biostudies-literatureUnknown13Tene TThe rapid and accurate detection of SARS-CoV-2 remains a critical challenge in biosensing technology, necessitating the development of highly sensitive and selective platforms. In this study, we present a mathematical modeling approach to optimize a MoSe₂-based Surface Plasmon Resonance (SPR) biosensor for detecting the novel coronavirus at nM scale. Using the Transfer Matrix Method (TMM), we systematically optimize the biosensor's structural parameters, including silver (Ag), silicon nitride (Si₃N₄), molybdenum diselenide (MoSe₂), and thiol-tethered single-stranded DNA (ssDNA) layers, to enhance sensitivity, detection accuracy, and optical performance. The results indicate that an optimized 45 nm Ag layer, 10 nm Si₃N₄ layer, and monolayer MoSe₂ configuration achieves a resonance shift (ΔθFrontiers in bioengineering and biotechnology1547248https://www.ebi.ac.uk/biostudies/studies/S-EPMC11907102biostudies-literatureMathematical modeling of a MoSe₂-based SPR biosensor for detecting SARS-CoV-2 at nM concentrations.PMC11907102Vacacela Gomez CTene TDavalos Villegas MXBonilla Garcia NMarcatoma Tixi JABellucci SfalseMathematical modeling of a MoSe₂-based SPR biosensor for detecting SARS-CoV-2 at nM concentrations.The rapid and accurate detection of SARS-CoV-2 remains a critical challenge in biosensing technology, necessitating the development of highly sensitive and selective platforms. In this study, we present a mathematical modeling approach to optimize a MoSe₂-based Surface Plasmon Resonance (SPR) biosensor for detecting the novel coronavirus at nM scale. Using the Transfer Matrix Method (TMM), we systematically optimize the biosensor's structural parameters, including silver (Ag), silicon nitride (Si₃N₄), molybdenum diselenide (MoSe₂), and thiol-tethered single-stranded DNA (ssDNA) layers, to enhance sensitivity, detection accuracy, and optical performance. The results indicate that an optimized 45 nm Ag layer, 10 nm Si₃N₄ layer, and monolayer MoSe₂ configuration achieves a resonance shift (Δθ2025-01-01T00:00:00Z20252025-04-18T14:02:59.837Z2025-04-06T23:58:43.066ZS-EPMC119071024009237210.3389/fbioe.2025.1547248