Metasurface-enabled molecular spectroscopy and machine learning resolve lipid membrane photoswitching

M. Barkey, R. Büchner, A. Wester, S. Pritzl, M. Makarenko, Q. Wang, T. Weber, S. A. Maier, A. Fratalocchi, T. Lohmüller, A. Tittl*

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

Abstract

We present an integrated platform for ultrasensitive in-situ biospectroscopy by combining all-dielectric pixelated metasurfaces and machine learning. Specifically designed metasurfaces with advanced sampling techniques probe the real-time dynamics of lipid membrane photoswitching in an aqueous environment in the mid-infrared, overcoming sensitivity limitations and strong water absorption associated with conventional infrared spectroscopy. Our platform combines metasurfaces, optofluidics, and artificial intelligence (AI) to extend the capabilities of dielectric metasurfaces for analyzing complex biological entities.

Original languageEnglish (US)
Pages1621-1623
Number of pages3
StatePublished - 2023
Event13th International Conference on Metamaterials, Photonic Crystals and Plasmonics, META 2023 - Paris, France
Duration: Jul 18 2023Jul 21 2023

Conference

Conference13th International Conference on Metamaterials, Photonic Crystals and Plasmonics, META 2023
Country/TerritoryFrance
CityParis
Period07/18/2307/21/23

Bibliographical note

Publisher Copyright:
© 2023, META Conference. All rights reserved.

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Materials Science (miscellaneous)
  • Electronic, Optical and Magnetic Materials
  • Materials Chemistry

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