Detection of hemoglobin in blood and urine glucose level samples using a graphene-coated SPR based biosensor

Shahriar Mostufa; Alok Kumar Paul; Kisalaya Chakrabarti

doi:10.1364/OSAC.433633

1. Introduction

The expeditious growth of genetics and biochemistry has led to expanding different medical and biomedical instruments to detect various diseases with tremendous accuracy. At present, optical-based sensing dominates biosensors due to the multiple characteristics of absorption, transmittance, and reflectance of light waves for the change in the surrounding medium [1]. Moreover, these optical sensors are not only super-sensitive to medium refractive index change but also fast and accurate due to the enormous speed of light waves. In recent years, several optical-based sensors have been proposed, for instance, whispering gallery mode (WGM), photonic crystal fiber, and surface plasmon resonance (SPR) [2–6]. Among other optical biosensors, the SPR based sensors are newly emerging and at present dominating the field of optical sensing due to significant enhancement in nanotechnology fabrications.

SPR phenomenon is a recent and highly sensitive technique for detecting refractive index variation of the biological or chemical analyte, which comes directly in contact with the sensor metal film [7,8]. Although several SPR based biosensors are already available to this date, the researchers are interested in upgrading the sensor sensitivities and introducing these sensors to a wide range of spectra for sensing purposes and applications. The SPR based sensor works on the principle of free electron oscillations called surface plasmon (SP). When a p-polarized light incident on the prism ($\textrm{B}{\textrm{K}_7}$) it excites the SP mode, and by using the angular interrogation technique, the resonance or SPR angle (${\mathrm{\theta }_{\textrm{spr}}}$) has been calculated by observing the output reflectance (%) line. Due to the multilayer interfaces, the light wave's output reflectance intensity (%) decays from the incident light wave intensity. But in the SPR or resonance condition, the reflectance intensity (%) becomes minimum (${\textrm{R}_{\textrm{min}}}$) due to maximum excitations of surface plasmons [9–11]. To monitor the total attenuated reflection, the reflection detector (CCD or CMOS) [12], works as a monitoring device, and the shift of SPR angle ($\mathrm{\Delta }{\mathrm{\theta }_{\textrm{spr}}}$) has been observed due to refractive index variation of samples or sensing medium. In SP mode, free electron oscillations developed due to the interaction between the metal and dielectric medium for having opposite dielectric constants of real value [13]. Moreover, the light-matter interaction due to SP causes a strongly localized exponentially deteriorating evanescent wave across the metal interface. This decaying becomes highly influenced due to the refractive index variation in the sensing medium and in the SPR condition for a particular SPR angle $({\mathrm{\theta }_{\textrm{spr}}}$) the deteriorating evanescent wave across the metal interface becomes maximum [9,14]. For adopting these mentioned characteristic effects of SP, the sensor has to operate on resonance conditions such as resonance angle or resonance wavelength of an incident light wave [8,13]. In this paper, we have focused only on the angular interrogation technique of an incident light wave. In the angular interrogation method, we get minimum reflectance for a particular incident angle of the light wave, also known as the resonance or SPR angle. For this resonance incident angle, the metal film has the excitation of the maximum SP, which also influences the propagation of surface plasmon waves (SPW) [14].

The traditional prism coupled Kretschmann configuration SPR sensor does not have better-sensing capability compared to the present hybrid, multiple layer SPR Kretschmann configuration sensor. It is because the conventional Kretschmann configuration used only the metal layer, which doesn't have the capabilities to absorb light energy for stronger SP excitations. But recently emerged transition metal dichalcogenide (TMDC) and 2-D materials had enhanced the light-matter interactions as well as the energy absorption because the TMDC materials have a larger real part of refractive index [9,15], and the 2D material graphene has the best interlayer interaction with versatile biocompatibilities [16,17]. Again, due to the recent enhancement in nanostructure fabrication technology, the performance and sensitivities of these hybrid models of the prism coupled Kretschmann configuration has become much more accessible [14]. Some similar work related to SPR sensitivity enhancement with the hybrid multilayered model is demonstrated in [9,13] [18–21]. In this SPR based sensor, we have used the Gold (Au) material as a plasmonic material. However, multiple plasmonic materials, for example, silver (Ag), copper (Cu), and aluminum (Al), can also be used as plasmonic material [22]. However, each of these materials has some positive and negative effects on the overall sensitivities of the SPR based sensor. For example, gold as a plasmonic material shows tremendous resonance angle shift due to refractive index variation, and it is also a chemically stable material [23,24].

Transition metal dichalcogenide (TMDC) material layer $\textrm{PtS}{\textrm{e}_2}$ has recently attracted powerfully due to its unique properties and potential applications in the next generation of electronic, optoelectronic, energy devices, and 2D nanomaterials over the past decade [25,18]. The monolayer consists of Pt atoms sandwiched between Se atoms, and the top view shows a hexagonal structure with Pt and Se atoms located at alternating corners and an additional Se atom in the center of each hexagon [26]. This newly emerging Transition metal dichalcogenide (TMDC) layer with a traditional Kretschmann configuration SPR sensor has enhanced the sensitivities and performance of the SPR based sensor [4]. As the bandgap of $\textrm{PtS}{\textrm{e}_2}\; $is highly tunable because of its intrinsic quantum confinement effect and strong interlayer interaction, so the TMDC material $\textrm{PtS}{\textrm{e}_2}$shows excellent optical and electrical properties. Moreover, $\textrm{PtS}{\textrm{e}_2}$ shows less toxicity and chemical stability investigated in $\textrm{PtS}{\textrm{e}_2}$sensing applications [26]. Furthermore, $\textrm{PtS}{\textrm{e}_2}$ can easily modulate different types of stress [27]. The TMDC material $\textrm{PtS}{\textrm{e}_2}$ monolayer also possesses a significant thermoelectric character with semiconductor properties [18,28]. Again, with graphene, this TMDC material $\textrm{PtS}{\textrm{e}_2}$ can be used as a suitable substrate as it forms van der Waals (vdW) heterojunction [22]. Using heterostructure of $\textrm{PtS}{\textrm{e}_2}\; $with a thickness of 2 nm, 3.3 nm, and 4.4 nm on the Kretschmann configuration SPR sensor sensitivity enhancement for multiple plasmonic materials with the graphene layer interrogation demonstrated in [13]. Graphene was introduced in 2004, and even today, it is one of the most preferred 2-D materials [9]. For its hexagonally organized carbon atoms, graphene shows the best optoelectronic and optomechanical properties of low loss, high confinement, turnability, and vast surface volume ratio, which confirms well contract with analyte molecules. In addition, when the graphene layer is placed on the metallic films or with the metallic nanoparticle, a strong coupling is created, resulting in substantial enhancement of the electric field at the nano interface [24], [29,30]. $\textrm{B}{\textrm{K}_7}$ prisms with 50 nm Au layer as plasmonic material, 2 nm $\textrm{PtS}{\textrm{e}_2}\; $as TMDC material, and the graphene five layer of each layer 0.34 nm show the best performance for this hybrid SPR sensor structure [13]. Some recently emerged 2-D materials other than graphene, such as $\textrm{Mo}{\textrm{S}_2}$, and $\textrm{W}{\textrm{S}_2}\; \textrm{can}\; $also be used to enhance the sensor performance [13].

