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<p>This work explores the use of the suggested surface plasmon resonance (SPR) sensor to detect acetone by the zinc oxide (ZnO), copper (Cu), silicon (Si), and MXene (Ti<sub>3</sub>C<sub>2</sub>Tx) layers. The high surface area, robust light absorption, thermal stability, and biocompatibility of MXene are its outstanding properties. The performance parameters are at their best when the ZnO and Cu layer thicknesses are optimal. A sensitivity of 289.40°/RIU with remarkable minimum reflectance (R<sub>min</sub>) was attained by the suggested configuration through structural parameter optimization. The enhanced sensing parameters demonstrate efficacy in detecting analytes with refractive index (RI) variations between 1.34 and 1.368. The sensor design had a figure of merit (FOM) of 50.95/RIU, indicating high sensitivity that is typical of sensing designs. The highest sensitivity is achieved at 31-nm thicknesses of ZnO and Cu layers. The penetration depths (PD) for acetone concentrations of 0% and 90% are also determined to be 181.24&#xa0;nm and 187.54&#xa0;nm, respectively. The analysis shows that the suggested sensor has exceptional performance for sensing applications in both the biomedical and industrial domains.</p>

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Detection of Acetone Concentration in Water Using a Refractive Index-Based Surface Plasmon Resonance Sensor

  • 期刊论文

  • 发表日期：

    2025年6月25日

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  • Mayank,
  • Swapnil Srivastava,
  • Manoj Kumar,
  • Agya Ram Verma,
  • Pushkar Praveen,
  • Ashish Kumar Singh

摘要

This work explores the use of the suggested surface plasmon resonance (SPR) sensor to detect acetone by the zinc oxide (ZnO), copper (Cu), silicon (Si), and MXene (Ti3C2Tx) layers. The high surface area, robust light absorption, thermal stability, and biocompatibility of MXene are its outstanding properties. The performance parameters are at their best when the ZnO and Cu layer thicknesses are optimal. A sensitivity of 289.40°/RIU with remarkable minimum reflectance (Rmin) was attained by the suggested configuration through structural parameter optimization. The enhanced sensing parameters demonstrate efficacy in detecting analytes with refractive index (RI) variations between 1.34 and 1.368. The sensor design had a figure of merit (FOM) of 50.95/RIU, indicating high sensitivity that is typical of sensing designs. The highest sensitivity is achieved at 31-nm thicknesses of ZnO and Cu layers. The penetration depths (PD) for acetone concentrations of 0% and 90% are also determined to be 181.24 nm and 187.54 nm, respectively. The analysis shows that the suggested sensor has exceptional performance for sensing applications in both the biomedical and industrial domains.