Scholarlink

<p>Formalin, the aqueous form of formaldehyde, is a Group 1 carcinogen that is increasingly misused as a food preservative in seafood and fresh produce. Rapid and accurate detection of formalin contamination in aqueous environments is therefore vital for food safety and public health monitoring. An innovative terahertz detection platform utilizing a multi-component metasurface architecture has been proposed for identifying formalin contamination in liquid environments. This simple structural arrangement delivers outstanding analytical performance, including 667&#xa0;GHz/RIU sensitivity, 18.018 figure of merit, and quality factors surpassing 13.4 across refractive indices spanning 1.33 to 1.36 RIU. Quantitative analysis revealed robust linear relationships linking resonance frequencies to both refractive index measurements (R<sup>2</sup> = 0.90) and formalin concentration levels (R<sup>2</sup> = 0.85), establishing reliable calibration standards. Machine learning integration through a one-dimensional convolutional neural network substantially improved prediction reliability, generating correlation coefficients between 0.87 and 0.92 in scatter plot evaluations and 0.91–1.00 in heat map assessments. The metasurface integrates graphene as a tunable conductive layer and Ti<sub>3</sub>C<sub>2</sub>T<sub>x</sub> MXene as a plasmonic enhancer, jointly for strong light–matter interaction and sensitivity in aqueous formalin environments. This biosensing technology offers a non-invasive, highly responsive approach for detecting carcinogenic compounds, representing a significant advancement in food safety monitoring capabilities.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

High-sensitivity graphene–Ti3C2Tx metasurface for terahertz detection of formalin in aqueous environments with machine learning enhancement

  • 期刊论文

  • 发表日期：

    2025年11月4日

查看全文
  • Jacob Wekalao,
  • Hussein A. Elsayed,
  • Haifa A. Alqhtani,
  • May Bin-Jumah,
  • Mostafa R. Abukhadra,
  • Ahmed Mehaney,
  • Amuthakkannan Rajakannu

摘要

Formalin, the aqueous form of formaldehyde, is a Group 1 carcinogen that is increasingly misused as a food preservative in seafood and fresh produce. Rapid and accurate detection of formalin contamination in aqueous environments is therefore vital for food safety and public health monitoring. An innovative terahertz detection platform utilizing a multi-component metasurface architecture has been proposed for identifying formalin contamination in liquid environments. This simple structural arrangement delivers outstanding analytical performance, including 667 GHz/RIU sensitivity, 18.018 figure of merit, and quality factors surpassing 13.4 across refractive indices spanning 1.33 to 1.36 RIU. Quantitative analysis revealed robust linear relationships linking resonance frequencies to both refractive index measurements (R2 = 0.90) and formalin concentration levels (R2 = 0.85), establishing reliable calibration standards. Machine learning integration through a one-dimensional convolutional neural network substantially improved prediction reliability, generating correlation coefficients between 0.87 and 0.92 in scatter plot evaluations and 0.91–1.00 in heat map assessments. The metasurface integrates graphene as a tunable conductive layer and Ti3C2Tx MXene as a plasmonic enhancer, jointly for strong light–matter interaction and sensitivity in aqueous formalin environments. This biosensing technology offers a non-invasive, highly responsive approach for detecting carcinogenic compounds, representing a significant advancement in food safety monitoring capabilities.