In this paper, we have shown the detection of blood hemoglobin level change and the glucose concentration level change in urine samples concerning refractive index variation using $\textrm{B}{\textrm{K}_7}\; $/Au /$\; \textrm{PtS}{\textrm{e}_2}\; $/graphene coated SPR sensor. The Finite element method (FEM) based on ‘COMSOL Multiphysics’ software has been used to design and simulate the proposed sensor. Using the simulation data extracted from COMSOL Multiphysics software, we have plotted the graphs using MATLAB software environment. The novelty of this work is that we have shown the detection of hemoglobin change with 0.001 refractive index increment and angular sensitivity near 200 deg/RIU, which indicates a 6.1025 g/l change in the blood hemoglobin level. In addition, we have also measured the glucose concentration level in the urine samples to detect the presence of diabetes in patients using this SPR based biosensor.

1.1 Blood hemoglobin

Blood is one of the most vital body fluids in the body, and hemoglobin (HB) is found on the red blood cell (RBC) of the blood. It is responsible for supplying oxygen in the blood, so the change in hemoglobin levels in blood causes several diseases. Some blood diseases related to blood hemoglobin change are explained in [31–33]. Normally blood hemoglobin level is measured in (g/l), and the average male person has hemoglobin level (140 to 180 g/l), and the average female has (120 to 160 g/l) [34]. The data from [34] explains that an average person's blood refractive index varies from 1.32919 to 1.34995, and every 0.001 refractive index changes in the blood, the hemoglobin level increases 6.1025 g/l. A linear relationship exists between the hemoglobin change with blood refractive index variation [34] determined from Eq.(1).

(1)$${\textrm{H}_\textrm{r}}\textrm{ = }{\textrm{H}_0}\textrm{ + B}\mathrm{\Delta}\textrm{n}$$

where ${\textrm{H}_\textrm{r}}\; $is the resultant HB level, ${\textrm{H}_0}\; $is the present HB level, B is the constant value of 5766.5, and the refractive index change is $\mathrm{\Delta}\textrm{n}$. Figure 1 describes the hemoglobin level change for each 0.001 refractive index increment.

Fig. 1. Hemoglobin concentration increment with respect to refractive index change 0.001

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For measuring the HB from RBC, prepossessing of blood samples with the addition of heparin has been explained in [35]. Preprocessing is required because RBC contains oxygen, so directly detecting HB in blood samples without processing might give a measurement error. Most of the methods used for detecting HB levels in the past were comparatively low sensitive. Moreover, a recently proposed whispering gallery mode (WGM) based HB detection shown in [34] is still less sensitive compared to this graphene-coated SPR based sensor because the maximum blood refractive index change shown in WGM based work is only 0.0044, but here we have shown for each 0.001 blood refractive index change. So, using this sensor for HB detection might help to detect HB related diseases in the early stages.

1.2 Urine samples

Diabetes is a chronic metabolic disease characterized by blood glucose (blood sugar) levels, which leads to severe damage to the heart, eyes, kidneys, and nervous system [36]. According to the World Health Organization (WHO), about 422 million people worldwide have diabetes, and 1.6 million deaths are attributed directly to diabetes each year [37]. Several body fluids and urine samples changed with glucose concentration levels changing. Due to the glucose concentration change, the refractive index varies in the urine sample of the affected person from the average healthy person. In normal conditions, the human body does not have glucose in the range of 0 to 15 mg/dl [38]. Due to glycosuria, glucose in urine increases, and the average range of glucose is between 165 and 180 mg per deciliter (mg/dl). Again, Hypoglycemia is a low blood glucose concentration less than 40 mg/dl, and Hyperglycemia indicates a high glucose concentration level around 279 ∼ 360 mg/dl. Variation of glucose concentration level with refractive index data obtained from [38], and it was done previously using photonic crystal fiber (PCF) nanocavity. Moreover, compared to SPR based sensors, PCF is a much more complex and costly structure.

2. Design methodology

2.1 Structural modeling

Figure 2 shows the multiple layered SPR based biosensor for detecting hemoglobin in blood and glucose concentration levels in urine samples. We have applied a monochromatic light source considered as He-Ne having a wavelength ($\mathrm{\lambda }$) of 632.8 nm on the $\textrm{B}{\textrm{K}_7}\; $prism for the best performance [12] of the following sensor. The $\textrm{B}{\textrm{K}_7}$ prism whose refractive index calculated is 1.5151 for that particular incident wavelength ($\mathrm{\lambda }$) light which is calculated [7] from Eq. (2) :

(2)$${n_{Bk7}} = \sqrt {1 + \frac{{1.03961212{\lambda ^2}}}{{{\lambda ^2} - 0.00600069867}} + \frac{{1.01046945{\lambda ^2}}}{{{\lambda ^2} - 103.560653}} + \frac{{0.231792344{\lambda ^2}}}{{{\lambda ^2} - 0.0200179144}}}$$

On the next layer, we have used Gold (Au) as a plasmonic material having a complex refractive index$({\textrm{n}_{\textrm{Au}}})\; $of 0.13774 + 3.6183i calculated using Drude–Lorentz model [13] or dispersion relations Eq. (3) for the incident wavelength ($\mathrm{\lambda }$), here plasma wavelength (${\mathrm{\lambda }_\textrm{p}})\; \textrm{is}$ $1.\textrm{6826}\; \times {10^{ - 7}}$m, which is corresponding to the bulk plasma frequency and collision wavelength (${\mathrm{\lambda }_\textrm{c}}$) is $\textrm{8}\textrm{.9342}\; \times \; \textrm{10}{^{ - 6}}\; $m related to losses [22].

(3)$${n_{Au}} = \sqrt {\left( {1 - \frac{{{\lambda^2} \times {\lambda_c}}}{{\lambda_p^2({\lambda_c} + \lambda \times i)}}} \right)}$$

$\textrm{Here,}\; $as TMDC material, we have used$\; \textrm{PtS}{\textrm{e}_2}$ and the refractive index of $\textrm{PtS}{\textrm{e}_2}$ depends on the thickness. Here we have taken 2 nm thickness and complex refractive index (${\textrm{n}_{\textrm{PtS}{\textrm{e}_2}}})$ is 2.9029 + 0.8905i [18]. Again, we have taken the complex refractive index of graphene calculated $({{\textrm{n}_\textrm{G}}} )$ is 3 + 1.1487i using Eq. (4) for the incident wavelength ($\mathrm{\lambda }$).

