Simulation and Analysis of the SnSe/Au Nanolayer Using SPR Technique for Biosensing Applications

Surface plasmons (SPs) are formed when an electric or magnetic field of p-polarized light excites electrons on a conducting material's surface, causing electronic oscillations to the surface of the material or metal. Stated differently, they originate at the boundaries of the dielectric materials and metals (the interface). SPs are thought of as electromagnetic waves because of the way these interactions happen at the interface between dielectric and metal [1]. The excited electrons have a high density and are known as plasmons because they display harmonic oscillations near the contact. The metal may produce potent SPs when it is positioned as a layer on the prism and comes into contact with the dielectric [2]. The well-known applications of SPR biosensors include sensing gases, studying surface interactions, and biomaterial detection [3].

Recently, an SPR-based optical biosensor technique has been developed with free-label and real-time detection capability [4]. In most of the SPR investigations, both silver and gold are the most commonly used metals due to their strong sensitivity for SPR biosensors in the visible and near-infrared bands [3]. Conventional SPR sensor systems make use of the gold or silver deposited on a massive prism as well as an optical process called incident light stimulation at the metal-dielectric interface [5]. Then, the light reflected from the thin metal prism is measured using SPR sensors for both incidence angle and light intensity [5]. The rapid expansion of SPR-based biosensors across a broad range of applications has led to a number of researchers conducting a variety of investigations to date. These methods are being used more often in military and defense [6], environmental monitoring [7], agriculture [8], food and water quality control [9], medical diagnostics [10], and ultra-sensitive and quick biological material detection fields [11, 12]. Our work contributes to the analysis and knowledge of how the tin selenide layer affects the conceptual model and structural design of the proposed SPR sensor. The sensor performance is determined using the reflectivity curves of the SnSe/Au nanolayers.

Since the invention of the first SPR sensor by Nylander et al. [13] in 1982 for biosensing and gas sensing, many researchers have devised a variety of methods to increase the sensitivity of SPR. Each strategy has its own unique design among a wide range of elements in SPR design, such as Bragg grating-based SPR, supercontinuum exciting SPR, optical design, magneto-optic SPR, plasmonic materials, Fabry-Perot-based SPR, and nanomaterials. In addition, the sensitivity of SPR considerably changes depending on the kind of dielectric, such as gas or liquid, as well as the type of structure, such as a diffraction grating, a prism, or an optical fiber.

Tin selenide is a P-type semiconductor material that is both chemically resistant and non-toxic. It features a gap of 0.9 eV for indirect transitions and a gap of 1.3 eV for direct transitions. It is a distinctive, multilayer-structured plasmonic material with excellent electrical and optical characteristics that attracts much interest as a two-dimensional substrate. Films manufactured from SnSe have a high transmittance (56-76%) and a high refractive index (2.05-2.55), so they are suitable for applications in photovoltaics, optical fibers, solar cells, etc. Therefore, many researchers have implemented different approaches with SnSe in different experiments. In 2019, Dai et al. [14] improved the sensitivity of the sensor while maintaining its chemical stability by adding three different types of 2-D SnSe to the structure between the metallic silver (Ag) thin and the sensing medium. Their goal was achieved, as they found that adding SnSe allotropes to the silver films enhanced the sensitivity. In another experiment in 2022, Dwivedi et al. [15] presented a configuration for a surface plasmon resonance (SPR) sensor to detect anemia, abnormalities in urine, and DNA hybridization. The configuration consisted of zinc oxide (ZnO) and tin di-selenide (SnSe₂) as the stacked structure on the prism (SF-10).

In an investigation by Varasteanu [16], 2019, he deposited an allotrope of SnSe (α, δ, and ε) monolayer on a gold layer for improving the interaction of SPR sensors and increasing their reflectivity and phase sensitivity. They did not address the practical constraints, scalability of the manufacturing process, or potential roadblocks in converting the simulation-based SnSe/gold-based SPR sensor into a feasible one in their proposal. In order to guarantee the robustness and dependability of the designed instrument when applied to practical scenarios, it is important to keep in mind that the success of these kinds of sensors frequently depends on structural parameters like the wavelength used, the type of prism, the refractive index of the sensing medium, the angles of incidence of the light source, and others. In 2023, Mohamad et al. [17], simulated a surface plasmon resonance (SPR) sensor for a gas sensor. They deposited a silver/cadmium sulfide (Ag/CdS) based on the Kretschmann configuration. They analyzed their results based on the reflectivity curves and used (detection accuracy, quality factor, sensitivity, and FWHM) as parameters to determine the sensor's performance. The authors investigated the effects of various design parameters, such as the wavelength of the light source and the thickness of the CdS and Ag layers, on the sensor's performance in order to make well-informed design decisions. In contrast, the experiment in this study employed the Otto configuration to build and test a biosensor system using a conductive material (Au) with a thickness of 50 nm placed over an insulating material (SnSe) with a variable thickness of 0-80 nm.

