and machine learning.

“We eliminate the need for detector arrays, dispersive components, and filters. It’s an all-in-one, miniaturised device that could revolutionise this field,” said Dr Hoon Hahn Yoon, from Aalto University in Finland, first author of the paper.

The tunable detector uses van der Waals heterostructures with 2D layers of graphene, molybdenum disulfide, and tungsten diselenide. Different combinations of material components enable light detection into the near infra-red, enabling applications such as chemical analysis and night vision.

The combination provides a wavelength accuracy of ∼0.36nm with a spectral resolution of ∼3nm across a bandwidth of 405 to 845nm

“We detect a continuum spectrum of light, opening a world of possibilities in a myriad of markets,” said Yoon. “Exploring other material combinations could uncover further functionalities, including even broader hyperspectral detection and improved resolution.”

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The machine learning compensates for the inherent noise increase from the detector.

“We were able to use mathematical algorithms to successfully reconstruct the signals and spectra, it’s a profound and transformative technological leap,” said Professor Zhipei Sun, also from Aalto University. “The current design is just a proof-of-concept. More advanced algorithms, as well as different combinations of materials, could soon provide even better miniaturised spectrometers.”

Shrinking the size of the spectrometer will open up applications in the Internet of Things and Industry 4.0 say the researchers, from sensing and surveillance to smart agriculture as well as chemical and biochemical analysis.

“Our miniaturised spectrometers offer high spatial and spectral resolution at the micrometre and nanometre scales, which is particularly exciting for responsive bio-implants and innovative imaging techniques,” said co-author Professor Tawfique Hasan, from the Cambridge Graphene Centre.

www.aalto.fi www.cambridge.ac.uk

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