Performance Optimization of a Kretschmann‐Configured Multilayer MgO/Ag/HfO 2 /2D‐WS 2 SPR Biosensor for Refractive Index‐Based Cancer Cell Detection: A TMM and FEM Approach

ABSTRACT Cancer remains a major global health burden, causing millions of deaths each year. Therefore, the development of rapid and efficient diagnostic methods is necessary to facilitate effective management and control. In this study, a computational study of a highly sensitive Kretschmann‐configured surface plasmon resonance (SPR) based biosensor is presented for detection of cancerous cells. The proposed biosensor is made up of a multilayer structure comprising a BK7 prism, magnesium oxide (MgO) as an adhesive layer, silver (Ag) as the plasmonic material, hafnium dioxide (HfO 2 ) as the dielectric layer, and a two‐dimensional (2D) material, tungsten disulfide (WS 2 ), to enhance optical performance. Performance metrics were analyzed for sensitivity using the transfer matrix method (TMM) in MATLAB (R2018b), with results validated by the finite element method (FEM) in COMSOL Multiphysics. Optimization of the thicknesses of different layers yielded maximum sensitivity values of 364.28, 320.83, and 245 deg/RIU for the Jurkat, HeLa, and Basal cells, respectively. Furthermore, the proposed biosensor performs well across a wide refractive index range of 1.30–1.39, achieving a linear coefficient of determination (R 2 ) value of 0.9679. The proposed biosensor can serve as a promising candidate for efficient cancer cell detection, as well as for various sensing applications.

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Publication Details

Journal
Advanced Theory and Simulations
Published
2026-10-27
DOI
https://doi.org/10.1002/adts.70590
Primary Topic
Plasmonic and Surface Plasmon Research
Type
article
Field-Weighted Citation Impact
0.00

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Performance Optimization of a Kretschmann‐Configured Multilayer MgO/Ag/HfO 2 /2D‐WS 2 SPR Biosensor for Refractive Index‐Based Cancer Cell Detection: A TMM and FEM Approach

Ajeet Kumar, Saurabh Mani Tripathi, Deepak Kumar Garg
6 links
Advanced Theory and Simulations
Plasmonic and Surface Plasmon Research
article

Performance Optimization of a Kretschmann‐Configured Multilayer MgO/Ag/HfO 2 /2D‐WS 2 SPR Biosensor for Refractive Index‐Based Cancer Cell Detection: A TMM and FEM Approach

Ajeet Kumar, Saurabh Mani Tripathi, Deepak Kumar Garg
article en

Abstract

ABSTRACT Cancer remains a major global health burden, causing millions of deaths each year. Therefore, the development of rapid and efficient diagnostic methods is necessary to facilitate effective management and control. In this study, a computational study of a highly sensitive Kretschmann‐configured surface plasmon resonance (SPR) based biosensor is presented for detection of cancerous cells. The proposed biosensor is made up of a multilayer structure comprising a BK7 prism, magnesium oxide (MgO) as an adhesive layer, silver (Ag) as the plasmonic material, hafnium dioxide (HfO 2 ) as the dielectric layer, and a two‐dimensional (2D) material, tungsten disulfide (WS 2 ), to enhance optical performance. Performance metrics were analyzed for sensitivity using the transfer matrix method (TMM) in MATLAB (R2018b), with results validated by the finite element method (FEM) in COMSOL Multiphysics. Optimization of the thicknesses of different layers yielded maximum sensitivity values of 364.28, 320.83, and 245 deg/RIU for the Jurkat, HeLa, and Basal cells, respectively. Furthermore, the proposed biosensor performs well across a wide refractive index range of 1.30–1.39, achieving a linear coefficient of determination (R 2 ) value of 0.9679. The proposed biosensor can serve as a promising candidate for efficient cancer cell detection, as well as for various sensing applications.

Advanced Theory and SimulationsVol. 9(11)
Indian Institute of Technology Delhi (IN), Delhi Technological University (IN)
Delhi Technological University
Good health and well-being
Openalex Percentile: Top 25%
Plasmonic and Surface Plasmon Research
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Performance Optimization of a Kretschmann‐Configured Multilayer MgO/Ag/HfO 2 /2D‐WS 2 SPR Biosensor for Refractive Index‐Based Cancer Cell Detection: A TMM and FEM Approach — Ajeet Kumar, Saurabh Mani Tripathi, et al. · Advanced Theory and Simulations (2026) | TGRS Research Map | TGRS