• search hit 1 of 16
Back to Result List

Semi-Selective Array for the Classification of Purines with Surface Plasmon Resonance Imaging and Deep Learning Data Analysis

  • In process analytics or environmental monitoring, the real-time recording of the composition of complex samples over a long period of time presents a great challenge. Promising solutions are label-free techniques such as surface plasmon resonance (SPR) spectroscopy. They are, however, often limited due to poor reversibility of analyte binding. In this work, we introduce how SPR imaging in combination with a semi-selective functional surface and smart data analysis can identify small and chemically similar molecules. Our sensor uses individual functional spots made from different ratios of graphene oxide and reduced graphene oxide, which generate a unique signal pattern depending on the analyte due to different binding affinities. These patterns allow four purine bases to be distinguished after classification using a convolutional neural network (CNN) at concentrations as low as 50 μM. The validation and test set classification accuracies were constant across multiple measurements on multiple sensors using a standard CNN, which promises to serve as a future method for developing online sensors in complex mixtures.

Export metadata

Additional Services

Share in Twitter Search Google Scholar Statistics
Metadaten
Author:Simon JobstORCiD, Patrick Recum, Ángela Écija-Arenas, Elisabeth MoserORCiD, Rudolf Bierl, Thomas Hirsch
DOI:https://doi.org/10.1021/acssensors.3c01114
Parent Title (English):ACS sensors
Publisher:American Chemical Society
Document Type:Article
Language:English
Year of Completion:2023
Year of first Publication:2023
Release Date:2023/10/17
Tag:2D materials; functional surface; graphene oxide; pattern recognition; reduced graphene oxide; small-molecule sensing; surface plasmon resonance imaging
Volume:8
Issue:9
First Page:3530
Last Page:3537
Institutes:Fakultät Angewandte Natur- und Kulturwissenschaften
Fakultät Angewandte Natur- und Kulturwissenschaften / Sensorik-Applikationszentrum (SappZ)
Begutachtungsstatus:peer-reviewed
research focus:Sensorik
Licence (German):Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG