Surface Plasmon Resonance Biosensor with High Sensitivity for Detecting SARS-CoV-2

Surface Plasmon Resonance Biosensor with High Sensitivity for Detecting SARS-CoV-2 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Surface Plasmon Resonance Biosensor with High Sensitivity for Detecting SARS-CoV-2 Shiven Bhatt, Naina Bose, Kamrun Nahar Shushama, Reefat Inum, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4005654/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Apr, 2024 Read the published version in Plasmonics → Version 1 posted 8 You are reading this latest preprint version Abstract This paper presents a novel surface plasmon resonance (SPR) biosensor based on Kretchmann configuration for detection of SARS-CoV-2. It combines Barium titanate (BaTiO 3 ) dielectric material on top of metal, also 2D material Tungsten Disulfide (WS 2 ) used alongside the traditional prism/metal/sensing layer setup. Sensitivity is enhanced by using BaTiO 3 on silver (Ag) and WS 2 on BaTiO 3 . The integration of these emerging materials into conventional sensor structures has been thoroughly examined to optimize sensor performance. An analysis of key performance parameters has been conducted using the transfer matrix method (TMM) and Fresnel equations, including sensitivity, full width at half-maxima (FWHM), and figure of merit (FOM). The proposed sensor demonstrates an exceptional angular sensitivity of 450°/RIU, with a 3.5° FWHM and a 128.57/RIU FoM. Optimal sensitivity is achieved with a configuration comprising 1 layer of WS 2 in addition to the metal layer. Our proposed SPR sensor shows more sensitivity for detecting SARS-CoV-2 than other proposed SPR sensors in literature. We also analyzed the electric field of the proposed biosensor with Finite Element Method based software and showed its future research aspect. SARS-CoV-2 has been successfully detected in patient samples due to the sensor's increased sensitivity at early stage of this disease. Surface plasmon resonance SARS-CoV-2 2D materials Sensitivity Detection Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction The onset of the lethal coronavirus (COVID-19) stemming from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presented a significant global health challenge. The rapid transmission and extensive impact of this virus have led the World Health Organization (WHO) to designate this outbreak as a pandemic on March 12, 2020 [ 1 – 3 ]. A total of 10925.05 million vaccine doses have been administered as of 27 March 2022. SARS-CoV-2 virus spreads rapidly and accurately, so timely diagnosis is essential. Various techniques, including real-time reverse transcriptase polymerase chain reaction (RT-PCR), antigen testing, and antibody assays, have been implemented [ 2 , 3 ]. However, the development of accurate and rapid detection techniques remains ongoing. Because these existing detection techniques require sophisticated instrument with trained personnel, high cost, time consuming and with some other drawbacks [ 2 , 3 ]. There remains a pressing need for ultra-sensitive, real-time, point-of-care diagnostic methods to further assist healthcare practitioners in combating COVID-19. Surface plasmon resonance (SPR) biosensor an optical based biosensor is proposed as a promising alternative technique for detecting COVID-19 [ 4 – 10 ]. Surface plasmon polariton (SPP) is defined as a wave of electron charge density propagating along the metal-dielectric interface. These waves are confined orthogonally to the metal-dielectric interface. Surface plasmons can be induced by incident light waves, and when certain conditions are met, this excitation at the interface between the metal and dielectric is identified as surface plasmon resonance (SPR) [ 11 – 14 ]. Due to the perpendicular confinement of surface plasmon polariton (SPP) waves at the metal-dielectric interface, only p-polarized light possesses the necessary momentum to excite these surface plasmon polaritons. Two configurations for exciting surface plasmon waves (SPW) exist: the Kretschmann configuration and the Otto configuration [ 12 ]. The utilization of surface plasmons (SPs) in biosensing technology has attracted considerable attention and research interest [ 13 , 15 ]. The sensitivity of Surface Plasmon Waves (SPWs) to changes in the refractive index of the analyte is remarkable. The relationship between reflectance and incident angle, known as the Surface Plasmon Resonance (SPR) curve, demonstrates high responsiveness to fluctuations in the refractive index of the sensing interface [ 11 , 12 ]. Even minor alterations in the refractive index of the sensing medium can lead to a substantial modification in the SPR signal. Attaining highest performance in an SPR biosensor requires maximizing sensitivity. Surface Plasmon Resonance (SPR)-based biosensors are utilized across various domains, encompassing different applications like gas sensing, food safety, enzyme detection, chemical and biochemical sensing, SARS-CoV-2 detection, tuberculosis, DNA-DNA hybridization, protein-protein interactions, protein-DNA interactions, enzyme-substrate studies [ 16 – 23 ]. Different plasmonic materials such as gold (Au), silver (Ag), and copper (Cu) are employed to generate surface plasmons in an SPR sensor [ 24 ]. Silver (Ag) and gold (Au) are favored for their optical properties, characterized by a high SPR ratio and a sharp resonance dip [ 25 ]. Over the past decade, there has been a significant rise in the use of 2D materials, notably Transition Metal Dichalcogenides TMDCs e.g. (MoS 2 , WS 2 , MoSe 2 , WSe 2 ) and graphene, and to a lesser extent, MXenes in SPR-based sensors [ 26 – 34 ]. Considerable focus has shifted towards two-dimensional nanomaterials (2D-nanomaterials) due to their outstanding electrooptic properties in SPR biosensors. Their ultrathin structure, high surface-to-volume ratio, and surface modifications contribute to improved chemical and physical functionality [ 14 , 35 ]. In this paper, an SPR-based structure was proposed, comprising a CaF 2 prism, silver (Ag) as plasmonic metal, BaTiO 3 and WS 2 . WS 2 has unique properties such as high carrier dynamics, high third-order nonlinear susceptibility and broadband light absorption. Nano-scaled WS 2 shows outstanding performance in the field of photo-electronics and plasmonic [ 36 – 39 ]. The adoption of a Barium titanate (BaTiO 3 ) layer is attributed to its excellent dielectric properties, characterized by a high dielectric constant and low dielectric loss. BaTiO 3 has significantly increase the sensitivity of this proposed biosensor [ 6 , 23 , 40 , 41 ]. The performance of this highly sensitive SPR sensor has been tested for the detection of SARS-CoV-2. Our proposed biosensor successfully diagnoses COVID at early stages when the refractive index (RI) of the sample is within 1.33 to 1.34 RIU. Numerical Modeling of Proposed Sensor Reflectivity (R p ) The proposed modified Kretschmann configuration of SPR biosensor is analyzed using five layer model, whose configuration is shown in Fig. 1 . The TM-polarized light incidents upon one lateral face of the prism and reaches to the base of the prism. After reaching the base, light is totally reflected out from the other lateral face. Light is collected and analyzed by a photodetector. For the SPR sensing 633 nm wavelength of excitation light is used. This sensor is composed of prism CaF 2 , metal Ag film, dielectric material BaTiO 3, transition metal dichalcogenides WS 2 as sensing layer. In sensing medium (SM), target analyte e. g. antigen of SARS-CoV-2 is injected through inlet for creating bond with the immobilized target specific antibody coated on the sensor surface and rest of the solution will go outside through outlet. To investigate the optical characteristics of multilayers, transfer matrix method (TMM) and Fresnel equations based on N layer model are used. It is considered that the layers are stacked along the z-axis. Any layer is defined by the thickness d k , dielectric constant ε k , permeability \({\mu }_{k}\) , and refractive index n k where k represents the prism, metal, BaTiO 3 , WS 2 layer, sample or the sensing medium e. g. liquid. All the layers are considered to be uniform, isotropic, and non-magnetic. The tangential fields of the first boundary Z = Z 1 are related to the final boundary Z = Z N−1 by [ 12 , 27 ], $$\left[\begin{array}{c}{A}_{1}\\ {B}_{1}\end{array}\right]= \text{M}\left[\begin{array}{c}{A}_{N-1}\\ {B}_{N-1}\end{array}\right]$$ 1 Here Z = Z 1 = 0 and A 1 , B 1 are the tangential components of electric and magnetic fields at the boundary of first layer respectively. \({A}_{N-1}\) and \({B}_{N-1}\) are the corresponding electric and magnetic fields at the boundary of Nth layer. M is known as characteristic matrix of the combined structure given by [ 12 , 27 ], M = \(\prod _{\text{K}=2}^{\text{N}-1}{\text{M}}_{\text{k}}\) (2) where M k \(= \left[\begin{array}{ccc} \text{cos}{\beta }_{k}& & -i\text{sin}{\beta }_{k}/{q}_{k}\\ & & \\ -i{q}_{k}\text{sin}{\beta }_{k}& & \text{cos}{\beta }_{k}\end{array}\right]\) (3) $${q}_{k} =\frac{{({\epsilon }_{k}-{n}_{c}^{2}{sin}^{2}\theta )}^{1/2}}{{\epsilon }_{k}} , {\beta }_{k}= \frac{2\pi {d}_{k}}{\lambda }\genfrac{}{}{0pt}{}{{ ({\epsilon }_{k}-{n}_{c}^{2}{sin}^{2}\theta )}^{1/2}}{{}_{}}$$ 4 here, θ is the incident angle and 𝞴 is the wavelength of light at the base of CaF 2 prism. The reflection intensity for p -polarized light is R p = \({│\text{r}\text{p}│}^{2}\) where total reflection coefficient, $${\text{r}}_{\text{p}}=\frac{({\text{M}}_{11}+{\text{M}}_{12}{\text{q}}_{\text{N}}){\text{q}}_{1}-({\text{M}}_{21} + {\text{M}}_{22}{\text{q}}_{\text{N}}) }{( {\text{M}}_{11}+ {\text{M}}_{12}{\text{q}}_{\text{N}}){\text{q}}_{1} + ({\text{M}}_{21} +{\text{M}}_{21}{\text{q}}_{\text{N}})}$$ 5 Refractive index of various layers The first layer is a CaF 2 prism. The second layer is Ag film with the thickness of d 2 = 50 nm . The third layer is BaTiO 3 thickness of d 3 = 2.2 nm. The fourth layer is transition metal dichalcogenides WS 2 with the thickness d 4 = M \(\times\) 0.80 nm (M is the number of WS 2 layers). Fifth layer is sensing medium refractive index (RI) 1.33. The refractive index of the CaF 2 prism is as [ 5 , 7 ], $${n}_{1} = {(1+ \frac{0.567888{\lambda }^{2}}{{\lambda }^{2}- {0.0502636}^{2}}+\frac{0.