Recently, a paper [18] was published that deals with the simulation of a SPR sensor for a gas sensing. They used the Kretschmann setup to deposit tantalum pentoxide on silver (Ag/Ta₂O₅). The Ta₂O₅ layer's thickness varied from 0 to 70 nm, whereas the silver layer's thickness was constant at 50 nm. Their study is similar to our research with respect to simulation boundary conditions, sensor performance metrics, and prism glass type. Nevertheless, they left out of their proposal any discussion of the manufacturing process's scalability, practical constraints, or potential obstacles to turning the Ag/Ta₂O₅-based SPR sensor model into a workable sensor.

The starting point of our study is to provide new theoretical analyses that have not yet been applied in practice but represent a fundamental step that can be used in future practical applications to improve the accuracy and sensitivity of biosensors through studying the simulation and configuration of a nanolayer of SnSe/Au using SPR technology for biosensing purposes.

This work aims to investigate the SnSe/Au sensor's sensitivity through the transfer matrix method (TMM) [19]. The sensitivity is determined by calculating the reflectance of multilayer structures. Since many performance improvement studies for this type of sensor have relied on computational methodologies like genetic algorithms [19-21] or particle swarm optimization [22-24], they are usually complex and time-consuming to configure. As a result, we used the TMM framework methodology to obtain simulation results for varying the SnSe layer thickness.

To verify the functionality of an SPR sensor, an accurate measurement of the intensity of the reflected light at the output terminal is required. In this work, a transfer matrix has been used to develop Matlab simulation software for a system that consists of two deposited layers on a hemi-cylindrical prism: a fixed layer of gold with a thickness of 50 nm and a variable layer of tin selenide with a thickness of 10-80 nm. The following boundary conditions and Fresnel equations for the reflection of electromagnetic waves in the visible range and near infrared were selected by the simulation program [14, 25]:

$\left[\begin{array}{l}E_1 \\ B_1\end{array}\right]=\Omega\left[\begin{array}{l}E_{N-1} \\ B_{N-1}\end{array}\right]$    (1)

where, B₁ and E₁ represent the tangential magnetic and electrical field components in the first layer of the boundary. The tangential elements of the electric and magnetic fields at the last layer are designated E_N-1 and B_N-1. The characteristics matrix of the composite design, called Ω, contains P_ij elements and is obtained by [14, 25]:

$\Omega=\prod_{K=2}^{N-1} P_k\left[\begin{array}{ll}P_{11} & P_{12} \\ P_{21} & P_{22}\end{array}\right]$    (2)

with

$P_k=\left[\begin{array}{cc}cos \beta_K & \frac{-i}{q_k} \sin \beta_K \\ -i q_K \sin \beta_K & \cos \beta_K\end{array}\right]$    (3)

where, β_K is phase thickness, k is a random number, and is represented by [25]:

$\beta_K=\frac{2 \pi}{\lambda}\left(d_K\right) \sqrt{\left(\epsilon_K-n_{\circ}^2 \sin ^2 \theta_{\circ}\right)}$    (4)

λ is wavelength of the incident light; ϵ_K represent the dielectric constant; θ_o is the angle of incidence; no indicates the refractive index of the glass prism; q_K stands for the refractive index of the equivalent layers and is denoted by:

$q_K=\sqrt{\left(\epsilon_K-n_{\circ}^2 \sin ^2 \theta_{\circ}\right)} / \epsilon_K$    (5)

The reflection coefficient (r_p) for incident polarized light is written as [25]:

$r_p=\frac{\left(P_{11}+P_{12} q_N\right) q_1-\left(P_{21}+P_{22} q_N\right)}{\left(P_{11}+P_{12} q_N\right) q_1+\left(P_{21}+P_{22} q_N\right)}$    (6)

The following formula [26] is used to ultimately determine the reflectivity of the multi-layer structure:

$R_P=\left|r_p\right|^2$    (7)

The Otto configuration of the SnSe/Au metal has contributed to simulating the refractive index biosensor characteristic in the suggested innovative structure. The proposed refractive index sensor showed high sensitivity, making it suitable for a variety of applications, including the detection of biological fluids dissolving in water, hard water detection, and biochemistry combined with water molecules.

In order to accurately determine the sensitivity capability of the SPR sensor, the reflectance curve was examined as a function of the incident angle. Different thicknesses of the SnSe layers (0, 10,..., 80 nm) were analyzed, and then the simulation results were used to determine the maximal sensitivity of the designed SPR model. In the designed sensor, it was assumed that the RI of the sensing medium changes from 1.33 to 1.34 and that the thickness of Au is 50 nm.

