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CVD-grown SnS2 active layers on AlGaN/GaN HEMT for arsenic (III) ions detection

  • Nipun Sharma
  • , Adarsh Nigam
  • , Jai Mishra
  • , Ashok Kumar
  • , Srinjoy Mitra
  • , Ankur Gupta
  • , Sudhiranjan Tripathy
  • , Mahesh Kumar*
  • *Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    Abstract

    The pervasive contamination of water sources by the toxic heavy metal arsenic presents a serious threat to human health and ecological systems. This raises the critical need for innovative detection platforms that can detect such contamination at low cost and as part of an onsite, distributed sensor network. In this context, we report an Arsenic (As3+) ion detection system that was fabricated using 2D SnS2 functionalized AlGaN/GaN high electron mobility transistor (HEMT). SnS2 layers were grown on the HEMT surface by chemical vapor deposition (CVD) which depicts hexagonal oriented nanosheets with crystal edges. The source and drain tri-metal contacts of Au/Cr/Al were fabricated by thermal evaporation using shadow mask. The sensor response was analyzed by measuring the variation in drain to source current of the device after introducing varied concentrations of As3+ ions, ranging from 1 ppb to 10 ppm. The observed sensitivity of the device is 0.42 μA ppb−1, with a detection limit of 0.90 ppb, and a response time of 3.2 s. Further, real-time data analysis was performed by the integration of the developed sensor with a customized printed circuit board connected with an Arduino Nano 33 Bluetooth Low Energy (BLE) module for data transmission. The concept of growing the SnS2 layer as a functionalizing layer by CVD results in quick response, good repeatability, and selectivity thereby eliminating the need for any additional reference electrode. Integration of the developed AlGaN/GaN HEMT sensor with Arduino Nano 33 BLE makes it an ideal candidate for portable heavy metal ion sensing device for onsite detection.

    Original languageEnglish
    Article number205501
    JournalNanotechnology
    Volume36
    Issue number20
    DOIs
    Publication statusPublished - 19-05-2025

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    All Science Journal Classification (ASJC) codes

    • Bioengineering
    • General Chemistry
    • General Materials Science
    • Mechanics of Materials
    • Mechanical Engineering
    • Electrical and Electronic Engineering

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