{471091\lambda }^{2}}{{\lambda }^{2}-{0.10039}^{2} }+ \frac{3.848472{\lambda }^{2}}{{\lambda }^{2}-{34.649040}^{2} })}^{1/2}$$ 6 here 𝞴 is the wavelength of the incident light. According to Drude formula, the refractive index ( \({n}_{2}\) ) of Ag or Au metal [ 28 , 42 ], \({n}_{2}\) ( \({\lambda })=\) \({{({\epsilon }}_{\text{m}\text{r}}+\text{i}{ {\epsilon }}_{\text{m}\text{i}})}^{1/2}\) = \(\) \({(1-\frac{{{\lambda }}^{2 } {{\lambda }}_{\text{c}}}{{{\lambda }}_{\text{p}}^{2}\left( {{\lambda }}_{\text{c}}+ \text{i} {\lambda }\right)}) }^{1/2}\) (7) \({{\lambda }}_{\text{p} }\) and \({{\lambda }}_{\text{c}}\) represent the plasma and the collision wavelengths respectively. The optical parameters for Ag, \({\lambda }_{p }\) = 1.4541× \({10}^{-7}\) m and \({ \lambda }_{c}\) = 1.7614 × \({10}^{-5}\) m and Au are \({\lambda }_{p }\) = 1.6826× \({10}^{-7}\) m and \({ \lambda }_{c}\) =8.9342 × \({10}^{-6}\) m. Here, refractive index of BaTiO 3 is 2.404 [ 6 ]. Also, transition metal dichalcogenides WS 2 layer is used. The complex refractive index of WS 2 is taken from L. Wu at 633nm incident wavelength [ 14 ]. Performance parameters Evaluating the performance of an SPR sensor includes assessing its sensitivity, detection accuracy, and quality factor; higher values suggesting superior sensor capabilities. Introducing biomolecules to the sensing medium alters its refractive index, with n 5 fixed at 1.33. Sensitivity is measured as the shift in resonance angle per unit change in the medium's refractive index. The sensitivity of an SPR sensor in angular interrogation is specified by [ 27 ]. S = \(\frac{{\varDelta \theta }_{res}}{\varDelta n}\) (8) Where \(\varDelta\) n represents the change in refractive index of the sensing medium and \({\varDelta \theta }_{res}\) denotes the resulting change in resonance angle due to biomolecule adsorption. Sensitivity is measured in degrees per refractive index unit (deg/RIU). It's considered the paramount parameter for characterizing a biosensor. The detection accuracy (D.A.) is known as signal-to-noise ratio (SNR) [ 43 ]. D.A. = \(\frac{{\varDelta \theta }_{res}}{FWHM}\) (9 ) FWHM represents the full width at half maximum of the SPR curve, a dimensionless parameter. The quality factor (Q) is defined as the ratio of sensitivity (S) to the FWHM of the reflectance curve [ 5 ]. Q = \(\frac{S }{FWHM}\) (10) The unit of quality factor is \({RIU}^{-1}\) . Quality factor is also called figure of merit (FoM) Results & Discussion Effect of prism and metal layer Each of the five layers in our proposed architecture has a significant impact on the overall sensor performance. It is therefore necessary to optimize design parameters in a systematic manner in order to achieve maximum performance from our sensor configuration. Our optimization procedure follows a layer-by-layer approach. In the first step, we investigate sequentially how each layer thickness affects different sensor performance parameters. In this procedure, we first analyze the reflectivity as it varies with incident angle. The lowest reflectivity value is denoted as R min , which correlates closely with the momentum transferred from the light beam to the surface plasmon. Enhanced momentum transfer results in reduced R min . As compared to any other prism for the proposed biosensor, calcium fluoride glass prism (CaF 2 ) offers lowest RI coupling medium and yields maximum angular sensitivity and wide shift in reflectivity. To obtain an almost-ideal reflectance minimum, the used metallic layer must also be optimized to provide a near-zero reflectance minimum. We start our simulation with Ag thickness 50nm. For this analysis we used different prisms CaF 2, BK 7, SF 6, SiO 2 , BaF 2 in addition with Ag metal to observe the sensor performance. Taking into account the refractive indices of prisms, which are 1.4329, 1.5151, 1.799, 1.4607, and 1.4733 respectively [ 7 ], alongside the refractive index (RI) of the sensing medium, denoted as n = 1.33, with a change in RI represented as Δn = 0.005 for the sensing medium, and an Ag thickness of 50 nm, this analysis is depicted in Figs. 2 and 3 (a).We used Eqs. ( 5 ) and (8) for calculating reflectance value and sensitivity. From Fig. 2 , it is seen that lowest reflectance can be achieved with CaF 2 prism which is smaller than others 0.0425. From Fig. 3 (a), it is seen that highest sensitivity 200 deg/RIU is achieved with the combination of CaF 2 prism with Ag metal. We also changed the thickness of Ag layer for optimization and simulated the structure. Figure 3 (b) shows that at 55 nm thickness of Ag layer lowest reflectance value is achieved. After 55 nm increasing the Ag thickness, reflectance value starts to increase. Although, at 55 nm thickness of Ag value reflectance is minimum, we finally choose 50 nm of Ag thickness due to easy fabrication of Ag on prism and reflectance value is very close to lowest minimum reflectance value. Effect of BaTiO 3 and WS 2 on sensor’s performance The Ag metal layer was covered with BaTiO 3 dielectric layer. For optimizing the performance of the sensor, we arbitrarily start the optimization with thickness of BaTiO 3 from 1.65 nm to 3.8 nm thickness in CaF 2 prism-Ag metal structure and observed their sensitivity, detection accuracy, minimum reflectance value and FoM. When BaTiO 3 thickness is 1.65 nm, its sensitivity is 240 deg/RIU, D.A is 0.526 \({deg}^{-1}\) . and FoM is 126.31 \({RIU}^{-1}\) . From Fig. 4 , it is seen that, when the thickness of BaTiO 3 is increasing, sensitivity is also increasing with decreasing detection accuracy. Therefore, FoM is also decreasing. Although the plot shows that optimal thickness of BaTiO 3 is greater than 2.75 nm, we selected a moderate thickness 2.2 nm that provides the structure with a satisfactory balance of minimum reflectivity, sensitivity, detection capability, and figure of merit (FoM) for further optimization of the structure. We chose 2.2 nm thickness of BaTiO 3 for the structure of CaF 2 -Ag metal- BaTiO 3 -sensing medium (SM) where RI of sensing medium is 1.33 and change in RI is 0.005. With this structure, we got 260 deg/RIU sensitivity, 0.476 \({deg}^{-1}\) detection accuracy and 123.8 \({RIU}^{-1}\) FoM. Due to TMDC’s outstanding performance, we chose WS 2 as sensing layer on the top of BaTiO 3 layer for improved functionality of attaching biomolecules. In Fig. 5 , (a) reflectance versus incidence angle curve is shown for CaF 2 -Ag- BaTiO3-sensing medium structure. Here, \({}_{res }\) is 79.9°, \({R}_{min}\) 0.0231 for refractive index (RI) 1.33 and \({}_{res }\) 82.2°, \({R}_{min}\) 0.0057 for refractive index (RI) 1.338. For this structure, we got sensitivity 287.5°. In Fig. 5 , (b) reflectance versus incidence angle curve is shown for CaF 2 -Ag- BaTiO 3 -WS 2 - SM structure. One layer of WS 2 with 0.8 nm thickness was used for simulation. Here, \({}_{res }\) is 83.2°, \({R}_{min}\) 0.0388 for refractive index (RI) 1.33 and \({}_{res }\) is 86.8°, \({R}_{min}\) 0.2908 for refractive index (RI) 1.338. For this structure, we got 450°/ RIU sensitivity. From this analysis we can say that for our proposed structure each layer has significant importance on increasing sensitivity. We also increased the number of WS 2 layers for seeing the effect on sensitivity. We observed that adding second layer of WS 2 layer, sensitivity decreases abruptly with the large increase in minimum reflectance value. So, we decided to choose one layer of WS 2 for this structure. We also analyzed our structure CaF 2 -Ag- BaTiO 3 for other TMDCs (MoS 2 , MoSe 2 , WSe 2 ) and graphene. Here, refractive index for black phosphorus (BP), MoS 2 , WS 2 , MoSe 2 , WSe 2 and graphene are used as 3.5 + 0.01i, 5.08 + 1.1723i,4.9 + 0.3124i, 4.62 + 1.0063i, 4.55 + 0.4332i, 3 + 1.149i respectively [ 14 , 44 ]. In Table 1 , we summarized sensitivity, detection accuracy and FoM for the structure CaF 2 -Ag- BaTiO 3 -fouth layer- SM. Here fourth layer is changed with the materials shown in Table 1 and Δn = 0.008. It is evident from Table 1 , that highest sensitivity is achieved with CaF 2 -Ag- BaTiO 3 -WS 2 - SM structure where detection accuracy and FoM are also reasonable. Table 1 Different materials effect as sensing layer on proposed CaF 2 -Ag- BaTiO 3 structure. Type of 2D materials Thickness (nm) \(\varDelta {\theta }_{res}\) (deg) FWHM (deg) Sensitivity (deg/RIU) D.A ( \({deg}^{-1})\) FoM ( \({RIU}^{-1})\) BP 0.53 nm 2.7 2.2 337.5 0.454 153.40 MoS 2 0.65 nm 3 4.6 375 0.217 81.52 MoSe 2 0.7 nm 3 4.1 375 0.243 91.46 WSe 2 0.7 nm 3.3 3.3 412.5 0.294 121.32 WS 2 0.8 nm 3.6 3.5 450 0.285 128.57 Graphene 0.34 nm 2.4 3 300 0.333 100 Electric Field analysis We confirmed our findings by utilizing Finite Element Method based COMSOL Multiphysics software to analyze the proposed structure. The literature widely acknowledges that as reflectivity decreases to its minimum, the intensity of the magnetic field increases towards its maximum. At the peak field intensity, the excitation of surface plasmons is maximized, resulting in minimal reflected light intensity [ 31 ]. As depicted in Fig. 6 (a), the Ag layer amplifies the field, reaching a peak at the Ag-BaTiO 3 interface due to surface plasmon excitation. Subsequently, the field intensity rises again due to the BaTiO 3 layer and is further enhanced by the WS 2 layer. Electric field distribution is shown in the figure as well. We also observed significant change of the real and imaginary parts of the effective index of the fundamental plasmonic mode supported by the structure as shown in Fig. 7 (a). Consequently, using a similar multilayer configuration (CaF 2 - Ag-BaTiO 3 -WS 2 -SM), a nanophotonic waveguide-based biosensor can be proposed as it shows significant variation in both phase shift (Δφ) and mode propagation length (L p ), shown in Fig. 7 (b). These parameters are related to the effective index as follows [ 45 ], $$\varDelta \varphi ={k}_{0}\{Re\left[{n}_{eff}\left({n}_{s}\right)\right]-Re\left[{n}_{eff}\left(1.33\right)\right]$$ 11 $${L}_{p}=\frac{1}{2{k}_{0}\left|Im\left[{n}_{eff}\right]\right|}$$ 12 SARS-CoV-2 Detection Finally, we applied this sensor for SARS-CoV-2 detection at early stage when viral load in patient is low. Detection of SARS-CoV-2 at very early stage is crucial for several reasons e. g. early intervention, containment of spread, public health management, reducing disease severity etc. A good SPR biosensor can detect a small change in refractive index showing a large variation in resonance shift which is easily detectable. We started our analysis when there are no target analytes of SARS-CoV-2 flowing on the sensor surface. Sensor surface is coated with SARS-CoV-2 target specific ligand (antibody). We considered a medium of phosphate buffered saline (PBS), refractive index 1.3348 as sensing medium with ligand. When target (antigen e.g. N protein, S protein) is added with a certain concentration, the refractive index of the sensing medium is changed due to binding between target analytes and ligand (antigen-antibody interaction). Change in refractive index depends on the target concentration in the sensing medium [ 7 ]. We used this relation for refractive index calculation of the medium, y = 5.1208 \({e}^{-6}\) x + 1.3348, where x is the concentration of target, 1.3348 is PBS refractive index [ 7 ]. In Fig. 8 , we performed our simulation for different cases of target analyte concentrations e.g. 15 nM, 70 nM, 100 nM, 200 nM, 400 nM, 600 nM. There is a significant shift in resonance angle when 15 nM target is added in sensing medium. The change in resonance angle increases with the increasing concentrations of analyte. These values are listed in Table 2 . Table 2 Refractive index, resonance angle and reflectance for different target analyte concentrations for SARS-CoV-2 Detection Target Concentration (nM) RI \({\theta }_{res}\) (deg) \(\varDelta {\theta }_{res}\) (deg) = Target concentration- PBS Reflectance (a.u) 0 nM (PBS) 1.3348 85.2 - 0.1177 15 nM 1.3349 85.3 0.1 0.1203 70 nM 1.3352 85.4 0.2 0.1304 100 nM 1.3353 85.5 0.3 0.1541 200 nM 1.3358 85.8 0.6 0.1541 400 nM 1.3368 86.3 1.1 0.2057 800 nM 1.3389 86.8 1.6 0.2797 From table, it is seen that this proposed sensor can detect target analyte when there is significant shift \({\varDelta \theta }_{res}\) = 0.1 in resonance angle. With the increasing concentration of target analyte, value of \(\varDelta {\theta }_{res}\) increases from 0.1 deg. So, if the resonance angle shift is 0.1deg or more for a suspected SARS-CoV-2 patient’s sample, we can say that the sample contains SARS- CoV-2 target analyte. Additionally, the refractive index increases with the concentration of the target analyte, resulting in an increase in the reflectance value. It is due to a decrease in electric field intensity enhancement factor [ 5 ]. This is because the increasing analyte strongly absorbs most of the incident light. Based on this analysis, it is clear that this biosensor is capable of detecting SARS-CoV-2. Conclusion In this study, we introduced a novel biosensor for SARS-CoV-2 detection utilizing BaTiO 3 and WS 2 . We performed layer by layer optimization of the proposed structure. Transfer matrix method (TMM) and COMSOL were used to conduct the evaluation of the performance of the structure. Initially optimization of prism and Ag thickness were performed to get a reasonable low minimum reflectance value and high sensitivity. After optimizing prism and Ag thickness, we optimized thickness of BaTiO 3 and WS 2 layer. Our optimized structure demonstrated remarkable sensitivity with a value of 450°/RIU, a bandwidth of 3.5° FWHM, and figure of merit (FOM) of 128.57/RIU within the refractive index range of 1.33–1.34. Notably, its sensitivity surpasses that of other SPR biosensors proposed for SARS-CoV-2 detection [ 5 – 8 ]. Furthermore, we showcased the application of this biosensor for early-stage detection. This sensor detects infected and non-infected samples by showing reasonable shift in resonance angle. Its high sensitivity makes it suitable for various other biosensing applications. Declarations Funding Information: The authors did not receive any funding from any organization for this work. Author Contribution Author Contribution The idea was conceived, data collected, analyzed, and interpreted, and the initial draft was written by Shiven Bhatt and Naina Bose. Kamrun Nahar Shushama, Reefat Inum, and K. B. M. Rakib Hasan: responsible for code writing, data gathering, analysis, interpretation, manuscript writing, editing, and final draft creation, serving as mentors for the research activity's planning and execution. All authors contributed equally to this paper. Data Availability The dataset generated during analysis is available in this article. References Yüce M, Filiztekin E, Özkaya KG (2021) COVID-19 diagnosis—A review of current methods. Biosens Bioelectron 172:112752 Kevadiya BD et al (2021) Diagnostics for SARS-CoV-2 infections. Nat Mater 20(5):593–605 Mattioli IA et al (2020) On the challenges for the diagnosis of SARS-CoV-2 based on a review of current methodologies. ACS Sens 5(12):3655–3677 Pandey PS et al (2022) SPR based biosensing chip for COVID-19 diagnosis-A review . IEEE Sens J Srivastava S et al (2023) Numerical study of titanium dioxide and mxene nanomaterial-based surface plasmon resonance biosensor for virus sars-cov-2 detection . 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Opt Quant Electron 54(2):107 Biswas R, Mazumder N (2022) Recent advances in plasmonic probes: Theory and practice. Ouyang Q et al (2016) Sensitivity enhancement of transition metal dichalcogenides/silicon nanostructure-based surface plasmon resonance biosensor. Sci Rep 6(1):28190 Yan P et al (2017) Large-area tungsten disulfide for ultrafast photonics. Nanoscale 9(5):1871–1877 Anower MS, Rahman MS, Rikta KA (2018) Performance enhancement of graphene-coated surface plasmon resonance biosensor using tungsten disulfide. Opt Eng 57(1):017114–017114 Ghodrati M, Mir A, Farmani A (2022) Sensitivity-enhanced surface plasmon resonance sensor with bimetal/tungsten disulfide (WS2)/MXene (Ti3C2Tx) hybrid structure. Plasmonics 17(5):1973–1984 Fouad S et al Enhanced sensitivity of surface plasmon resonance sensor based on bilayers of silver-barium titanate. Журнал нано-та електронної фізики, 2016(8,№ 4 (2)): p. 04085-1-04085-5 Ishtiak KM, Imam S-A, Khosru QD (2022) BaTiO3-Blue Phosphorus/WS2 hybrid structure-based surface plasmon resonance biosensor with enhanced sensor performance for rapid bacterial detection. Results Eng 16:100698 Shushama KN, Rana MM, Inum R (2016) Comparison of two types of graphene coated fiber optic spr biosensors . in 2nd International Conference on Electrical, Computer & Telecommunication Engineering (ICECTE) . 2016. IEEE Rahman MS et al (2020) Enhanced performance of SnSe-Graphene hybrid photonic surface plasmon refractive sensor for biosensing applications. Photonics Nanostructures-Fundamentals Appl 39:100779 Rahman MS et al (2017) Sensitivity analysis of graphene coated surface plasmon resonance biosensors for biosensing applications. Sens bio-sensing Res 16:41–45 Hasan KR, Islam MA, Alam MS (2020) Design of a Broadband Hybrid Plasmonic Waveguide for High Bulk Index Sensitivity . in 11th International Conference on Electrical and Computer Engineering (ICECE) . 2020. IEEE Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 19 Apr, 2024 Read the published version in Plasmonics → Version 1 posted Editorial decision: Revision requested 14 Mar, 2024 Reviews received at journal 05 Mar, 2024 Reviewers agreed at journal 04 Mar, 2024 Reviewers agreed at journal 04 Mar, 2024 Reviewers invited by journal 04 Mar, 2024 Submission checks completed at journal 03 Mar, 2024 Editor assigned by journal 03 Mar, 2024 First submitted to journal 02 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4005654","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":276443589,"identity":"e8dd76d2-d793-4ca5-8e8d-5e14bccb1324","order_by":0,"name":"Shiven Bhatt","email":"","orcid":"","institution":"Monta Vista High School","correspondingAuthor":false,"prefix":"","firstName":"Shiven","middleName":"","lastName":"Bhatt","suffix":""},{"id":276443590,"identity":"a290a894-0fd0-456d-b847-1148ee48cd7b","order_by":1,"name":"Naina Bose","email":"","orcid":"","institution":"Mclean High School","correspondingAuthor":false,"prefix":"","firstName":"Naina","middleName":"","lastName":"Bose","suffix":""},{"id":276443591,"identity":"e93728f7-3038-4cf1-9385-b21fa7580f5d","order_by":2,"name":"Kamrun Nahar Shushama","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxUlEQVRIiWNgGAWjYBACCQYeBgbGBgYGfqgAiE2kFskGkrUYHCBWi2T/2WOSP3fYRRvfSH784QeDjeyGAwS0SEvkpUnznknO3XYjzUyyhyHNmKAWOQkeM2nGNmaglhw2ZgaGw4mEtfCfMZP82Vafu3lGDvNnBob/hLVIM+SYSfC2Hc7dIJED5DAcIKxFckaOsTVv2/HcGWeeAf1ikGw8k5AWifNnDG/+bKvO7W8HhViFnWwfIS1owIA05aNgFIyCUTAKcAAAjQlBZkyGZEMAAAAASUVORK5CYII=","orcid":"","institution":"University of California","correspondingAuthor":true,"prefix":"","firstName":"Kamrun","middleName":"Nahar","lastName":"Shushama","suffix":""},{"id":276443592,"identity":"6d21dab7-5f4e-4ac5-b2bc-f06397f0fd4d","order_by":3,"name":"Reefat Inum","email":"","orcid":"","institution":"University of California","correspondingAuthor":false,"prefix":"","firstName":"Reefat","middleName":"","lastName":"Inum","suffix":""},{"id":276443593,"identity":"0795b566-a466-4209-9883-8cd23522b005","order_by":4,"name":"K. B. M Rakib Hasan","email":"","orcid":"","institution":"University of California","correspondingAuthor":false,"prefix":"","firstName":"K.","middleName":"B. M Rakib","lastName":"Hasan","suffix":""}],"badges":[],"createdAt":"2024-03-02 06:14:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4005654/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4005654/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11468-024-02304-6","type":"published","date":"2024-04-19T23:00:46+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":52103563,"identity":"fbc0959d-cec3-4091-ac3a-cb8aa41e3bc6","added_by":"auto","created_at":"2024-03-06 19:19:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":145919,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of proposed biosensor structure (CaF\u003csub\u003e2 \u003c/sub\u003e-Ag- BaTiO\u003csub\u003e3\u003c/sub\u003e -WS\u003csub\u003e2\u003c/sub\u003e- Sensing Medium) for SARS-CoV-2 Detection.