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Disordered metasurfaces with ultimate information capacity for near-infrared spectroscopy

Project description

Advanced imaging and sensing leveraging speckle patterns

Speckle patterns, often regarded as pure noise, are distinct features of disordered materials, offering a wealth of information owing to their sensitivity to external changes. This makes them ideal for hyperspectral imaging and sensing applications. Funded by the Marie Sklodowska-Curie Actions programme, the Metaspectrometer project will harness these patterns using resonant disordered metasurfaces and machine learning to create a compact, efficient near-infrared spectrometer. The initiative brings together experts in metasurface engineering, silicon photonics and machine learning. The newly developed near-infrared spectrometers will advance fields like health monitoring, food safety, and agriculture.

Objective

Speckle patterns are distinct features of disordered materials. While often regarded as mere noise, the intricate and responsive speckle patterns to minor fluctuations in external factors render them an ideal candidate for applications in hyperspectral imaging and sensing. The MetaSpectrometer harnesses the high information capacity of the speckle pattern of resonant disordered metasurfaces for compact, machine learning-assisted, non-invasive, and efficient near-infrared spectroscopy. An ultra-compact footprint, portability, cost-efficiency, minimal losses, machine-learning assisted recognition, angle-insensitivity, suppressed specular scatterance, significant memory effect, and ability to accommodate low coherence fields are the main features that cannot be currently obtained with any technology proposed so far and would represent a huge step forward in the state of the art. MetaSpectrometer brings together the complementary expertise of the postdoctoral researcher (PR) in metasurface engineering; the incoming host (CNRS-C2N, France) in silicon photonics, optoelectronics and nanofabrication; the associated the outgoing host (MIT, USA) in spectroscopy and machine learning, the secondment host (Rice, USA) in lensless imaging and the industrial partner (ZEISS, Germany) in spectroscopy and market analysis. The project allows PR to acquire expertise in silicon photonics technology's design, fabrication, characterization, and commercialization while giving back his expertise in metasurface design. The developed NIR spectrometers will find direct potential applications in wearable health monitoring systems, food screening, agriculture, and environmental screening that a remarkable global market size. The distribution of the work packages with distinct and clearly defined milestones and deliverables makes sure that the progress of the project will be monitored and matched with the work plan.

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-TMA-MSCA-PF-GF - HORIZON TMA MSCA Postdoctoral Fellowships - Global Fellowships

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Call for proposal

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(opens in new window) HORIZON-MSCA-2023-PF-01

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Coordinator

CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 353 380,32
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

No data

Partners (3)

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