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

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 conference › Paper › peer-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 language	English (US)
Pages	1621-1623
Number of pages	3
State	Published - 2023
Event	13th International Conference on Metamaterials, Photonic Crystals and Plasmonics, META 2023 - Paris, France Duration: Jul 18 2023 → Jul 21 2023

Conference

Conference	13th International Conference on Metamaterials, Photonic Crystals and Plasmonics, META 2023
Country/Territory	France
City	Paris
Period	07/18/23 → 07/21/23

ASJC Scopus subject areas

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

Cite this

Barkey, M., Büchner, R., Wester, A., Pritzl, S., Makarenko, M., Wang, Q., Weber, T., Maier, S. A., Fratalocchi, A., Lohmüller, T., & Tittl, A. (2023). Metasurface-enabled molecular spectroscopy and machine learning resolve lipid membrane photoswitching. 1621-1623. Paper presented at 13th International Conference on Metamaterials, Photonic Crystals and Plasmonics, META 2023, Paris, France.

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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.",

author = "M. Barkey and R. B{\"u}chner and A. Wester and S. Pritzl and M. Makarenko and Q. Wang and T. Weber and Maier, {S. A.} and A. Fratalocchi and T. Lohm{\"u}ller and A. Tittl",

note = "Publisher Copyright: {\textcopyright} 2023, META Conference. All rights reserved.; 13th International Conference on Metamaterials, Photonic Crystals and Plasmonics, META 2023 ; Conference date: 18-07-2023 Through 21-07-2023",

year = "2023",

language = "English (US)",

pages = "1621--1623",

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Barkey, M, Büchner, R, Wester, A, Pritzl, S, Makarenko, M, Wang, Q, Weber, T, Maier, SA, Fratalocchi, A, Lohmüller, T & Tittl, A 2023, 'Metasurface-enabled molecular spectroscopy and machine learning resolve lipid membrane photoswitching', Paper presented at 13th International Conference on Metamaterials, Photonic Crystals and Plasmonics, META 2023, Paris, France, 07/18/23 - 07/21/23 pp. 1621-1623.

TY - CONF

T1 - Metasurface-enabled molecular spectroscopy and machine learning resolve lipid membrane photoswitching

AU - Barkey, M.

AU - Büchner, R.

AU - Wester, A.

AU - Pritzl, S.

AU - Makarenko, M.

AU - Wang, Q.

AU - Weber, T.

AU - Maier, S. A.

AU - Fratalocchi, A.

AU - Lohmüller, T.

AU - Tittl, A.

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85174589675&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:85174589675

SP - 1621

EP - 1623

T2 - 13th International Conference on Metamaterials, Photonic Crystals and Plasmonics, META 2023

Y2 - 18 July 2023 through 21 July 2023

ER -

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

Abstract

Conference

ASJC Scopus subject areas

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