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4005654/v1/fd372814e99577e59fe906bf.png"},{"id":52105391,"identity":"8fb7fe45-184a-4eda-b191-3533896cb043","added_by":"auto","created_at":"2024-03-06 19:27:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":80695,"visible":true,"origin":"","legend":"\u003cp\u003eReflectance versus incidence \u0026nbsp;angle (theta) curve for different prisms-Ag layer structure.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4005654/v1/9bd05155ccaeabd9449c142f.png"},{"id":52103559,"identity":"be176a7c-8843-4f99-a0a3-546eea2138c9","added_by":"auto","created_at":"2024-03-06 19:19:32","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":168868,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Sensitivity curve for different types of prism with Ag metal layer (b) Reflectance curve of CaF\u003csub\u003e2\u003c/sub\u003e-Ag-Sensing medium for different thickness of Ag layer.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4005654/v1/bd9f60c682d82bffd3170cec.png"},{"id":52103561,"identity":"8d5a9bdf-517e-42c3-9c6d-4bf064f5f51d","added_by":"auto","created_at":"2024-03-06 19:19:32","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":60017,"visible":true,"origin":"","legend":"\u003cp\u003eSensitivity \u0026nbsp;\u0026amp; Detection accuracy curves for different thickness of BaTiO\u003csub\u003e3 \u003c/sub\u003elayer.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4005654/v1/57b7d4eb9aaaf8a0a860bedf.png"},{"id":52103565,"identity":"37ed99ec-4b01-4c9f-a818-148236be08fa","added_by":"auto","created_at":"2024-03-06 19:19:32","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":223466,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Reflectance versus incidence angle curve for the structure CaF\u003csub\u003e2\u003c/sub\u003e-Ag- BaTiO\u003csub\u003e3\u003c/sub\u003e-SM (b) Reflectance versus incidence angle curve for the structure CaF\u003csub\u003e2\u003c/sub\u003e-Ag- BaTiO\u003csub\u003e3\u003c/sub\u003e-WS\u003csub\u003e2\u003c/sub\u003e- SM.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4005654/v1/a5a033d374152e2f8cf68ffd.png"},{"id":52103562,"identity":"c07cb48a-af8a-4d11-8a8b-8d011907da85","added_by":"auto","created_at":"2024-03-06 19:19:32","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":121880,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Transverse magnetic field (TM) intensity as function of distance normal to interface for CaF\u003csub\u003e2\u003c/sub\u003e-Ag- BaTiO\u003csub\u003e3\u003c/sub\u003e-WS\u003csub\u003e2\u003c/sub\u003e structure with electric field distribution in inset.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-4005654/v1/5a4d660ca6fe8722880f63bf.png"},{"id":52103566,"identity":"fe469859-6b51-4f22-878c-89d12e442729","added_by":"auto","created_at":"2024-03-06 19:19:32","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":49958,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Real and imaginary part of effective refractive index (b) Plot of phase shift (Df) and mode propagation length (L\u003csub\u003ep\u003c/sub\u003e).\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-4005654/v1/6ab09d7b7fbf38e7095048d0.png"},{"id":52103564,"identity":"96b2d913-501f-4de7-8ab3-dde644cc8b47","added_by":"auto","created_at":"2024-03-06 19:19:32","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":133718,"visible":true,"origin":"","legend":"\u003cp\u003eResonance angle shift of SPR curves with varying concentration of target of SARS-CoV-2.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-4005654/v1/80dc5b353122c8804aa39976.png"},{"id":55691108,"identity":"98d9336a-8d09-4064-8452-7bc08f55457d","added_by":"auto","created_at":"2024-05-01 23:01:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1617544,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4005654/v1/11da41e1-482b-4da6-bed1-649a4f2f25c2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Surface Plasmon Resonance Biosensor with High Sensitivity for Detecting SARS-CoV-2","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe onset of the lethal coronavirus (COVID-19) stemming from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presented a significant global health challenge. The rapid transmission and extensive impact of this virus have led the World Health Organization (WHO) to designate this outbreak as a pandemic on March 12, 2020 [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. A total of 10925.05\u0026nbsp;million vaccine doses have been administered as of 27 March 2022. SARS-CoV-2 virus spreads rapidly and accurately, so timely diagnosis is essential. Various techniques, including real-time reverse transcriptase polymerase chain reaction (RT-PCR), antigen testing, and antibody assays, have been implemented [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, the development of accurate and rapid detection techniques remains ongoing. Because these existing detection techniques require sophisticated instrument with trained personnel, high cost, time consuming and with some other drawbacks [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. There remains a pressing need for ultra-sensitive, real-time, point-of-care diagnostic methods to further assist healthcare practitioners in combating COVID-19. Surface plasmon resonance (SPR) biosensor an optical based biosensor is proposed as a promising alternative technique for detecting COVID-19 [\u003cspan additionalcitationids=\"CR5 CR6 CR7 CR8 CR9\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSurface plasmon polariton (SPP) is defined as a wave of electron charge density propagating along the metal-dielectric interface. These waves are confined orthogonally to the metal-dielectric interface. Surface plasmons can be induced by incident light waves, and when certain conditions are met, this excitation at the interface between the metal and dielectric is identified as surface plasmon resonance (SPR) [\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Due to the perpendicular confinement of surface plasmon polariton (SPP) waves at the metal-dielectric interface, only p-polarized light possesses the necessary momentum to excite these surface plasmon polaritons. Two configurations for exciting surface plasmon waves (SPW) exist: the Kretschmann configuration and the Otto configuration [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The utilization of surface plasmons (SPs) in biosensing technology has attracted considerable attention and research interest [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The sensitivity of Surface Plasmon Waves (SPWs) to changes in the refractive index of the analyte is remarkable. The relationship between reflectance and incident angle, known as the Surface Plasmon Resonance (SPR) curve, demonstrates high responsiveness to fluctuations in the refractive index of the sensing interface [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Even minor alterations in the refractive index of the sensing medium can lead to a substantial modification in the SPR signal. Attaining highest performance in an SPR biosensor requires maximizing sensitivity. Surface Plasmon Resonance (SPR)-based biosensors are utilized across various domains, encompassing different applications like gas sensing, food safety, enzyme detection, chemical and biochemical sensing, SARS-CoV-2 detection, tuberculosis, DNA-DNA hybridization, protein-protein interactions, protein-DNA interactions, enzyme-substrate studies [\u003cspan additionalcitationids=\"CR17 CR18 CR19 CR20 CR21 CR22\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDifferent plasmonic materials such as gold (Au), silver (Ag), and copper (Cu) are employed to generate surface plasmons in an SPR sensor [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Silver (Ag) and gold (Au) are favored for their optical properties, characterized by a high SPR ratio and a sharp resonance dip [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Over the past decade, there has been a significant rise in the use of 2D materials, notably Transition Metal Dichalcogenides TMDCs e.g. (MoS\u003csub\u003e2\u003c/sub\u003e, WS\u003csub\u003e2\u003c/sub\u003e, MoSe\u003csub\u003e2\u003c/sub\u003e, WSe\u003csub\u003e2\u003c/sub\u003e) and graphene, and to a lesser extent, MXenes in SPR-based sensors [\u003cspan additionalcitationids=\"CR27 CR28 CR29 CR30 CR31 CR32 CR33\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Considerable focus has shifted towards two-dimensional nanomaterials (2D-nanomaterials) due to their outstanding electrooptic properties in SPR biosensors. Their ultrathin structure, high surface-to-volume ratio, and surface modifications contribute to improved chemical and physical functionality [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In this paper, an SPR-based structure was proposed, comprising a CaF\u003csub\u003e2\u003c/sub\u003e prism, silver (Ag) as plasmonic metal, BaTiO\u003csub\u003e3\u003c/sub\u003e and WS\u003csub\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e2\u003c/span\u003e\u003c/sub\u003e. WS\u003csub\u003e2\u003c/sub\u003e has unique properties such as high carrier dynamics, high third-order nonlinear susceptibility and broadband light absorption. Nano-scaled WS\u003csub\u003e2\u003c/sub\u003e shows outstanding performance in the field of photo-electronics and plasmonic [\u003cspan additionalcitationids=\"CR37 CR38\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The adoption of a Barium titanate (BaTiO\u003csub\u003e3\u003c/sub\u003e) layer is attributed to its excellent dielectric properties, characterized by a high dielectric constant and low dielectric loss. BaTiO\u003csub\u003e3\u003c/sub\u003e has significantly increase the sensitivity of this proposed biosensor [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The performance of this highly sensitive SPR sensor has been tested for the detection of SARS-CoV-2. Our proposed biosensor successfully diagnoses COVID at early stages when the refractive index (RI) of the sample is within 1.33 to 1.34 RIU.