• 文献标题:   Artificial Intelligence-Aided Low Cost and Flexible Graphene Oxide-Based Paper Sensor for Ultraviolet and Sunlight Monitoring
  • 文献类型:   Article
  • 作  者:   ABUSULTAN A, ABUNAHLA H, HALAWANI Y, MOHAMMAD B, ALAMOODI N, ALAZZAM A
  • 作者关键词:   sunlight, uv, sensor, flexible, reduction, go, paper
  • 出版物名称:   NANOSCALE RESEARCH LETTERS
  • ISSN:   1931-7573 EI 1556-276X
  • 通讯作者地址:  
  • 被引频次:   2
  • DOI:   10.1186/s11671-022-03727-y
  • 出版年:   2022

▎ 摘  要

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.