(4)$$3 + \frac{{ic\lambda }}{3}$$

Here, c is 5.446 $\mathrm{\mu }{\textrm{m}^{ - 1}}$ [9], [13,39]. The thickness of each graphene sheet layer is $0.\textrm{34}\ast l$ nm, here the layer number is denoted by l. we have used a five-layered (l = 5) graphene sheet which is 1.7 nm because with the plasmonic material gold (Au) with thickness 50 nm and TMDC material $\textrm{PtS}{\textrm{e}_2}$ with thickness 2 nm layer at 632.8 nm incident wavelength light sensor shows the best angular sensitivity with graphene five layered thickness [12,13].

Fig. 2. Schematic diagram of multiple layered ($\textrm{B}{\textrm{K}_7}$ / Au /$\; \textrm{PtS}{\textrm{e}_2}\; $/ graphene) SPR sensor for blood hemoglobin and urine glucose level detection

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In the sensing analytic region, we have to place the biological samples. This paper has shown the detection of two types (blood hemoglobin and urine glucose concentration level) of biological samples. Here ${\textrm{n}_{\textrm{analytic}}} = {\textrm{n}_0} + \partial \textrm{n}$, where ${\textrm{n}_{\textrm{analytic}}}$ is the total refractive index, ${\textrm{n}_0}\; $is the reference refractive index, and $\partial \textrm{n}\; \textrm{is}\; \textrm{the}\; $variation or change in the refractive index from the reference refractive index. Again, we have taken the sensing analyte medium width 1.3463 $\mathrm{\mu }\textrm{m}$. The angular interrogation of incident light has been used here with the range from 60 degrees to 89 degrees with a 0.1 degree increment. The frequency-domain solver has been used where the frequency taken is $3 \times \textrm{1}{\textrm{0}^8}/\; \mathrm{\lambda }\; $ Hz. We have measured the sensor sensitivity by observing the shifting of the dip in the reflectance intensity (%) line in the detector due to the sample's refractive index variation.

In this paper, to detect the blood hemoglobin and urine glucose concentration level biological samples with the refractive index variation, we have used the finite element method (FEM) based on “COMSOL Multiphysics” software for performance analysis [40,41]. Here, we have simulated the proposed sensor with “COMSOL Multiphysics” v 5.4 with extremely fine sized physics controlled mapped mesh whose maximum element size is 0.028 $\mathrm{\mu }\textrm{m,}$ and the minimum element size is 5.6E-5 $\mathrm{\mu }\textrm{m}$. From Fig. 3(a), we have shown that the light incident on $\textrm{B}{\textrm{K}_7}$ prism, and using parametric sweep, we have performed the angular interrogation (range from 60 degrees to 89 degrees with a 0.1-degree increment), and we have measured the reflectance intensity (%) for each incident angle. Figure 3(b) and Fig. 3(c) are surface magnetic field distributions in 3D for z component (A/m) propagation at SPR angle (75.1 deg) and at none SPR angle (85.1 deg), respectively. Comparing Fig. 3(b) and Fig. 3(c), we have found that SPR formed and propagated at resonance condition along with the metal and dielectric interface, and the propagation of surface plasmon is maximum at this condition. Though our model is a complete numerical simulation based analysis, practical implementation is also possible using multiple layer deposition techniques. Using physical vapor deposition (PVD) or sputtering method, the Gold (Au) layer can be deposited [42], and using the chemical vapor deposition (CVD), Graphene layers can be deposited [43–45]. Firstly, the substrate $\textrm{B}{\textrm{K}_7}$ has to be washed using piranha solution $({{\textrm{H}_2}{\textrm{O}_2}\textrm{:3}{\textrm{H}_2}\textrm{S}{\textrm{O}_4}} )$ to eliminate pollutants. Then the gold (Au) layer is deposited on the top of $\textrm{B}{\textrm{K}_7}$ using physical vapor deposition (PVD) or sputtering techniques. The thickness of the gold layer depends on the particle sputtering deposition time. The next step is heating a thin layer of platinum (Pt) in selenium (Se) steam at $\textrm{40}{\textrm{0}^\textrm{o}}\textrm{C}$ to form the layer $\textrm{PtS}{\textrm{e}_2}$. Again, finally, using the chemical vapor deposition (CVD), the high quality graphene layer is grown onto $\textrm{PtS}{\textrm{e}_2}$ at $\textrm{100}{\textrm{0}^\textrm{o}}\textrm{C}\; $and under the chamber pressure of 3.6 Torr [12].

Fig. 3. (a) General configuration of proposed ($\textrm{B}{\textrm{K}_7}\; $/ Au / $\; \textrm{PtS}{\textrm{e}_2}\; $/ graphene) SPR biosensors using COMSOL Multiphysics (Software view) (b) surface magnetic field z component (A/m) Propagation of with 3D representation at SPR angle (75.1 deg) (c) surface magnetic field z component(A/m) Propagation of with 3D representation at no SPR angle (85.1 deg)

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2.2 Mathematical and theoretical modeling

The reflection intensity measurement at the output is a prerequisite for the sensing purpose of this SPR sensor, and the reflection intensity of p-polarized light can be denoted as [46]:

(5)$${R_p} = |r_p^2|$$

(6)$${r_p} = \frac{{({{F_{11}} + {F_{12}}{n_N}} ){n_1} - ({{F_{21}} + {F_{22}}{n_N}} )}}{{({{F_{11}} + {F_{12}}{n_N}} ){n_1} + ({{F_{21}} + {F_{22}}{n_N}} )}}$$

As here we have used multilayer coating so, ${\textrm{F}_{\textrm{ij}}}\; $represents the transfer matrix function is given as follows [46,47]:

(7)$${F_{ij}} = {\left[ {\Pi _{k = 2}^{N - 1}\left( {\begin{array}{cc} {\cos {\beta_k}}&{\frac{{ - i\sin {\beta_k}}}{{{n_k}}}}\\ { - i{n_k}\sin {\beta_k}}&{\cos {\beta_k}} \end{array}} \right)} \right]_{ij}} = \left[ {\begin{array}{cc} {{F_{11}}}&{{F_{12}}}\\ {{F_{21}}}&{{F_{22}}} \end{array}} \right]$$

The explanation of transverse refractive index for respective ${\textrm{k}^{\textrm{th}}}\; $ layer and ${n_p}$ represents the refractive index of the prism [46,47]:

(8)$${n_k} = \sqrt {\left( {\frac{{{\mu_k}}}{{{\varepsilon_k}}}} \right)}$$

(9)$${\theta _k} = {\cos ^{ - 1}}\frac{{\sqrt {({{\varepsilon_k} - {n_p}^2{{\sin }^2}{\theta_1}} )} }}{{{\varepsilon _k}}}$$

