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Artificial Intelligence-Aided Low Cost and Flexible Graphene Oxide-Based Paper Sensor for Ultraviolet and Sunlight Monitoring

The adverse effect of ultraviolet (UV) radiation on human beings has sparked intense interest in the development of new sensors to effectively monitor UV and solar exposure. This paper describes a novel low-cost and flexible graphene oxide (GO)-based paper sensor capable of detecting the total amoun...

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Autores principales: Abusultan, Ahmed, Abunahla, Heba, Halawani, Yasmin, Mohammad, Baker, Alamoodi, Nahla, Alazzam, Anas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9468200/
https://www.ncbi.nlm.nih.gov/pubmed/36094698
http://dx.doi.org/10.1186/s11671-022-03727-y
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author Abusultan, Ahmed
Abunahla, Heba
Halawani, Yasmin
Mohammad, Baker
Alamoodi, Nahla
Alazzam, Anas
author_facet Abusultan, Ahmed
Abunahla, Heba
Halawani, Yasmin
Mohammad, Baker
Alamoodi, Nahla
Alazzam, Anas
author_sort Abusultan, Ahmed
collection PubMed
description The adverse effect of ultraviolet (UV) radiation on human beings has sparked intense interest in the development of new sensors to effectively monitor UV and solar exposure. This paper describes a novel low-cost and flexible graphene oxide (GO)-based paper sensor capable of detecting the total amount of UV or sun energy delivered per unit area. GO is incorporated into the structure of standard printing paper, cellulose, via a low-cost fabrication technique. The effect of UV and solar radiation exposure on the GO paper-based sensor is investigated using a simple color change analysis. As a result, users can easily determine the amount of ultraviolet or solar energy received by the sensor using a simple color analysis application. A neural network (ANN) model is also explored to learn the relation between UV color intensity and exposure time, then digitally display the results. The accuracy for the developed ANN reached 96.83%. The disposable, cost-effective, simple, biodegradable, safe, and flexible characteristics of the paper-based UV sensor make it an attractive candidate for a variety of sensing applications. This work provides new vision toward developing highly efficient and fully disposable GO-based photosensors. GRAPHICAL ABSTRACT: [Image: see text]
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spelling pubmed-94682002022-09-14 Artificial Intelligence-Aided Low Cost and Flexible Graphene Oxide-Based Paper Sensor for Ultraviolet and Sunlight Monitoring Abusultan, Ahmed Abunahla, Heba Halawani, Yasmin Mohammad, Baker Alamoodi, Nahla Alazzam, Anas Nanoscale Res Lett Research The adverse effect of ultraviolet (UV) radiation on human beings has sparked intense interest in the development of new sensors to effectively monitor UV and solar exposure. This paper describes a novel low-cost and flexible graphene oxide (GO)-based paper sensor capable of detecting the total amount of UV or sun energy delivered per unit area. GO is incorporated into the structure of standard printing paper, cellulose, via a low-cost fabrication technique. The effect of UV and solar radiation exposure on the GO paper-based sensor is investigated using a simple color change analysis. As a result, users can easily determine the amount of ultraviolet or solar energy received by the sensor using a simple color analysis application. A neural network (ANN) model is also explored to learn the relation between UV color intensity and exposure time, then digitally display the results. The accuracy for the developed ANN reached 96.83%. The disposable, cost-effective, simple, biodegradable, safe, and flexible characteristics of the paper-based UV sensor make it an attractive candidate for a variety of sensing applications. This work provides new vision toward developing highly efficient and fully disposable GO-based photosensors. GRAPHICAL ABSTRACT: [Image: see text] Springer US 2022-09-12 /pmc/articles/PMC9468200/ /pubmed/36094698 http://dx.doi.org/10.1186/s11671-022-03727-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Abusultan, Ahmed
Abunahla, Heba
Halawani, Yasmin
Mohammad, Baker
Alamoodi, Nahla
Alazzam, Anas
Artificial Intelligence-Aided Low Cost and Flexible Graphene Oxide-Based Paper Sensor for Ultraviolet and Sunlight Monitoring
title Artificial Intelligence-Aided Low Cost and Flexible Graphene Oxide-Based Paper Sensor for Ultraviolet and Sunlight Monitoring
title_full Artificial Intelligence-Aided Low Cost and Flexible Graphene Oxide-Based Paper Sensor for Ultraviolet and Sunlight Monitoring
title_fullStr Artificial Intelligence-Aided Low Cost and Flexible Graphene Oxide-Based Paper Sensor for Ultraviolet and Sunlight Monitoring
title_full_unstemmed Artificial Intelligence-Aided Low Cost and Flexible Graphene Oxide-Based Paper Sensor for Ultraviolet and Sunlight Monitoring
title_short Artificial Intelligence-Aided Low Cost and Flexible Graphene Oxide-Based Paper Sensor for Ultraviolet and Sunlight Monitoring
title_sort artificial intelligence-aided low cost and flexible graphene oxide-based paper sensor for ultraviolet and sunlight monitoring
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9468200/
https://www.ncbi.nlm.nih.gov/pubmed/36094698
http://dx.doi.org/10.1186/s11671-022-03727-y
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