\u003c/p\u003e"},{"header":"Numerical Modeling of Proposed Sensor","content":"\u003cp\u003e \u003cb\u003eReflectivity (R\u003c/b\u003e \u003csub\u003e \u003cb\u003ep\u003c/b\u003e \u003c/sub\u003e \u003cb\u003e)\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe proposed modified Kretschmann configuration of SPR biosensor is analyzed using five layer model, whose configuration is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The TM-polarized light incidents upon one lateral face of the prism and reaches to the base of the prism. After reaching the base, light is totally reflected out from the other lateral face. Light is collected and analyzed by a photodetector. For the SPR sensing 633 nm wavelength of excitation light is used. This sensor is composed of prism CaF\u003csub\u003e2\u003c/sub\u003e, metal Ag film, dielectric material BaTiO\u003csub\u003e3,\u003c/sub\u003e transition metal dichalcogenides WS\u003csub\u003e2\u003c/sub\u003e as sensing layer. In sensing medium (SM), target analyte e. g. antigen of SARS-CoV-2 is injected through inlet for creating bond with the immobilized target specific antibody coated on the sensor surface and rest of the solution will go outside through outlet. To investigate the optical characteristics of multilayers, transfer matrix method (TMM) and Fresnel equations based on N layer model are used. It is considered that the layers are stacked along the z-axis. Any layer is defined by the thickness d\u003csub\u003ek\u003c/sub\u003e, dielectric constant ε\u003csub\u003ek\u003c/sub\u003e, permeability \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\mu }_{k}\\)\u003c/span\u003e\u003c/span\u003e, and refractive index n\u003csub\u003ek\u003c/sub\u003e where k represents the prism, metal, BaTiO\u003csub\u003e3\u003c/sub\u003e, WS\u003csub\u003e2\u003c/sub\u003e layer, sample or the sensing medium e. g. liquid. All the layers are considered to be\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003euniform, isotropic, and non-magnetic. The tangential fields of the first boundary Z\u0026thinsp;=\u0026thinsp;Z\u003csub\u003e1\u003c/sub\u003e are related to the final boundary Z\u0026thinsp;=\u0026thinsp;Z\u003csub\u003eN\u0026minus;1\u003c/sub\u003e by [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e],\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\left[\\begin{array}{c}{A}_{1}\\\\ {B}_{1}\\end{array}\\right]= \\text{M}\\left[\\begin{array}{c}{A}_{N-1}\\\\ {B}_{N-1}\\end{array}\\right]$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eHere Z\u0026thinsp;=\u0026thinsp;Z\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0 and A\u003csub\u003e1\u003c/sub\u003e, B\u003csub\u003e1\u003c/sub\u003e are the tangential components of electric and magnetic fields at the boundary of first layer respectively. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({A}_{N-1}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({B}_{N-1}\\)\u003c/span\u003e\u003c/span\u003e are the corresponding electric and magnetic fields at the boundary of Nth layer. M is known as characteristic matrix of the combined structure given by [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e],\u003c/p\u003e \u003cp\u003eM =\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\prod _{\\text{K}=2}^{\\text{N}-1}{\\text{M}}_{\\text{k}}\\)\u003c/span\u003e\u003c/span\u003e (2)\u003c/p\u003e \u003cp\u003ewhere\u003c/p\u003e \u003cp\u003eM\u003csub\u003e\u003cem\u003ek\u003c/em\u003e\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(= \\left[\\begin{array}{ccc} \\text{cos}{\\beta }_{k}\u0026amp; \u0026amp; -i\\text{sin}{\\beta }_{k}/{q}_{k}\\\\ \u0026amp; \u0026amp; \\\\ -i{q}_{k}\\text{sin}{\\beta }_{k}\u0026amp; \u0026amp; \\text{cos}{\\beta }_{k}\\end{array}\\right]\\)\u003c/span\u003e\u003c/span\u003e (3)\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$${q}_{k} =\\frac{{({\\epsilon }_{k}-{n}_{c}^{2}{sin}^{2}\\theta )}^{1/2}}{{\\epsilon }_{k}} , {\\beta }_{k}= \\frac{2\\pi {d}_{k}}{\\lambda }\\genfrac{}{}{0pt}{}{{ ({\\epsilon }_{k}-{n}_{c}^{2}{sin}^{2}\\theta )}^{1/2}}{{}_{}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ehere, θ is the incident angle and \u0026#120756; is the wavelength of light at the base of CaF\u003csub\u003e2\u003c/sub\u003e prism. The reflection intensity for \u003cem\u003ep\u003c/em\u003e-polarized light is R\u003csub\u003ep\u003c/sub\u003e = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({│\\text{r}\\text{p}│}^{2}\\)\u003c/span\u003e\u003c/span\u003e where total reflection coefficient,\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$${\\text{r}}_{\\text{p}}=\\frac{({\\text{M}}_{11}+{\\text{M}}_{12}{\\text{q}}_{\\text{N}}){\\text{q}}_{1}-({\\text{M}}_{21} + {\\text{M}}_{22}{\\text{q}}_{\\text{N}}) }{( {\\text{M}}_{11}+ {\\text{M}}_{12}{\\text{q}}_{\\text{N}}){\\text{q}}_{1} + ({\\text{M}}_{21} +{\\text{M}}_{21}{\\text{q}}_{\\text{N}})}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e5\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eRefractive index of various layers\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe first layer is a CaF\u003csub\u003e2\u003c/sub\u003e prism. The second layer is Ag film with the thickness of \u003cem\u003ed\u003c/em\u003e\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;50 \u003cem\u003enm\u003c/em\u003e. The third layer is BaTiO\u003csub\u003e3\u003c/sub\u003e thickness of d\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;2.2 nm. The fourth layer is transition metal dichalcogenides WS\u003csub\u003e2\u003c/sub\u003e with the thickness d\u003csub\u003e4\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;M \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e 0.80 nm (M is the number of WS\u003csub\u003e2\u003c/sub\u003e layers). Fifth layer is sensing medium refractive index (RI) 1.33.\u003c/p\u003e \u003cp\u003eThe refractive index of the CaF\u003csub\u003e2\u003c/sub\u003e prism is as [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e],\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$${n}_{1} = {(1+ \\frac{0.567888{\\lambda }^{2}}{{\\lambda }^{2}- {0.0502636}^{2}}+\\frac{0.{471091\\lambda }^{2}}{{\\lambda }^{2}-{0.10039}^{2} }+ \\frac{3.848472{\\lambda }^{2}}{{\\lambda }^{2}-{34.649040}^{2} })}^{1/2}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e6\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ehere \u0026#120756; is the wavelength of the incident light. According to Drude formula, the refractive index (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({n}_{2}\\)\u003c/span\u003e\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eof Ag or Au metal [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e],\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\({n}_{2}\\)\u003c/span\u003e \u003c/span\u003e(\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\lambda })=\\)\u003c/span\u003e\u003c/span\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({{({\\epsilon }}_{\\text{m}\\text{r}}+\\text{i}{ {\\epsilon }}_{\\text{m}\\text{i}})}^{1/2}\\)\u003c/span\u003e\u003c/span\u003e = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\)\u003c/span\u003e\u003c/span\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({(1-\\frac{{{\\lambda }}^{2 } {{\\lambda }}_{\\text{c}}}{{{\\lambda }}_{\\text{p}}^{2}\\left( {{\\lambda }}_{\\text{c}}+ \\text{i} {\\lambda }\\right)}) }^{1/2}\\)\u003c/span\u003e\u003c/span\u003e (7)\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\({{\\lambda }}_{\\text{p} }\\)\u003c/span\u003e \u003c/span\u003eand \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({{\\lambda }}_{\\text{c}}\\)\u003c/span\u003e\u003c/span\u003e represent the plasma and the collision wavelengths respectively. The optical parameters for Ag, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\lambda }_{p }\\)\u003c/span\u003e\u003c/span\u003e= 1.4541\u0026times;\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({10}^{-7}\\)\u003c/span\u003e\u003c/span\u003e m and\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({ \\lambda }_{c}\\)\u003c/span\u003e\u003c/span\u003e = 1.7614 \u0026times;\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({10}^{-5}\\)\u003c/span\u003e\u003c/span\u003em and Au are \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\lambda }_{p }\\)\u003c/span\u003e\u003c/span\u003e= 1.6826\u0026times;\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({10}^{-7}\\)\u003c/span\u003e\u003c/span\u003e m and\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({ \\lambda }_{c}\\)\u003c/span\u003e\u003c/span\u003e =8.9342 \u0026times;\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({10}^{-6}\\)\u003c/span\u003e\u003c/span\u003em.