Again, the arbitrary phase constant denoted ${\beta _k}$ for respective to ${\textrm{k}^{\textrm{th}}}$ layer is [46,47]:

(10)$${\beta _k} = \frac{{2\pi {d_k}}}{\lambda }\sqrt {({{\varepsilon_k} - {n_1}^2{{\sin }^2}{\theta_1}} )}$$

So finally, the angle of the entrance ${\theta _k}$ for ${\textrm{k}^{\textrm{th}}}$ layer can be shown in the following [46]:

(11)$${\theta _k} = a\cos (\sqrt {1 - ({n_{k - 1}}/{n_k}){{\sin }^2}{\theta _1}} )$$

Here mentioned ${\textrm{d}_\textrm{k}}$ and ${\mathrm{\varepsilon }_\textrm{k}}$ are the thickness and dielectric constant for ${\textrm{k}^{\textrm{th}}}$ layer and $\mathrm{\lambda }\; $, ${\mathrm{\theta }_1}$ are incident wavelength and angle, respectively. As the refractive index of the sensing medium is increasing, it makes the SPR angle shift right and increases the reflectance intensity (%). This phenomenon can be explained using Eq. (12), and the detailed explanation is in [48,9]:

(12)$${\mathrm{\theta }_{\textrm{spr}}} = {\sin ^{ - 1}}\frac{{{\mathrm{\eta }_{\textrm{eff}\; }}{\mathrm{\eta }_\textrm{a}}}}{{{\mathrm{\eta }_\textrm{p}}\sqrt {\mathrm{\eta }_{\textrm{eff}}^2 + } \mathrm{\eta }_\textrm{a}^2}}$$

Here ${\eta _p}\; $and ${\eta _a}$ represents the prism ($\textrm{B}{\textrm{K}_7}$) and analyte or sensing medium, respectively and ${\eta _{eff}}$ represents the equivalent refractive index (RI) of the composite layer. Surface plasmon waves (SPW) are the charge density oscillation known as surface plasmon (SP), which occurs on the interface of a metal and dielectric material, and SPW has an exponential decay nature as they move from the following interface [41], [49,50]. The matching condition of wave vectors in glass ${\textrm{K}_\textrm{x}}$ and in the metal is ${\textrm{K}_{\textrm{spw}}}\; $ [41], [49,50] are denoted by Eq. (13) as follows:

(13)$${K_x} = {K_0}{n_p}\sin {\theta _1} = Re ({K_{spw}}) = Re ({K_0}\sqrt {\frac{{{\varepsilon _m}{\varepsilon _a}}}{{{\varepsilon _m} + {\varepsilon _a}}}} )$$

Here ${\varepsilon _m}$ is the permittivity of the metal layer and ${\varepsilon _a}$ is dielectric permittivity again from Fresnel refractive law between the sensing medium (analyte) and the prism [41], [49,50]:

(14)$${n_a}\sin {\theta _t} = {n_p}\sin {\theta _1}$$

(15)$${K_0}{n_a}\sin {\theta _t} = Re ({K_0}\sqrt {\frac{{{\varepsilon _m}{\varepsilon _a}}}{{{\varepsilon _m} + {\varepsilon _a}}}} )$$

Here, ${\textrm{K}_0}\; $is the wave vector in a vacuum and the refractive index of the sensing medium, ${\textrm{n}_\textrm{a}}$ and the ${\mathrm{\theta }_\textrm{t}}$ is the incident angle from the medium to the prism. So the total wave vector of SPW is shown in Eq. (16) where ${\textrm{K}_\textrm{p}}$ represents the perturbation in prism or sensing medium [41], [49,50]:

(16)$$K = {K_p} + {K_{spw}}$$

So finally, the dip of full width half maxima (FWHM) of the SPR angle shown in Eq. (17) have been explained in [41], [49,50]:

(17)$${W_\theta } = \frac{{2img(K)}}{{{K_0}{n_g}\cos ({\theta _{spr}})}}$$

From Eq. (17), we see that the term $\cos ({\mathrm{\theta }_{\textrm{spr}}})$ directly related to the FWHM change. Here, as the analyte or samples refractive index increases and causes the SPR angle (${\mathrm{\theta }_{\textrm{spr}}})$ to shift right to increase, which is resulting in the FWHM growing. Again, reflectance intensity (%) also increases with FWHM, and the SPR angle shifts due to the increment of the refractive index of the sensing medium.

Parameters used for sensor sensitivity comparison are angular sensitivity (S), detection accuracy (DA), Figure of merit (FOM) [13]. For a good quality sensor, all these parameters must be as high as possible. In angular sensitivity measurement (S) in Eq.(18), we have denoted the change in resonance angle with $\mathrm{\Delta }{\mathrm{\theta }_{\textrm{spr}}}$ and the change in refractive index unit (RIU) with $\mathrm{\Delta}\textrm{n}$ for each next consecutive refractive index ($\mathrm{\Delta}\textrm{n}$) increment.

(18)$$S = \frac{{\Delta {\theta _{spr}}}}{{\Delta n}}$$

The angular sensitivity is expressed as deg/RIU and describes the angular change due to refractive index variation. Again, the detection accuracy (DA) of the sensor is related to the full width half maxima (FWHM) of the reflectance intensity (%) curve.

(19)$$DA = \frac{1}{{FWHM}}$$

DA is expressed as 1/deg and describes the ability of a sensor to identify refractive index variation more accurately. Again, the figure of merit (FOM) parameter is applied to utilize the sensitivities and detection accuracy of the sensor defined as:

