Scholarlink

<p>This study presents a biosensor design integrating multiple two-dimensional (2D) materials for brain tumor detection. The sensor architecture features dual circular resonators coated with MXene, square resonators with black phosphorus, and a gold rectangular boundary on a graphene substrate. The device achieves a remarkable sensitivity of 2308&#xa0;GHz/RIU and a figure of merit of 44.379 RIU⁻<sup>1</sup>. Parametric optimization studies demonstrate tunable absorption characteristics through modulation of graphene chemical potential (0.1–0.9&#xa0;eV) and variation of incident angle (0°–80°). The sensor exhibits stable performance with a consistent full width at half maximum (FWHM) of 0.052 THz and detection accuracy of 19.231. Machine learning implementation using the Extra Trees Regressor achieved up to 100% prediction accuracy for incident angle responses. This high-performance biosensor platform offers significant potential for early, non-invasive brain tumor detection and monitoring.</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

Polarization Insensitive Terahertz Surface Plasmon Resonance Biosensor for Brain Tumor Detection with Extra Trees Regressor for Behavior Prediction

  • 期刊论文

  • 发表日期：

    2025年7月2日

查看全文
  • Vithyalakshmi N.,
  • Elamparithi Pandian,
  • Dhivya R.,
  • Sandeep Prabhu

摘要

This study presents a biosensor design integrating multiple two-dimensional (2D) materials for brain tumor detection. The sensor architecture features dual circular resonators coated with MXene, square resonators with black phosphorus, and a gold rectangular boundary on a graphene substrate. The device achieves a remarkable sensitivity of 2308 GHz/RIU and a figure of merit of 44.379 RIU⁻1. Parametric optimization studies demonstrate tunable absorption characteristics through modulation of graphene chemical potential (0.1–0.9 eV) and variation of incident angle (0°–80°). The sensor exhibits stable performance with a consistent full width at half maximum (FWHM) of 0.052 THz and detection accuracy of 19.231. Machine learning implementation using the Extra Trees Regressor achieved up to 100% prediction accuracy for incident angle responses. This high-performance biosensor platform offers significant potential for early, non-invasive brain tumor detection and monitoring.