Scholarlink

<p>This study presents a novel terahertz metasurface biosensor incorporating graphene-MXene hybrid materials for enhanced salinity detection across environmental and industrial applications. The sensor features a multilayered architecture with three copper-coated rectangular resonators, concentric MXene-coated circular ring resonators, and a graphene-integrated circular base resonator on a silicon dioxide substrate. Numerical simulations using COMSOL Multiphysics demonstrated tunable electromagnetic response through graphene chemical potential modulation (0.1–0.9&#xa0;eV) and maintained stable performance across incident angles up to 60°. The optimized sensor achieved a sensitivity of 286&#xa0;GHz/RIU with a figure of merit of 3.247 RIU⁻<sup>1</sup>, quality factor of 4.398, and detection limit of 0.022 RIU across a refractive index range of 1.3325–1.3505. Experimental validation showed strong correlation (R<sup>2</sup> = 0.80) between theoretical and measured absorption values. The proposed biosensor addresses critical limitations of conventional conductivity-based sensors, offering superior performance in high-salinity and turbid environments while providing real-time monitoring capabilities essential for oceanography, aquaculture, agriculture, and desalination applications.</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

Machine Learning-Enhanced MXene–Copper–Graphene THz Sensor for Accurate Salinity Sensing in Environmental Applications

  • 期刊论文

  • 发表日期：

    2025年7月23日

查看全文
  • Jagannathan Jayachandran,
  • V. Sivakumar,
  • Vijayalakshmi K,
  • Ngaira Mandela

摘要

This study presents a novel terahertz metasurface biosensor incorporating graphene-MXene hybrid materials for enhanced salinity detection across environmental and industrial applications. The sensor features a multilayered architecture with three copper-coated rectangular resonators, concentric MXene-coated circular ring resonators, and a graphene-integrated circular base resonator on a silicon dioxide substrate. Numerical simulations using COMSOL Multiphysics demonstrated tunable electromagnetic response through graphene chemical potential modulation (0.1–0.9 eV) and maintained stable performance across incident angles up to 60°. The optimized sensor achieved a sensitivity of 286 GHz/RIU with a figure of merit of 3.247 RIU⁻1, quality factor of 4.398, and detection limit of 0.022 RIU across a refractive index range of 1.3325–1.3505. Experimental validation showed strong correlation (R2 = 0.80) between theoretical and measured absorption values. The proposed biosensor addresses critical limitations of conventional conductivity-based sensors, offering superior performance in high-salinity and turbid environments while providing real-time monitoring capabilities essential for oceanography, aquaculture, agriculture, and desalination applications.