\u003c/p\u003e \u003cp\u003eHere, refractive index of BaTiO\u003csub\u003e3\u003c/sub\u003e is 2.404 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Also, transition metal dichalcogenides WS\u003csub\u003e2\u003c/sub\u003e layer is used. The complex refractive index of WS\u003csub\u003e2\u003c/sub\u003e is taken from L. Wu at 633nm incident wavelength [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003ePerformance parameters\u003c/b\u003e \u003c/p\u003e \u003cp\u003eEvaluating the performance of an SPR sensor includes assessing its sensitivity, detection accuracy, and quality factor; higher values suggesting superior sensor capabilities. Introducing biomolecules to the sensing medium alters its refractive index, with n\u003csub\u003e5\u003c/sub\u003e fixed at 1.33. Sensitivity is measured as the shift in resonance angle per unit change in the medium's refractive index. The sensitivity of an SPR sensor in angular interrogation is specified by [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eS = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{\\varDelta \\theta }_{res}}{\\varDelta n}\\)\u003c/span\u003e\u003c/span\u003e (8)\u003c/p\u003e \u003cp\u003eWhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varDelta\\)\u003c/span\u003e\u003c/span\u003en represents the change in refractive index of the sensing medium and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varDelta \\theta }_{res}\\)\u003c/span\u003e\u003c/span\u003e denotes the resulting change in resonance angle due to biomolecule adsorption. Sensitivity is measured in degrees per refractive index unit (deg/RIU). It's considered the paramount parameter for characterizing a biosensor.\u003c/p\u003e \u003cp\u003eThe detection accuracy (D.A.) is known as signal-to-noise ratio (SNR) [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eD.A. = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{\\varDelta \\theta }_{res}}{FWHM}\\)\u003c/span\u003e\u003c/span\u003e (9 )\u003c/p\u003e \u003cp\u003eFWHM represents the full width at half maximum of the SPR curve, a dimensionless parameter. The quality factor (Q) is defined as the ratio of sensitivity (S) to the FWHM of the reflectance curve [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eQ = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{S }{FWHM}\\)\u003c/span\u003e\u003c/span\u003e (10)\u003c/p\u003e \u003cp\u003eThe unit of quality factor is \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({RIU}^{-1}\\)\u003c/span\u003e\u003c/span\u003e. Quality factor is also called figure of merit (FoM)\u003c/p\u003e"},{"header":"Results \u0026 Discussion","content":"\u003cp\u003e \u003cb\u003eEffect of prism and metal layer\u003c/b\u003e \u003c/p\u003e \u003cp\u003eEach of the five layers in our proposed architecture has a significant impact on the overall sensor performance. It is therefore necessary to optimize design parameters in a systematic manner in order to achieve maximum performance from our sensor configuration. Our optimization procedure follows a layer-by-layer approach. In the first step, we investigate sequentially how each layer thickness affects different sensor performance parameters. In this procedure, we first analyze the reflectivity as it varies with incident angle. The lowest reflectivity value is denoted as R\u003csub\u003e\u003cem\u003emin\u003c/em\u003e\u003c/sub\u003e, which correlates closely with the momentum transferred from the light beam to the surface plasmon. Enhanced momentum transfer results in reduced R\u003csub\u003e\u003cem\u003emin\u003c/em\u003e\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs compared to any other prism for the proposed biosensor, calcium fluoride glass prism (CaF\u003csub\u003e2\u003c/sub\u003e) offers lowest RI coupling medium and yields maximum angular sensitivity and wide shift in reflectivity. To obtain an almost-ideal reflectance minimum, the used metallic layer must also be optimized to provide a near-zero reflectance minimum. We start our simulation with Ag thickness 50nm. For this analysis we used different prisms CaF\u003csub\u003e2,\u003c/sub\u003e BK\u003csub\u003e7,\u003c/sub\u003e SF\u003csub\u003e6,\u003c/sub\u003e SiO\u003csub\u003e2\u003c/sub\u003e, BaF\u003csub\u003e2\u003c/sub\u003e in addition with Ag metal to observe the sensor performance. Taking into account the refractive indices of prisms, which are 1.4329, 1.5151, 1.799, 1.4607, and 1.4733 respectively [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], alongside the refractive index (RI) of the sensing medium, denoted as n\u0026thinsp;=\u0026thinsp;1.33, with a change in RI represented as Δn\u0026thinsp;=\u0026thinsp;0.005 for the sensing medium, and an Ag thickness of 50 nm, this analysis is depicted in Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (a).We used Eqs.\u0026nbsp;(\u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e5\u003c/span\u003e) and (8) for calculating reflectance value and sensitivity. From Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, it is seen that lowest reflectance can be achieved with CaF\u003csub\u003e2\u003c/sub\u003e prism which is smaller than others 0.0425.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFrom Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (a), it is seen that highest sensitivity 200 deg/RIU is achieved with the combination of CaF\u003csub\u003e2\u003c/sub\u003e prism with Ag metal. We also changed the thickness of Ag layer for optimization and simulated the structure. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e(b) shows that at 55 nm thickness of Ag layer lowest reflectance value is achieved. After 55 nm increasing the Ag thickness, reflectance value starts to increase. Although, at 55 nm thickness of Ag value reflectance is minimum, we finally choose 50 nm of Ag thickness due to easy fabrication of Ag on prism and reflectance value is very close to lowest minimum reflectance value.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEffect of BaTiO\u003c/b\u003e \u003csub\u003e \u003cb\u003e3\u003c/b\u003e \u003c/sub\u003e \u003cb\u003eand WS\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e \u003cb\u003eon sensor\u0026rsquo;s performance\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe Ag metal layer was covered with BaTiO\u003csub\u003e3\u003c/sub\u003e dielectric layer. For optimizing the performance of the sensor, we arbitrarily start the optimization with thickness of BaTiO\u003csub\u003e3\u003c/sub\u003e from 1.65 nm to 3.8 nm thickness in CaF\u003csub\u003e2\u003c/sub\u003e prism-Ag metal structure and observed their sensitivity, detection accuracy, minimum reflectance value and FoM. When BaTiO\u003csub\u003e3\u003c/sub\u003e thickness is 1.65 nm, its sensitivity is 240 deg/RIU, D.A is 0.526 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({deg}^{-1}\\)\u003c/span\u003e\u003c/span\u003e. and FoM is 126.31 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({RIU}^{-1}\\)\u003c/span\u003e\u003c/span\u003e. From Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, it is seen that, when the thickness of BaTiO\u003csub\u003e3\u003c/sub\u003e is increasing, sensitivity is also increasing with decreasing detection accuracy. Therefore, FoM is also decreasing. Although the plot shows that optimal thickness of BaTiO\u003csub\u003e3\u003c/sub\u003e is greater than 2.75 nm, we selected a moderate thickness 2.2 nm that provides the structure with a satisfactory balance of minimum reflectivity, sensitivity, detection capability, and figure of merit (FoM) for further optimization of the structure. We chose 2.2 nm thickness of BaTiO\u003csub\u003e3\u003c/sub\u003e for the structure of CaF\u003csub\u003e2\u003c/sub\u003e-Ag metal- BaTiO\u003csub\u003e3\u003c/sub\u003e-sensing medium (SM) where RI of sensing medium is 1.33 and change in RI is 0.005. With this structure, we got 260 deg/RIU sensitivity, 0.476 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({deg}^{-1}\\)\u003c/span\u003e\u003c/span\u003e detection accuracy and 123.8 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({RIU}^{-1}\\)\u003c/span\u003e\u003c/span\u003e FoM.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDue to TMDC\u0026rsquo;s outstanding performance, we chose WS\u003csub\u003e2\u003c/sub\u003e as sensing layer on the top of BaTiO\u003csub\u003e3\u003c/sub\u003e layer for improved functionality of attaching biomolecules. In Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, (a) reflectance versus incidence angle curve is shown for CaF\u003csub\u003e2\u003c/sub\u003e-Ag- BaTiO3-sensing medium structure. Here, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({}_{res }\\)\u003c/span\u003e\u003c/span\u003e is 79.9\u0026deg;, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({R}_{min}\\)\u003c/span\u003e\u003c/span\u003e 0.0231 for refractive index (RI) 1.33 and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({}_{res }\\)\u003c/span\u003e\u003c/span\u003e 82.2\u0026deg;, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({R}_{min}\\)\u003c/span\u003e\u003c/span\u003e 0.0057 for refractive index (RI) 1.338. For this structure, we got sensitivity 287.5\u0026deg;. In Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, (b) reflectance versus incidence angle curve is shown for CaF\u003csub\u003e2\u003c/sub\u003e-Ag- BaTiO\u003csub\u003e3\u003c/sub\u003e-WS\u003csub\u003e2\u003c/sub\u003e- SM structure. One layer of WS\u003csub\u003e2\u003c/sub\u003e with 0.8 nm thickness was used for simulation. Here, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({}_{res }\\)\u003c/span\u003e\u003c/span\u003e is 83.2\u0026deg;, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({R}_{min}\\)\u003c/span\u003e\u003c/span\u003e 0.0388 for refractive index (RI) 1.33 and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({}_{res }\\)\u003c/span\u003e\u003c/span\u003e is 86.8\u0026deg;, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({R}_{min}\\)\u003c/span\u003e\u003c/span\u003e 0.2908 for refractive index (RI) 1.338. For this structure, we got 450\u0026deg;/\u003cem\u003eRIU\u003c/em\u003e sensitivity. From this analysis we can say that for our proposed structure each layer has significant importance on