(20)$$FOM = \frac{{\Delta {\theta _{spr}}/\Delta n}}{{FWHM}}$$

3. Results and analysis

3.1 Detection of the blood hemoglobin level

The blood hemoglobin level has a linear relationship with the refractive index of blood mentioned previously. So, to detect the hemoglobin level in blood samples, we have to place the corresponding blood samples on the sensing medium, which is the surface of the graphene layer. Again, each 0.001 refractive index variation causes a 6.1025 g/l hemoglobin increment in the blood. Therefore, in Fig. 1, we have shown the relation between blood refractive index and the hemoglobin level for 0.001 refractive index variation within the range of 1.32919 to 1.34995, which is the blood refractive index variation limit for hemoglobin level increment. In Table 1, we have calculated the variation for each 0.001 refractive index change by observing the output of the minimum reflectance intensity (%) line for corresponding resonance angle shift. We have calculated all parameters from the results of FEM numerical analysis done by ‘COMSOL Multiphysics’ software, and MATLAB software environment has been used to plot graphs from those numerical data. The SPR angle shifts were calculated from the numerical data, and Fig. 4 shows the shift of SPR angle for each (0.001) refractive index variation of blood samples. In Table 1, we have calculated the reflectance change ${\textrm{R}_\textrm{t}} = \textrm{R} - {\textrm{R}_0}$ where ${\textrm{R}_0}$ is the reference reflectance intensity (%), and$\; \textrm{R}$ is the changed reflectance intensity (%). Again, for each 6.1025 g/l hemoglobin increment, total cumulative incident angle changes are calculated ${\mathrm{\theta }_\textrm{t}} = {\mathrm{\theta }_0} + \mathrm{\Delta }\mathrm{\theta }\; $where $\mathrm{\Delta }\mathrm{\theta }\; \; $is the SPR angle change for each next 0.001 refractive index variation and ${\mathrm{\theta }_0}$ is the cumulative summations of previous SPR angles change. Moreover, we have plotted the shift in resonance incident angle$\; ({\mathrm{\Delta }{\mathrm{\theta }_{\textrm{spr}}}} )$ with respect to each 6.1025 g/l hemoglobin level change in Fig. 5. Sensing parameters have been calculated using Eq. (18, 19, 20), and maximum sensitivity (S) is 200 deg/RIU, FWHM is near 10.6 deg, DA is 0.0943 $\textrm{de}{\textrm{g}^{ - 1}}$and FOM is 18.86 $\textrm{RI}{\textrm{U}^{\textrm{ - 1}}}$.

Fig. 4. Effect of sample refractive index on reflectance and incident angle for $\textrm{B}{\textrm{K}_7}$/ Au (50 nm) /$\; \textrm{PtS}{\textrm{e}_2}\; $(2 nm) / graphene (1.7 nm) sensor, inset figure shows the zoom version

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Fig. 5. Relation between Hb concentration changes with SPR angle shifts for each 6.1025 g/l hemoglobin level increment

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Table 1. Hemoglobin level detection in blood samples

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Here we have calculated sensitivity for each 0.001 refractive index variation, and we have found some sensitivities are asymmetric or below 200 deg/RIU. The main reason behind it is the shift of SPR angle ($\mathrm{\Delta }{\mathrm{\theta }_{\textrm{spr}}}$) is not linear for all refractive index variations because as it is a hybrid multilayered structure, the SPR angle shown Eq. (12) depends on several layer refractive index and interaction as denoted ${\mathrm{\eta }_{\textrm{eff}}}$. So, it is very common to get an asymmetrical shift of SPR angle ($\mathrm{\Delta }{\mathrm{\theta }_{\textrm{spr}}}$). Similar asymmetry in the shift of SPR angle ($\mathrm{\Delta }{\mathrm{\theta }_{\textrm{spr}}}$) can be found in [51,52]. As the angular sensitivity shown in Eq. (18) is directly related to the SPR angle shift, so the variation in angular sensitivity due to refractive index variation has been measured. In addition, as the number of graphene layers increases, the angular sensitivity enhances for the $\textrm{B}{\textrm{K}_7}\; $/ Au (50 nm) /$\; \textrm{PtS}{\textrm{e}_2}\; $(2 nm) / graphene (1.7 nm) layered hybrid sensor. But with the increment of graphene layer number (l), the reflectance intensity (%) and FWHM also increases, shown in detail [12,2]. Again, the hybrid configuration of $\textrm{B}{\textrm{K}_7}$ / Au (50nm) /$\; \textrm{PtS}{\textrm{e}_2}\; $(2 nm) /graphene (1.7 nm) layered sensor provides maximum angular shift sensitivities, and in this paper, we have mainly focused on angular shift sensitivities due to the sensing medium samples refractive index variation. Therefore, blood hemoglobin components could be easily detected using this prism-based graphene coated SPR sensor with high angular sensitivity.

3.2 Detection of glucose levels in urine

The glucose level in the patient's urine fluctuates if the patient is affected by diabetes. Similarly, to detect the glucose level in urine samples, we have to place the biological urine samples on the surface of the graphene layer. As there is a refractive index increment due to glucose concentration level increment in urine samples, the sensor would detect that by shifting the SPR angle to the right. Table 2 shows the detection of glucose levels in the urine sample by using the refractive index change for the respective glucose concentration variation. Again, we have measured the resonance incident angle shift due to glucose concentration level variation in urine samples. As the glucose concentration increases in urine samples, the refractive index increases resulting in an SPR angle shift. We have calculated the sensitivities for refractive index change using Eq. (18, 19, 20). Here for 0.001, refractive index change in the angular shift sensitivity (S) is 200 deg/RIU, FWHM is near 10.4 deg, DA is 0.096$\; \textrm{de}{\textrm{g}^{\textrm{ - 1}\; }}$and FOM is 19.23$\; \textrm{RI}{\textrm{U}^{\textrm{ - 1}}}$. Again, for 0.006 refractive index change, the sensitivity is 166.67 deg/RIU, FWHM is near 10.8 deg, DA is 0.0925$\; \textrm{de}{\textrm{g}^{\textrm{ - 1}}}\; $and FOM is 15.43 $\textrm{RI}{\textrm{U}^{\textrm{ - 1}}}$calculated from Fig. 6. So, for urine glucose level (0-15) mg/dl to 0.625 gm/dl change, we have found the refractive index variation of 0.001 and our corresponding SPR angle shift from 76.1 deg to 76.3 deg. So, the angular sensitivity calculated is 200 deg/RIU for the following particular change of glucose concentration level in urine samples. Similarly, for glucose concentration level change from 1.25 gm/dl to 2.5 gm/dl, we get refractive index variation 0.001, and the SPR angle change from 76.5 deg to 76.7 deg. So, the angular sensitivity calculated for glucose concentration 1.25 gm/dl to 2.5 gm/dl is 200 deg/RIU. Finally, for glucose concentration levels from 5 gm/dl to 10 gm/dl, the refractive index variation is 0.006, and the corresponding SPR angle changes from 77.3 deg to 78.3 deg. So, the angular sensitivity for 5 gm/dl to 10 gm/dl glucose concentration change is 166.67 deg/RIU. So, by observing the SPR angle shift in the output detector due to glucose concentration variation, the glucose level in urine samples can be measured accurately. Therefore, the detection of glucose levels has been demonstrated with this SPR high sensitivity sensor.

Fig. 6. Detection of glucose level in the urine samples using refractive index inset figure shows the zoom version

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Table 2. Glucose level detection using patient urine samples

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4. Conclusion

In this paper, we have focused mainly on the detection of blood hemoglobin level and glucose concentration level in urine samples using FEM based numerical simulation. We have shown a relation of the hemoglobin level change in the blood and resonance angle for each 0.001 refractive index variation. In addition, we have also demonstrated the resonance angle shift due to the change in glucose concentration level in urine samples. So, the practical implementation of this SPR sensor for detecting the blood hemoglobin level and glucose level in urine samples might help to detect these biological samples more precisely due to the sensor's simple structure and high sensitivity.

Disclosures

The authors declare no conflicts of interest.

Data availability

No data were generated or analyzed in the presented research.