This paper deals with simulation to find the optimal regions where plasmonic resonance occurs, which has not been achieved in earlier research using this model. Our study attempts to give an appropriate design and numerical values for the parameters that might help to improve the practical performance of biological sensors, whereas prior studies concentrated on various materials and approaches. This analysis will provide clearer insights into the benefits and possible practical applications, highlighting the importance and innovation of the present work.

2a.jpg

2b.jpg

2c.jpg

2d.jpg

2e.jpg

Figure 2. The reflectance curve as a function of light incidence angle for the SnSe nanolayer on Au with varying thicknesses (0-80) nm and different RI: left (n=1.33), right (n=1.34)

We examined the performance parameters of SPR in the ultraviolet, visible, and near-infrared ranges at an operating wavelength of 300-1000 nm. It is clear from the results in Figure 2, that the SPR characteristic completely disappears at small wavelengths, particularly at 300, 400, and 500 nm. Since the sensor layer absorbs the SPR wave energy, the reflectance at the Au/water interface is low across the whole angle range. The SPR wave appears at 600, 700, 900, 700, and 1000 nm wavelengths, and the resonance angle (ϴ_spr) is 60º, 54.5º, 51.5º, and 50.5º, respectively. Tiny variations in the sensing layer's refractive index will result in a small shift in the SPR angle, which was achieved at 61.5º, 55.5º, 52.5º, and 51.5º for the same wavelengths.

The reflectivity curves show that there is no angular interrogation at the wavelengths of 300, 400, and 500 nm. The response appears at wavelengths of 600 and 700 nm and then disappears at 800 nm. Surface plasmon wave production completely disappears for all SnSe layer thicknesses, as water shows anomalous scattering [31]. The SPR angles decrease with increasing wavelengths, while they are constant at all thicknesses of the SnSe layer. The greater reflection intensity at 1000 nm when d=0 is 0.96 for (Δn=0 and Δn=0.01); this value reduces slightly at d=80 nm to reach 0.95 in the same conditions.

When surface plasmons are excited at longer wavelengths (and lower incidence angles), the reflection dips affected by this excitation are narrower than when surface plasmons are excited at shorter wavelengths (and higher incidence angles). Figure 2 shows the lowest FWHM value at 600 nm was found at 9º with a thickness of 10, 20, 30, 40 nm for an analyte RI of 1.33. On the other hand, the FWHM value changed to 9.3º at (10, 20, 30)nm thickness as a result of a change in the analyte RI from 1.33 to 1.34, which is indicated in bold in Table 1. The FWHM value reaches 2.1º and 0.8º at wavelengths of 700 nm and 900 nm, respectively, which were indicated in bold in Tables 2 and 3, as the wavelength and layer thickness increase. Subsequently, it takes a minimum value of 0.7º at the 1000 nm wavelength (see Table 4). Due to the SnSe material's small bandgap and higher absorption efficiency, the SPR dip gets its maximum value of 0.95º at 900 nm.

A greater sensitivity of the biosensor can be achieved at the lowest FWHM value and the longest SPR dip. Actually, as the wavelengths changed, the SPR dip changed, and the FWHM value decreased, resulting in an increase in the detection accuracy. The biosensor's sensitivity values of 140deg/RIU and 110deg/RIU at 600 and 700 nm, respectively, were disregarded due to the low detection accuracy values as displayed in Tables 1 and 2 for all SnSe thicknesses. Consequently, the maximum sensitivity of an SPR instrument does not necessarily translate to the best sensitivity for detecting molecule binding, also known as surface sensitivity. As the wavelength increases, the SPR-created evanescent field's penetration length into the fluid medium grows. Although longer wavelengths can penetrate farther than the sensor surface, surface sensitivity is significantly lost in the process. The maximum sensitivity of the suggested biosensor is 100deg/RIU at wavelength 900 nm. For thicknesses of 0, 10, 70, and 80 nm, the sensitivity is 100deg/RIU at wavelength 1000 nm. As seen in Table 4, it obtained the greatest detection accuracy of 1.42.

Table 1. The performance parameters of the biosensor at 600 nm wavelength

Table 2. The performance parameters of the biosensor at 700 nm wavelength

Table 3. The performance parameters of the biosensor at 900 nm wavelength

Table 4. The performance parameters of the biosensor at 1000 nm wavelength

From Tables 1-4, it is clear that there is a change in the calculated values of the parameters FWHM, DA, and QF. Where it is attributed that the parameters of the designed model have an effect on those parameters when the thickness of the SnSe layer is changed. In addition to the fact that reflectivity, transmittance, and absorbance vary with angle of incidence, this also depends on the change in refractive index values of the materials utilized as a function of wavelength; the absorption value is necessarily impacted by variations in thickness, and these changes have an impact on the computed values of these parameters. The depth and length of the prism can also have an effect on sensitivity.

The authors would like to express their gratitude to Mustansiriyah University (www.uomustansiriyah.edu.iq) in Baghdad, Iraq, for its assistance with this work.