SOURCE-LINKED INTELLIGENCE
Disordered metasurfaces with ultimate information capacity for near-infrared spectroscopy
l 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
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 353380.32
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T03:21:21.440Z. This is not the publication date.