Artificial intelligence-based refractive index sensing achieving atto-mol detection limit

N. Li; Q. Wang; Z. He; A. B. Lopez; F. Xiang; A. Fratalocchi

Artificial intelligence-based refractive index sensing achieving atto-mol detection limit

N. Li, Q. Wang, Z. He, A. B. Lopez, F. Xiang, A. Fratalocchi^*

^*Corresponding author for this work

Research output: Contribution to conference › Paper › peer-review

Abstract

This study implements an ultrasensitive platform technology that integrates a wet-chemistry scalable sensor with optical artificial intelligence hardware attached to a conventional monochrome camera. The system extracts sensing features in the optical hardware, enabling accurate quantification of glucose concentration with a detection limit as low as 10^-20 mol/L. The results improve the current state-of-the-art by six orders of magnitude. The system does not require an electrochemical workstation and works in real-time.

Original language	English (US)
Pages	1360-1361
Number of pages	2
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

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

Cite this

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title = "Artificial intelligence-based refractive index sensing achieving atto-mol detection limit",

abstract = "This study implements an ultrasensitive platform technology that integrates a wet-chemistry scalable sensor with optical artificial intelligence hardware attached to a conventional monochrome camera. The system extracts sensing features in the optical hardware, enabling accurate quantification of glucose concentration with a detection limit as low as 10-20 mol/L. The results improve the current state-of-the-art by six orders of magnitude. The system does not require an electrochemical workstation and works in real-time.",

author = "N. Li and Q. Wang and Z. He and Lopez, {A. B.} and F. Xiang and A. Fratalocchi",

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TY - CONF

T1 - Artificial intelligence-based refractive index sensing achieving atto-mol detection limit

AU - Li, N.

AU - Wang, Q.

AU - He, Z.

AU - Lopez, A. B.

AU - Xiang, F.

AU - Fratalocchi, A.

PY - 2023

Y1 - 2023

N2 - This study implements an ultrasensitive platform technology that integrates a wet-chemistry scalable sensor with optical artificial intelligence hardware attached to a conventional monochrome camera. The system extracts sensing features in the optical hardware, enabling accurate quantification of glucose concentration with a detection limit as low as 10-20 mol/L. The results improve the current state-of-the-art by six orders of magnitude. The system does not require an electrochemical workstation and works in real-time.

AB - This study implements an ultrasensitive platform technology that integrates a wet-chemistry scalable sensor with optical artificial intelligence hardware attached to a conventional monochrome camera. The system extracts sensing features in the optical hardware, enabling accurate quantification of glucose concentration with a detection limit as low as 10-20 mol/L. The results improve the current state-of-the-art by six orders of magnitude. The system does not require an electrochemical workstation and works in real-time.

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M3 - Paper

AN - SCOPUS:85174590483

SP - 1360

EP - 1361

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

Y2 - 18 July 2023 through 21 July 2023

ER -

Artificial intelligence-based refractive index sensing achieving atto-mol detection limit

Abstract

Conference

Bibliographical note

ASJC Scopus subject areas

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