Hybrid Ag/Graphene/Cu/Al/WS₂ terahertz metasurface biosensing platform for high-sensitivity refractive-index sensing toward wastewater monitoring using machine learning

Abstract Rapid and reliable monitoring of organic contaminants in wastewater requires sensitive sensing platforms capable of resolving small changes in the local dielectric environment. A hybrid Ag/Graphene/Cu/Al/WS₂ asymmetric metasurface is proposed, exploiting plasmonic–excitonic coupling and Fano-type resonance to enhance near-field confinement and refractive-index sensitivity. The 2 × 2 resonator array was numerically investigated using COMSOL Multiphysics over the 0.4–1.4 THz range, with graphene chemical potential, incident angle, resonator geometry, and analyte refractive index systematically varied. The optimized sensor exhibits resonance behavior around 0.74–0.76 THz and achieves a maximum local sensitivity of 909 GHz/RIU and a figure of merit of 17.483 RIU⁻¹ over an RI range of 1.3256–1.542 RIU. Peak transmission remains above 96.7% up to an incidence angle of 80°, while the resonance frequency shows a linear dependence on refractive index with R² = 0.90245. The Random Forest model achieves R² ≥ 0.999735 for transmission prediction. These results establish the proposed hybrid metasurface as a tunable and broad-angle platform for terahertz refractive-index sensing toward wastewater monitoring applications.

Authors

Institutions

Publication Details

Journal
Journal of Optics
Published
2026-09-11
DOI
https://doi.org/10.1007/s12596-026-03286-w
Primary Topic
Metamaterials and Metasurfaces Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Hybrid Ag/Graphene/Cu/Al/WS₂ terahertz metasurface biosensing platform for high-sensitivity refractive-index sensing toward wastewater monitoring using machine learning

Kumaravel Kaliaperumal, V. Kalaipoonguzhali, Jhelai Sahadevan, V. Gomathy et al.
Journal of Optics
Metamaterials and Metasurfaces Applications
article

Hybrid Ag/Graphene/Cu/Al/WS₂ terahertz metasurface biosensing platform for high-sensitivity refractive-index sensing toward wastewater monitoring using machine learning

Kumaravel Kaliaperumal, V. Kalaipoonguzhali, Jhelai Sahadevan, V. Gomathy, Sandeep Prabhu
article en

Abstract

Abstract Rapid and reliable monitoring of organic contaminants in wastewater requires sensitive sensing platforms capable of resolving small changes in the local dielectric environment. A hybrid Ag/Graphene/Cu/Al/WS₂ asymmetric metasurface is proposed, exploiting plasmonic–excitonic coupling and Fano-type resonance to enhance near-field confinement and refractive-index sensitivity. The 2 × 2 resonator array was numerically investigated using COMSOL Multiphysics over the 0.4–1.4 THz range, with graphene chemical potential, incident angle, resonator geometry, and analyte refractive index systematically varied. The optimized sensor exhibits resonance behavior around 0.74–0.76 THz and achieves a maximum local sensitivity of 909 GHz/RIU and a figure of merit of 17.483 RIU⁻¹ over an RI range of 1.3256–1.542 RIU. Peak transmission remains above 96.7% up to an incidence angle of 80°, while the resonance frequency shows a linear dependence on refractive index with R² = 0.90245. The Random Forest model achieves R² ≥ 0.999735 for transmission prediction. These results establish the proposed hybrid metasurface as a tunable and broad-angle platform for terahertz refractive-index sensing toward wastewater monitoring applications.

Journal of Optics
Symbiosis International University (IN), PSG INSTITUTE OF TECHNOLOGY AND APPLIED RESEARCH (IN), Orthopaedic Research Group (IN), KPR Institute of Engineering and Technology (IN), Karpagam Academy of Higher Education (IN), Saveetha University (IN)
Clean water and sanitation
Openalex Percentile: Top 28%
Metamaterials and Metasurfaces Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.