increasing sensitivity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe also increased the number of WS\u003csub\u003e2\u003c/sub\u003e layers for seeing the effect on sensitivity. We observed that adding second layer of WS\u003csub\u003e2\u003c/sub\u003e layer, sensitivity decreases abruptly with the large increase in minimum reflectance value. So, we decided to choose one layer of WS\u003csub\u003e2\u003c/sub\u003e for this structure. We also analyzed our structure CaF\u003csub\u003e2\u003c/sub\u003e-Ag- BaTiO\u003csub\u003e3\u003c/sub\u003e for other TMDCs (MoS\u003csub\u003e2\u003c/sub\u003e, MoSe\u003csub\u003e2\u003c/sub\u003e, WSe\u003csub\u003e2\u003c/sub\u003e) and graphene. Here, refractive index for black phosphorus (BP), MoS\u003csub\u003e2\u003c/sub\u003e, WS\u003csub\u003e2\u003c/sub\u003e, MoSe\u003csub\u003e2\u003c/sub\u003e, WSe\u003csub\u003e2\u003c/sub\u003e and graphene are used as 3.5\u0026thinsp;+\u0026thinsp;0.01i, 5.08\u0026thinsp;+\u0026thinsp;1.1723i,4.9\u0026thinsp;+\u0026thinsp;0.3124i, 4.62\u0026thinsp;+\u0026thinsp;1.0063i, 4.55\u0026thinsp;+\u0026thinsp;0.4332i, 3\u0026thinsp;+\u0026thinsp;1.149i respectively [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. In Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, we summarized sensitivity, detection accuracy and FoM for the structure CaF\u003csub\u003e2\u003c/sub\u003e-Ag- BaTiO\u003csub\u003e3\u003c/sub\u003e-fouth layer- SM. Here fourth layer is changed with the materials shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Δn\u0026thinsp;=\u0026thinsp;0.008. It is evident from Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, that highest sensitivity is achieved with CaF\u003csub\u003e2\u003c/sub\u003e-Ag- BaTiO\u003csub\u003e3\u003c/sub\u003e-WS\u003csub\u003e2\u003c/sub\u003e- SM structure where detection accuracy and FoM are also reasonable.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferent materials effect as sensing layer on proposed CaF\u003csub\u003e2\u003c/sub\u003e-Ag- BaTiO\u003csub\u003e3\u003c/sub\u003e structure.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of 2D materials\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThickness\u003c/p\u003e \u003cp\u003e(nm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varDelta {\\theta }_{res}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003e(deg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFWHM\u003c/p\u003e \u003cp\u003e(deg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003cp\u003e(deg/RIU)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eD.A\u003c/p\u003e \u003cp\u003e(\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({deg}^{-1})\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFoM\u003c/p\u003e \u003cp\u003e(\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({RIU}^{-1})\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.53 nm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e337.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e153.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoS\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.65 nm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e81.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoSe\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.7 nm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e91.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWSe\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.7 nm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e412.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e121.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWS\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.8 nm\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e450\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.285\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e128.57\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGraphene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.34 nm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eElectric Field analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe confirmed our findings by utilizing Finite Element Method based COMSOL Multiphysics software to analyze the proposed structure. The literature widely acknowledges that as reflectivity decreases to its minimum, the intensity of the magnetic field increases towards its maximum. At the peak field intensity, the excitation of surface plasmons is maximized, resulting in minimal reflected light intensity [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. As depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e(a), the Ag layer amplifies the field, reaching a peak at the Ag-BaTiO\u003csub\u003e3\u003c/sub\u003e interface due to surface plasmon excitation. Subsequently, the field intensity rises again due to the BaTiO\u003csub\u003e3\u003c/sub\u003e layer and is further enhanced by the WS\u003csub\u003e2\u003c/sub\u003e layer. Electric field distribution is shown in the figure as well.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe also observed significant change of the real and imaginary parts of the effective index of the fundamental plasmonic mode supported by the structure as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e (a).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eConsequently, using a similar multilayer configuration (CaF\u003csub\u003e2\u003c/sub\u003e- Ag-BaTiO\u003csub\u003e3\u003c/sub\u003e-WS\u003csub\u003e2\u003c/sub\u003e-SM), a nanophotonic waveguide-based biosensor can be proposed as it shows significant variation in both phase shift (Δφ) and mode propagation length (L\u003csub\u003ep\u003c/sub\u003e), shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e (b). These parameters are related to the effective index as follows [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e],\u003cdiv id=\"Equ5\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ5\" name=\"EquationSource\"\u003e\n$$\\varDelta \\varphi ={k}_{0}\\{Re\\left[{n}_{eff}\\left({n}_{s}\\right)\\right]-Re\\left[{n}_{eff}\\left(1.33\\right)\\right]$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e11\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ6\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ6\" name=\"EquationSource\"\u003e\n$${L}_{p}=\\frac{1}{2{k}_{0}\\left|Im\\left[{n}_{eff}\\right]\\right|}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e12\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eSARS-CoV-2 Detection\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFinally, we applied this sensor for SARS-CoV-2 detection at early stage when viral load in patient is low. Detection of SARS-CoV-2 at very early stage is crucial for several reasons e. g. early intervention, containment of spread, public health management, reducing disease severity etc. A good SPR biosensor can detect a small change in refractive index showing a large variation in resonance shift which is easily detectable. We started our analysis when there are no target analytes of SARS-CoV-2 flowing on the sensor surface. Sensor surface is coated with SARS-CoV-2 target specific ligand (antibody). We considered a medium of phosphate buffered saline (PBS), refractive index 1.3348 as sensing medium with ligand. When target (antigen e.g. N protein, S protein) is added with a certain concentration, the refractive index of the sensing medium is changed due to binding between target analytes and ligand (antigen-antibody interaction). Change in refractive index depends on the target concentration in the sensing medium [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. We used this relation for refractive index calculation of the medium, y\u0026thinsp;=\u0026thinsp;5.1208\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({e}^{-6}\\)\u003c/span\u003e\u003c/span\u003e x\u0026thinsp;+\u0026thinsp;1.3348, where x is the concentration of target, 1.3348 is PBS refractive index [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, we performed our simulation for different cases of target analyte concentrations e.g. 15 nM, 70 nM, 100 nM, 200 nM, 400 nM, 600 nM. There is a significant shift in resonance angle when 15 nM target is added in sensing medium. The change in resonance angle increases with the increasing concentrations of analyte. These values are listed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRefractive index, resonance angle and reflectance for different target analyte concentrations for SARS-CoV-2 Detection\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTarget Concentration (nM)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\theta }_{res}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003e(deg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varDelta {\\theta }_{res}\\)\u003c/span\u003e\u003c/span\u003e (deg)\u0026thinsp;=\u0026thinsp;Target concentration- PBS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReflectance (a.u)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 nM (PBS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.3348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15 nM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.3349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1203\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70 nM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.3352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1304\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100 nM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.3353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1541\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e200 nM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.3358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1541\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e400 nM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.3368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.2057\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e800 nM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.3389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.2797\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFrom table, it is seen that this proposed sensor can detect target analyte when there is significant shift \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varDelta \\theta }_{res}\\)\u003c/span\u003e\u003c/span\u003e = 0.1 in resonance angle. With the increasing concentration of target analyte, value of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varDelta {\\theta }_{res}\\)\u003c/span\u003e\u003c/span\u003e increases from 0.1 deg. So, if the resonance angle shift is 0.1deg or more for a suspected SARS-CoV-2 patient\u0026rsquo;s sample, we can say that the sample contains SARS- CoV-2 target analyte. Additionally, the refractive index increases with the concentration of the target analyte, resulting in an increase in the reflectance value. It is due to a decrease in electric field intensity enhancement factor [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This is because the increasing analyte strongly absorbs most of the incident light. Based on this analysis, it is clear that this biosensor is capable of detecting SARS-CoV-2.