References

1. Q. Yan, B. Peng, G. Su, B. E. Cohan, T. C. Major, and M. E. Meyerhoff, “Measurement of tear glucose levels with amperometric glucose biosensor/capillary tube configuration,” Anal. Chem. 83(21), 8341–8346 (2011). [CrossRef]

2. T. B. A. Akib, S. F. Mou, M. M. Rahman, M. M. Rana, M. R. Islam, I. M. Mehedi, M. A. P. Mahmud, and A. Z. Kouzani, “Design and Numerical Analysis of a Graphene-Coated SPR Biosensor for Rapid Detection of the Novel Coronavirus,” Sensors 21(10), 3491 (2021). [CrossRef]

3. M. A. Jabin, K. Ahmed, M. J. Rana, B. K. Paul, Y. Luo, and D. Vigneswaran, “Titanium-Coated Dual-Core D-Shaped SPR-Based PCF for Hemoglobin Sensing,” Plasmonics 14(6), 1601–1610 (2019). [CrossRef]

4. M. S. Rahman, M. R. Hasan, K. A. Rikta, and M. S. Anower, “A novel graphene coated surface plasmon resonance biosensor with tungsten disulfide (WS2) for sensing DNA hybridization,” Opt. Mater. 75, 567–573 (2018). [CrossRef]

5. H. Quan and Z. Guo, “Simulation of whispering-gallery-mode resonance shifts for optical miniature biosensors,” J. Quant. Spectrosc. Radiat. Transfer 93(1-3), 231–243 (2005). [CrossRef]

6. L. M. Alameri, T. S. Mansour, F. F. Rashid, and S. J. Belal, “Design in line lma-10 photonic crystal fiber mzi for detection and investigation of beta thalassemia,” Medico-Legal Updat. 20(1), 591–595 (2020). [CrossRef]

7. X. Dai, Y. Liang, Y. Zhao, S. Gan, Y. Jia, and Y. Xiang, “Sensitivity enhancement of a surface plasmon resonance with tin selenide (SnSe) allotropes,” Sensors 19(1), 173 (2019). [CrossRef]

8. V. E. Bochenkov, M. Frederiksen, and D. S. Sutherland, “Enhanced refractive index sensitivity of elevated short-range ordered nanohole arrays in optically thin plasmonic Au films,” Opt. Express 21(12), 14763 (2013). [CrossRef]

9. B. Dey, M. S. Islam, and J. Park, “Numerical design of high-performance WS2/metal/WS2/graphene heterostructure based surface plasmon resonance refractive index sensor,” Results Phys. 23, 104021 (2021). [CrossRef]

10. R. Islam, B. Hossain, and I. M. Mehedi, “Modeling of highly improved SPR sensor for formalin detection,” Results Phys. 16, 102874 (2020). [CrossRef]

11. W. W. Lam, L. H. Chu, C. L. Wong, and Y. T. Zhang, “A surface plasmon resonance system for the measurement of glucose in aqueous solution,” Sens. Actuators, B 105(2), 138–143 (2005). [CrossRef]

12. T. B. A. Akib, S. F. Mou, M. M. Rahman, M. M. Rana, M. R. Islam, I. M. Mehedi, M. A. Parvez Mahmud, and A. Z. Kouzani, “Design and numerical analysis of a graphene-coated spr biosensor for rapid detection of the novel coronavirus,” Sensors 21(1), 1–5 (2021). [CrossRef]

13. M. M. Rahman, M. M. Rana, M. S. Rahman, M. S. Anower, M. A. Mollah, and A. K. Paul, “Sensitivity enhancement of SPR biosensors employing heterostructure of PtSe2 and 2D materials,” Opt. Mater. 107, 110123 (2020). [CrossRef]

14. A. Nisha, P. Maheswari, P. M. Anbarasan, K. B. Rajesh, and Z. Jaroszewicz, “Sensitivity enhancement of surface plasmon resonance sensor with 2D material covered noble and magnetic material (Ni),” Opt. Quantum Electron. 51(1), 19 (2019). [CrossRef]

15. M. S. Anower, M. M. Rahman, and M. S. Rahman, “Hybrid Heterostructures for SPR Biosensor,” in Biosensors - Current and Novel Strategies for Biosensing (IntechOpen, 2021), p. Ch. 8. [CrossRef]

16. Y. Zhu, S. Murali, W. Cai, X. Li, J. W. Suk, J. R. Potts, and R. S. Ruoff, “Graphene and graphene oxide: Synthesis, properties, and applications,” Adv. Mater. 22(35), 3906–3924 (2010). [CrossRef]

17. J. B. Maurya, Y. K. Prajapati, V. Singh, J. P. Saini, and R. Tripathi, “Performance of graphene–MoS 2 based surface plasmon resonance sensor using silicon layer,” Opt. Quantum Electron. 47(11), 3599–3611 (2015). [CrossRef]

18. Y. Jia, Z. Li, H. Wang, M. Saeed, and H. Cai, “Sensitivity enhancement of a surface plasmon resonance sensor with platinum diselenide,” Sensors 20(1), 131 (2019). [CrossRef]

19. A. Bijalwan, B. K. Singh, and V. Rastogi, “Surface Plasmon Resonance-Based Sensors Using Nano-Ribbons of Graphene and WSe2,” Plasmonics 15(4), 1015–1023 (2020). [CrossRef]

20. A. Pal and A. Jha, “A theoretical analysis on sensitivity improvement of an SPR refractive index sensor with graphene and barium titanate nanosheets,” Optik 231, 166378 (2021). [CrossRef]

21. P. Varasteanu and M. Kusko, “A Multi-Objective Optimization of 2D Materials Modified Surface Plasmon Resonance (SPR) Based Sensors: An NSGA II Approach,” Appl. Sci. 11(10), 4353 (2021). [CrossRef]

22. A. K. Mishra, S. K. Mishra, and R. K. Verma, “Graphene and beyond Graphene MoS2: A New Window in Surface-Plasmon-Resonance-Based Fiber Optic Sensing,” J. Phys. Chem. C 120(5), 2893–2900 (2016). [CrossRef]

23. L. Wu, H. S. Chu, W. S. Koh, and E. P. Li, “Highly sensitive graphene biosensors based on surface plasmon resonance,” Opt. Express 18(14), 14395 (2010). [CrossRef]

24. P. K. Maharana and R. Jha, “Chalcogenide prism and graphene multilayer based surface plasmon resonance affinity biosensor for high performance,” Sens. Actuators, B 169, 161–166 (2012). [CrossRef]

25. Z. Wang, Q. Li, F. Besenbacher, and M. Dong, “Facile Synthesis of Single Crystal PtSe2Nanosheets for Nanoscale Electronics,” Adv. Mater. 28(46), 10224–10229 (2016). [CrossRef]

