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

Ahmed Abusultan, Heba Abunahla, Yasmin Halawani, Baker Mohammad, Nahla Alamoodi, Anas Alazzam

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

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: [Figure not available: see fulltext.]

Original languageBritish English
Article number89
JournalNanoscale Research Letters
Volume17
Issue number1
DOIs
StatePublished - 2022

Keywords

  • Flexible
  • GO
  • Paper
  • Reduction
  • Sensor
  • Sunlight
  • UV

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