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Scalable graphene sensor array for real-time toxins monitoring in flowing water.
Maity, Arnab; Pu, Haihui; Sui, Xiaoyu; Chang, Jingbo; Bottum, Kai J; Jin, Bing; Zhou, Guihua; Wang, Yale; Lu, Ganhua; Chen, Junhong.
Afiliación
  • Maity A; Department of Mechanical Engineering, College of Engineering & Applied Science, University of Wisconsin-Milwaukee, Milwaukee, WI, 53211, USA.
  • Pu H; Department of Mechanical Engineering, College of Engineering & Applied Science, University of Wisconsin-Milwaukee, Milwaukee, WI, 53211, USA.
  • Sui X; Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, 60637, USA.
  • Chang J; Chemical Sciences and Engineering Division, Physical Sciences and Engineering Directorate, Argonne National Laboratory, 9700 S. Cass Ave., Lemont, IL, 60439, USA.
  • Bottum KJ; Department of Mechanical Engineering, College of Engineering & Applied Science, University of Wisconsin-Milwaukee, Milwaukee, WI, 53211, USA.
  • Jin B; Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, 60637, USA.
  • Zhou G; Chemical Sciences and Engineering Division, Physical Sciences and Engineering Directorate, Argonne National Laboratory, 9700 S. Cass Ave., Lemont, IL, 60439, USA.
  • Wang Y; Department of Mechanical Engineering, College of Engineering & Applied Science, University of Wisconsin-Milwaukee, Milwaukee, WI, 53211, USA.
  • Lu G; Department of Mechanical Engineering, College of Engineering & Applied Science, University of Wisconsin-Milwaukee, Milwaukee, WI, 53211, USA.
  • Chen J; Department of Mechanical Engineering, College of Engineering & Applied Science, University of Wisconsin-Milwaukee, Milwaukee, WI, 53211, USA.
Nat Commun ; 14(1): 4184, 2023 Jul 13.
Article en En | MEDLINE | ID: mdl-37443127
ABSTRACT
Risk management for drinking water often requires continuous monitoring of various toxins in flowing water. While they can be readily integrated with existing water infrastructure, two-dimensional (2D) electronic sensors often suffer from device-to-device variations due to the lack of an effective strategy for identifying faulty devices from preselected uniform devices based on electronic properties alone, resulting in sensor inaccuracy and thus slowing down their real-world applications. Here, we report the combination of wet transfer, impedance and noise measurements, and machine learning to facilitate the scalable nanofabrication of graphene-based field-effect transistor (GFET) sensor arrays and the efficient identification of faulty devices. Our sensors were able to perform real-time detection of heavy-metal ions (lead and mercury) and E. coli bacteria simultaneously in flowing tap water. This study offers a reliable quality control protocol to increase the potential of electronic sensors for monitoring pollutants in flowing water.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Contaminantes del Agua / Agua Potable / Metales Pesados / Grafito / Mercurio Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2023 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Contaminantes del Agua / Agua Potable / Metales Pesados / Grafito / Mercurio Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2023 Tipo del documento: Article