26. M. Sajjad, E. Montes, N. Singh, and U. Schwingenschlögl, “Superior Gas Sensing Properties of Monolayer PtSe₂,” Adv. Mater. Interfaces 4(5), 1600911 (2017). [CrossRef]

27. P. Li, L. Li, and X. C. Zeng, “Tuning the electronic properties of monolayer and bilayer PtSe2 via strain engineering,” J. Mater. Chem. C 4(15), 3106–3112 (2016). [CrossRef]

28. C. Yim, K. Lee, N. Mcevoy, M. O. Brien, S. Riazimehr, N. C. Berner, C. P. Cullen, J. Kotakoski, J. C. Meyer, M. C. Lemme, and G. S. Duesberg, “High-Performance Hybrid Electronic Devices from Layered PtSe 2 Films Grown at Low Temperature,” ACS Nano 10(10), 9550–9558 (2016). [CrossRef]

29. J. Lou, T. Cheng, S. Li, and X. Zhang, “Surface plasmon resonance photonic crystal fiber biosensor based on gold-graphene layers,” Opt. Fiber Technol. 50, 206–211 (2019). [CrossRef]

30. A. K. Geim and K. S. Novoselov, “The rise of graphene,” in Nanoscience and Technology: A Collection of Reviews from Nature Journals (World Scientific, 2010), pp. 11–19.

31. D. T. Gilbertson, J. P. Ebben, R. N. Foley, E. D. Weinhandl, B. D. Bradbury, and A. J. Collins, “Hemoglobin level variability: Associations with mortality,” Clin. J. Am. Soc. Nephrol. 3(1), 133–138 (2008). [CrossRef]

32. T. B. Drüeke, F. Locatelli, N. Clyne, K.-U. Eckardt, I. C. Macdougall, D. Tsakiris, H.-U. Burger, and A. Scherhag, “Normalization of Hemoglobin Level in Patients with Chronic Kidney Disease and Anemia,” N. Engl. J. Med. 355(20), 2071–2084 (2006). [CrossRef]

33. M. R. Islam, M. Moinuddin, A. Ahmed, and S. M. Rahman, “Association of sickle cell disease with anthropometric indices among under-five children: evidence from 2018 Nigeria Demographic and Health Survey,” BMC Med. 19(1), 5 (2021). [CrossRef]

34. A. K. Ajad, M. J. Islam, M. R. Kaysir, and J. Atai, “Highly sensitive bio sensor based on WGM ring resonator for hemoglobin detection in blood samples,” Optik 226, 166009 (2021). [CrossRef]

35. M. A. Pérez, O. Gonzlez, and J. R. Arias, “Optical Fiber Sensors for Chemical and Biological Measurements,” in Current Developments in Optical Fiber Technology (IntechOpen, 2013). [CrossRef]

36. X. Jouven, R. N. Lemaître, T. D. Rea, N. Sotoodehnia, J. P. Empana, and D. S. Siscovick, “Diabetes, glucose level, and risk of sudden cardiac death,” Eur. Heart J. 26(20), 2142–2147 (2005). [CrossRef]

37. “Diabetes,” https://www.who.int/health-topics/diabetes#tab=tab_1.

38. M. H. Sani and S. Khosroabadi, “A Novel Design and Analysis of High-Sensitivity Biosensor Based on Nano-Cavity for Detection of Blood Component, Diabetes, Cancer and Glucose Concentration,” IEEE Sens. J. 20(13), 7161–7168 (2020). [CrossRef]

39. M. Bruna and S. Borini, “Optical constants of graphene layers in the visible range,” Appl. Phys. Lett. 94(3), 031901 (2009). [CrossRef]

40. D. L. Fay, “The angluar reflectance of single-layer gradient refractive-index films,” Angew. Chem., Int. Ed. Engl. 6(11), 951–952 (1967). [CrossRef]

41. C. Basak, K. Hosain, and A. Ahmed, “Design and Simulation of a High Sensitive Surface Plasmon Resonance Biosensor for Detection of Biomolecules,” Sens. Imaging 21(1), 2 (2020). [CrossRef]

42. N. AL-Janaby and A. AL-Dergazly, “Fabrication of multi-mode tip fiber sensor based on surface plasmon resonance (SPR),” Sustain. Eng. Innov. 2(1), 10–17 (2020). [CrossRef]

43. A. Srivastava, C. Galande, L. Ci, L. Song, C. Rai, D. Jariwala, K. F. Kelly, and P. M. Ajayan, “Novel liquid precursor-based facile synthesis of large-area continuous, single, and few-layer graphene films,” Chem. Mater. 22(11), 3457–3461 (2010). [CrossRef]

44. J. N. Coleman, M. Lotya, A. O’Neill, S. D. Bergin, P. J. King, U. Khan, K. Young, A. Gaucher, S. De, R. J. Smith, I. V. Shvets, S. K. Arora, G. Stanton, H. Y. Kim, K. Lee, G. T. Kim, G. S. Duesberg, T. Hallam, J. J. Boland, J. J. Wang, J. F. Donegan, J. C. Grunlan, G. Moriarty, A. Shmeliov, R. J. Nicholls, J. M. Perkins, E. M. Grieveson, K. Theuwissen, D. W. McComb, P. D. Nellist, and V. Nicolosi, “Two-dimensional nanosheets produced by liquid exfoliation of layered materials,” Science 331(6017), 568–571 (2011). [CrossRef]

45. H. Wang, H. Zhang, J. Dong, S. Hu, W. Zhu, W. Qiu, H. Lu, J. Yu, H. Guan, S. Gao, Z. Li, W. Liu, M. He, J. Zhang, Z. Chen, and Y. Luo, “Sensitivity-enhanced surface plasmon resonance sensor utilizing a tungsten disulfide (WS 2) nanosheets overlayer,” Photonics Res. 6(6), 485 (2018). [CrossRef]

46. M. B. Hossain, I. M. Mehedi, M. Moznuzzaman, L. F. Abdulrazak, and M. A. Hossain, “High performance refractive index SPR sensor modeling employing graphene tri sheets,” Results Phys. 15, 102719 (2019). [CrossRef]

47. M. Saifur Rahman, K. A. Rikta, L. Bin Bashar, and M. S. Anower, “Numerical analysis of graphene coated surface plasmon resonance biosensors for biomedical applications,” Optik 156, 384–390 (2018). [CrossRef]

48. M. B. Hossain, T. Tasnim, L. F. Abdulrazak, M. M. Rana, and M. R. Islam, “A Numerical Approach to Design the Kretschmann Configuration Based Refractive Index Graphene-MoS2 Hybrid Layers With TiO2-SiO2 Nano for Formalin Detection,” Photonic Sens. 10(2), 134–146 (2020). [CrossRef]

49. W. P. Chen and J. M. Chen, “Use of surface plasma waves for determination of the thickness and optical constants of thin metallic films,” J. Opt. Soc. Am. 71(2), 189–191 (1981). [CrossRef]

50. G. Lan, S. Liu, X. Zhang, Y. Wang, and Y. Song, “A simplified high figure-of-merit prism-free surface plasmon resonance refractive index sensor based on self adaptive angular interrogation,” Rev. Sci. Instrum. 86(2), 025006 (2015). [CrossRef]

51. S. Mohapatra and R. S. Moirangthem, “Theoretical study of modulated multilayer SPR device for improved refractive index sensing,” in IOP Conference Series: Materials Science and Engineering (2018), Vol. 310.

