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<p>An electronic nose enables non-invasive cancer detection by analyzing volatile organic compounds in exhaled breath. This study utilized finite element simulation to design and optimize a surface acoustic wave sensor for the detection of lung cancer biomarkers. The simulation incorporated piezoelectric constitutive equations, solved using solid mechanics and electrostatics boundary conditions. The piezoelectric substrate was modeled with solid mechanics, while the electrostatic model controlled the input voltage of interdigitated electrodes (IDE). The study optimized the IDE pitch by testing values between 2&#xa0;<i>µ</i>m and 12&#xa0;<i>µ</i>m, identifying 4&#xa0;<i>µ</i>m as the most effective. The sensor demonstrated sensitivities of 502.85&#xa0;Hz/ppm for toluene, 112.41&#xa0;Hz/ppm for hexane, 76.42&#xa0;Hz/ppm for 2-methylpentane, and 7.32&#xa0;Hz/ppm for isoprene, with detection limits of 3&#xa0;ppb, 10&#xa0;ppb, 20&#xa0;ppb, and 200&#xa0;ppb, respectively. Cross-sensitivity analysis confirmed that the PIB sensing layer had strong selectivity towards targeted VOCs compared to ambient and common background gases. Additionally, the sensor performance was examined towards the targeted VOCs with variable temperature and relative humidity (RH). The sensor exhibited linear response for RH from 20% to 80% in the temperature range from 30&#xa0;°C to 40&#xa0;°C. These results highlight the sensor's potential for early lung cancer detection via breath analysis.</p> Graphical Abstract <p></p>

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Enhancing Surface Acoustic Wave Sensor Performance Through Geometric Optimization for the Detection of Lung Cancer Biomarkers

  • 期刊论文

  • 发表日期：

    2025年8月6日

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  • D. Hannah Jerrin Thangam,
  • G. Gnanasangeetha,
  • J. Jayachandiran,
  • C. Venkateswaran,
  • D. Nedumaran

摘要

An electronic nose enables non-invasive cancer detection by analyzing volatile organic compounds in exhaled breath. This study utilized finite element simulation to design and optimize a surface acoustic wave sensor for the detection of lung cancer biomarkers. The simulation incorporated piezoelectric constitutive equations, solved using solid mechanics and electrostatics boundary conditions. The piezoelectric substrate was modeled with solid mechanics, while the electrostatic model controlled the input voltage of interdigitated electrodes (IDE). The study optimized the IDE pitch by testing values between 2 µm and 12 µm, identifying 4 µm as the most effective. The sensor demonstrated sensitivities of 502.85 Hz/ppm for toluene, 112.41 Hz/ppm for hexane, 76.42 Hz/ppm for 2-methylpentane, and 7.32 Hz/ppm for isoprene, with detection limits of 3 ppb, 10 ppb, 20 ppb, and 200 ppb, respectively. Cross-sensitivity analysis confirmed that the PIB sensing layer had strong selectivity towards targeted VOCs compared to ambient and common background gases. Additionally, the sensor performance was examined towards the targeted VOCs with variable temperature and relative humidity (RH). The sensor exhibited linear response for RH from 20% to 80% in the temperature range from 30 °C to 40 °C. These results highlight the sensor's potential for early lung cancer detection via breath analysis.

Graphical Abstract