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, we introduced a novel biosensor for SARS-CoV-2 detection utilizing BaTiO\u003csub\u003e3\u003c/sub\u003e and WS\u003csub\u003e2\u003c/sub\u003e. We performed layer by layer optimization of the proposed structure. Transfer matrix method (TMM) and COMSOL were used to conduct the evaluation of the performance of the structure. Initially optimization of prism and Ag thickness were performed to get a reasonable low minimum reflectance value and high sensitivity. After optimizing prism and Ag thickness, we optimized thickness of BaTiO\u003csub\u003e3\u003c/sub\u003e and WS\u003csub\u003e2\u003c/sub\u003e layer. Our optimized structure demonstrated remarkable sensitivity with a value of 450\u0026deg;/RIU, a bandwidth of 3.5\u0026deg; FWHM, and figure of merit (FOM) of 128.57/RIU within the refractive index range of 1.33\u0026ndash;1.34. Notably, its sensitivity surpasses that of other SPR biosensors proposed for SARS-CoV-2 detection [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Furthermore, we showcased the application of this biosensor for early-stage detection. This sensor detects infected and non-infected samples by showing reasonable shift in resonance angle. Its high sensitivity makes it suitable for various other biosensing applications.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding Information:\u003c/h2\u003e \u003cp\u003eThe authors did not receive any funding from any organization for this work.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthor Contribution The idea was conceived, data collected, analyzed, and interpreted, and the initial draft was written by Shiven Bhatt and Naina Bose. Kamrun Nahar Shushama, Reefat Inum, and K. B. M. Rakib Hasan: responsible for code writing, data gathering, analysis, interpretation, manuscript writing, editing, and final draft creation, serving as mentors for the research activity's planning and execution. All authors contributed equally to this paper.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e \u003cp\u003eThe dataset generated during analysis is available in this article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eY\u0026uuml;ce M, Filiztekin E, \u0026Ouml;zkaya KG (2021) COVID-19 diagnosis\u0026mdash;A review of current methods. Biosens Bioelectron 172:112752\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKevadiya BD et al (2021) Diagnostics for SARS-CoV-2 infections. Nat Mater 20(5):593\u0026ndash;605\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMattioli IA et al (2020) On the challenges for the diagnosis of SARS-CoV-2 based on a review of current methodologies. ACS Sens 5(12):3655\u0026ndash;3677\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePandey PS et al (2022) \u003cem\u003eSPR based biosensing chip for COVID-19 diagnosis-A review\u003c/em\u003e. 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IEEE\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRahman MS et al (2020) Enhanced performance of SnSe-Graphene hybrid photonic surface plasmon refractive sensor for biosensing applications. Photonics Nanostructures-Fundamentals Appl 39:100779\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRahman MS et al (2017) Sensitivity analysis of graphene coated surface plasmon resonance biosensors for biosensing applications. Sens bio-sensing Res 16:41\u0026ndash;45\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHasan KR, Islam MA, Alam MS (2020) \u003cem\u003eDesign of a Broadband Hybrid Plasmonic Waveguide for High Bulk Index Sensitivity\u003c/em\u003e. in \u003cem\u003e11th International Conference on Electrical and Computer Engineering (ICECE)\u003c/em\u003e. 2020. IEEE\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"plasmonics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plas","sideBox":"Learn more about [Plasmonics](https://www.springer.com/journal/11468)","snPcode":"11468","submissionUrl":"https://submission.nature.com/new-submission/11468/3","title":"Plasmonics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Surface plasmon resonance, SARS-CoV-2, 2D materials, Sensitivity, Detection","lastPublishedDoi":"10.21203/rs.3.rs-4005654/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4005654/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eThis paper presents a novel surface plasmon resonance (SPR) biosensor based on Kretchmann configuration for detection of SARS-CoV-2. It combines Barium titanate (BaTiO\u003c/span\u003e \u003csub\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e3\u003c/span\u003e \u003c/sub\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e) dielectric material on top of metal, also 2D material Tungsten Disulfide (WS\u003c/span\u003e \u003csub\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e2\u003c/span\u003e \u003c/sub\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e) used alongside the traditional prism/metal/sensing layer setup. Sensitivity is enhanced by using BaTiO\u003c/span\u003e \u003csub\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e3\u003c/span\u003e \u003c/sub\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eon silver (Ag) and WS\u003c/span\u003e\u003csub\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e2\u003c/span\u003e\u003c/sub\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eon BaTiO\u003c/span\u003e\u003csub\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e3\u003c/span\u003e\u003c/sub\u003e. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eThe integration of these emerging materials into conventional sensor structures has been thoroughly examined to optimize sensor performance. An analysis of key performance parameters has been conducted using the transfer matrix method (TMM) and Fresnel equations, including sensitivity, full width at half-maxima (FWHM), and figure of merit (FOM). The proposed sensor demonstrates an exceptional angular sensitivity of 450\u0026deg;/RIU, with a 3.5\u0026deg; FWHM and a 128.57/RIU FoM. Optimal sensitivity is achieved with a configuration comprising 1 layer of WS\u003c/span\u003e\u003csub\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e2\u003c/span\u003e\u003c/sub\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ein addition to the metal layer. Our proposed SPR sensor shows more sensitivity for detecting SARS-CoV-2 than other proposed SPR sensors in literature. We also analyzed the electric field of the proposed biosensor with Finite Element Method based software and showed its future research aspect. SARS-CoV-2 has been successfully detected in patient samples due to the sensor's increased sensitivity at early stage of this disease.\u003c/span\u003e\u003c/p\u003e","manuscriptTitle":"Surface Plasmon Resonance Biosensor with High Sensitivity for Detecting SARS-CoV-2","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-06 19:19:27","doi":"10.21203/rs.3.rs-4005654/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-03-14T10:35:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-03-05T08:13:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"40d47ae5-b403-432c-82dd-ead002262d3c","date":"2024-03-04T13:54:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"2274867d-222b-4c4b-9a5a-a2d75bee4e3c","date":"2024-03-04T13:51:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-04T13:48:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-04T00:09:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-04T00:09:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"Plasmonics","date":"2024-03-02T06:11:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"plasmonics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plas","sideBox":"Learn more about [Plasmonics](https://www.springer.com/journal/11468)","snPcode":"11468","submissionUrl":"https://submission.nature.com/new-submission/11468/3","title":"Plasmonics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"4e17f6a9-0881-465d-b43d-ea65a66c3488","owner":[],"postedDate":"March 6th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-05-01T23:00:46+00:00","versionOfRecord":{"articleIdentity":"rs-4005654","link":"https://doi.org/10.1007/s11468-024-02304-6","journal":{"identity":"plasmonics","isVorOnly":false,"title":"Plasmonics"},"publishedOn":"2024-04-19 23:00:46","publishedOnDateReadable":"April 19th, 2024"},"versionCreatedAt":"2024-03-06 19:19:27","video":"","vorDoi":"10.1007/s11468-024-02304-6","vorDoiUrl":"https://doi.org/10.1007/s11468-024-02304-6","workflowStages":[]},"version":"v1","identity":"rs-4005654","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4005654","identity":"rs-4005654","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}