52. N. Mudgal, A. Saharia, A. Agarwal, J. Ali, P. Yupapin, and G. Singh, “Modeling of highly sensitive surface plasmon resonance (SPR) sensor for urine glucose detection,” Opt. Quantum Electron. 52(6), 307–314 (2020). [CrossRef]

Refractive index	Refractive index change ( $Δ n$ )	Incident angle ( $θ_{spr}$ )	Incident angle shift ( $Δ θ_{spr}$ )	Reflectance (%)	Reflectance change (%) $R_{t} = R - R_{0}$	Sensitivit (S) (deg/RIU)	Hemoglobin increment (HB) (g/l)	total Incident angle change ( $θ_{t} = θ_{0} + θ$ )
1.32919	ref	75.2	ref	32.22 ( $R_{0}$ )	ref	ref	ref	ref
1.33019	0.001	75.3	0.1	32.47	0.2500	100	6.1025	0.1
1.33119	0.001	75.5	0.2	32.73	0.5100	200	12.205	0.3
1.33219	0.001	75.7	0.2	33.003	0.7830	200	18.3075	0.5
1.33319	0.001	75.8	0.1	33.27	1.0500	100	24.410	0.6
1.33419	0.001	76	0.2	33.55	1.3300	200	30.5125	0.8
1.33519	0.001	76.2	0.2	33.84	1.6200	200	36.615	1
1.33619	0.001	76.4	0.2	34.13	1.9100	200	42.7175	1.2
1.33719	0.001	76.5	0.1	34.43	2.2100	100	48.820	1.3
1.33819	0.001	76.7	0.2	34.74	2.5200	200	54.92250	1.5
1.33919	0.001	76.9	0.1	35.05	2.8300	100	61.025	1.6
1.34019	0.001	77.1	0.2	35.38	3.1600	200	67.1275	1.8
1.34119	0.001	77.3	0.2	35.73	3.5100	200	73.230	2
1.34219	0.001	77.4	0.1	36.07	3.8500	100	79.3325	2.1
1.34319	0.001	77.6	0.2	36.44	4.2200	200	85.4350	2.3
1.34419	0.001	77.8	0.2	36.81	4.5900	200	91.5375	2.5
1.34519	0.001	78	0.2	37.20	4.9800	200	97.6400	2.7
1.34619	0.001	78.1	0.1	37.62	5.4000	100	103.7425	2.8
1.34719	0.001	78.3	0.2	38.05	5.8300	200	109.8450	3
1.34819	0.001	78.5	0.2	38.5	6.2800	200	115.9475	3.2
1.34919	0.001	78.7	0.2	38.97	6.7500	200	122.0500	3.4

Refractive index	Refractive index change ( $Δ n$ )	Incident angle ( $θ_{spr}$ )	Incident angle shift ( $Δ θ_{spr}$ )	Reflectance (%)	Reflectance change (%) $R_{t} = R - R_{0}$	Sensitivit (S) (deg/RIU)	Hemoglobin increment (HB) (g/l)	total Incident angle change ( $θ_{t} = θ_{0} + θ$ )
1.32919	ref	75.2	ref	32.22 ( $R_{0}$ )	ref	ref	ref	ref
1.33019	0.001	75.3	0.1	32.47	0.2500	100	6.1025	0.1
1.33119	0.001	75.5	0.2	32.73	0.5100	200	12.205	0.3
1.33219	0.001	75.7	0.2	33.003	0.7830	200	18.3075	0.5
1.33319	0.001	75.8	0.1	33.27	1.0500	100	24.410	0.6
1.33419	0.001	76	0.2	33.55	1.3300	200	30.5125	0.8
1.33519	0.001	76.2	0.2	33.84	1.6200	200	36.615	1
1.33619	0.001	76.4	0.2	34.13	1.9100	200	42.7175	1.2
1.33719	0.001	76.5	0.1	34.43	2.2100	100	48.820	1.3
1.33819	0.001	76.7	0.2	34.74	2.5200	200	54.92250	1.5
1.33919	0.001	76.9	0.1	35.05	2.8300	100	61.025	1.6
1.34019	0.001	77.1	0.2	35.38	3.1600	200	67.1275	1.8
1.34119	0.001	77.3	0.2	35.73	3.5100	200	73.230	2
1.34219	0.001	77.4	0.1	36.07	3.8500	100	79.3325	2.1
1.34319	0.001	77.6	0.2	36.44	4.2200	200	85.4350	2.3
1.34419	0.001	77.8	0.2	36.81	4.5900	200	91.5375	2.5
1.34519	0.001	78	0.2	37.20	4.9800	200	97.6400	2.7
1.34619	0.001	78.1	0.1	37.62	5.4000	100	103.7425	2.8
1.34719	0.001	78.3	0.2	38.05	5.8300	200	109.8450	3
1.34819	0.001	78.5	0.2	38.5	6.2800	200	115.9475	3.2
1.34919	0.001	78.7	0.2	38.97	6.7500	200	122.0500	3.4

Detection of hemoglobin in blood and urine glucose level samples using a graphene-coated SPR based biosensor

Abstract

1. Introduction

1.1 Blood hemoglobin

1.2 Urine samples

2. Design methodology

2.1 Structural modeling

2.2 Mathematical and theoretical modeling

3. Results and analysis

3.1 Detection of the blood hemoglobin level

3.2 Detection of glucose levels in urine

4. Conclusion

Disclosures

Data availability

References

Data availability

Cited By

Figures (6)

Tables (2)

Equations (20)

OSA Continuum

Glucose level	Refractive index	Refractive index change ( $Δ n$ )	Incident angle ( $θ_{spr}$ )	Incident angle shift ( $Δ θ_{spr}$ )	Reflectance (%)	Reflectance change respect to (ref)	Sensitivity (S) (deg/RIU)
0 -15 mg/dl	1.335	ref	76.1	ref	33.79	ref	ref
0.625gm/dl	1.336	0.001	76.3	0.2	34.80	1.01	200
1.25gm/dl	1.337	ref	76.5	ref	34.37	ref	ref
2.5gm/dl	1.338	0.001	76.7	0.2	34.68	0.31	200
5gm/dl	1.341	ref	77.3	ref	35.69	ref	ref
10gm/dl	1.347	0.006	78.3	1.0	37.97	2.28	166.67