- Email: [email protected]
High performance refractive index SPR sensor modeling employing graphene tri sheets
Journal Pre-proofs High Performance Refractive Index SPR Sensor Modeling Employing Graphene Tri Sheets Md. Biplob Hossain, Ibrahim Mustafa Mehedi, M. Moznuzzaman, Lway Faisal Abdulrazak, Md. Amzad Hossain PII: DOI: Reference:
S2211-3797(19)32748-2 https://doi.org/10.1016/j.rinp.2019.102719 RINP 102719
To appear in:
Results in Physics
Received Date: Revised Date: Accepted Date:
12 September 2019 1 October 2019 1 October 2019
Please cite this article as: Biplob Hossain, Md., Mustafa Mehedi, I., Moznuzzaman, M., Faisal Abdulrazak, L., Amzad Hossain, Md., High Performance Refractive Index SPR Sensor Modeling Employing Graphene Tri Sheets, Results in Physics (2019), doi: https://doi.org/10.1016/j.rinp.2019.102719
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
© 2019 The Authors. Published by Elsevier B.V.
High Performance Refractive Index SPR Sensor Modeling Employing Graphene Tri Sheets Md. Biplob Hossain1*, Ibrahim Mustafa Mehedi2, M. Moznuzzaman1, Lway Faisal Abdulrazak3, Md. Amzad Hossain1 1Department
of Electrical and Electronic Engineering Jashore University of Science & Technology, Jashore, Bangladesh 2Center
Excellence in Intelligent Engineering Systems (CEIES) Electrical and Computer Engineering Department (ECE) King Abdulaziz University, Jeddah, Saudi Arabia 3 Department of Computer Science Cihan University Slemani, Sulaimaniya, Iraq.
Email: [email protected], [email protected], [email protected], [email protected], [email protected] * Corresponding Author: Dept. of Electrical and Electronic Engineering Jashore University of Science & Technology Jashore, Bangladesh [email protected]
Abstract: This article illustrates a graphene tri sheets based surface plasmon resonance (SPR) biosensor. The exciting configuration consists of Gold (Au), graphene, prism (SF11 glass) and sensing medium. The angular interrogation scheme is basically utilized owing to inspect the light reflection from the sensor. For sake of the augmentation of sensor sensitivity (S), signal to noise ratio (SNR), quality factor (QF), first of all, the impact of adding graphene layer is investigated and then the number of graphene layers are optimized to tri layers. According to that tri sheets, the SPR curves are sketched and comparison of sensor sensitivity, SNR, the quality factor is made among the existing works. It is audited that an extraordinary improvement of sensitivity to 121.67° RIU-1. The most effective graphene layers states with improved SNR of 2.21and QF of 36.87 RIU-1 respect conventional SPR sensor. After then, the electric field intensity on implanting graphene sheet is analyzed by incorporating the finite difference time domain (FDTD) method by applying the Opti FDTD multiphysiscs commercial software environment. The proposed design bears the advantages of high sensitivity, QF and SNR comparing with the existing sensors along with simple stricture, no need of plasmonic coatings of other dielectrics, compactness, light weight, real time fabrication flexibility due to avoid multi materials optical structure. Keywords: ATR; Quality factor; signal to noise ratio: Sensitivity ; FDTD method; Graphene; SPR.
1. Introduction Surface plasmon resonance (SPR) technology-based biosensors have stretched out great eye as one of the prominent sensing technologies because of their hopeful applications in sundry venues such as detection of a biomolecule, pathological diagnostics, biochemical marking off, environmental trouble monitoring, etc.[1-3]. They have conducted a crucial indication in monitoring diversified interactions of biomolecules namely making bonds among the proteins and hybridization of DNA [4-5]. SPR, an optical spectacle, provides a label-free way of inspecting the interactions of binding between the analyte and biomolecule [6–9]. SPR has an augmentative interest in the various sectors of optoelectronics and optics. Besides that SPR is widely applied in the plasmonic detections [10], biomedical diagnosis [11], the light-emitting diode of organic materials [12], and optical solar cells [12-13], etc.
Surface Plasmons (SPs), materially are the charge density oscillations that are localized at the interfacing surface of a dielectric in any possible state either solid, gas or liquid and a metal (e.g. silver or gold) propagating on the interface [14]. The propagation of the SPs is very much dependent on the refractive index of the medium adjoining to the metal that shapes it a powerful tactic of tracking the changes in the refractive index of a sample for binding events and in this way, it becomes effective for biosensing applications [15]. When the settlement of a particular incident circumstance happens [16], surface plasmon wave (SPW) can get activated and the activation for SPR is basically guided by the prospect of the drastic dip in reflectance and a high numerical reflection [17]. The reflectance dip and the wave vector of SPR wave are the large-handed reactionaries to the changeability of the complex value of the refractive index (RI) of the metal ledge and the surroundings of the metal ledge, and their geometrical ground which depends on the excitation of the SPW [18]. Biosensors using the SP method possess rapid and extremely responsive to biomolecular detection [19] that makes it more convenient than fluorescence-based optical biosensors which require more time and have high molecular binding disorder [20]. Optical biosensors based on SPR technology have illustrious uses in biological and chemical detecting involving the measurings on the doping of an analyte a perplexing sample and the kinetics of biomolecular interactions [21-22]. Over the last several years, the architecture of SPR based biosensors have got thriving attention in the medical sector for diagnostic applications [23]. In very recent, the hybrid architecture SPR biosensors for medical diagnostics as well as optical interactions have a chemical action between adenine (A) and thymine (T) or between cytosine (C) and guanine (G) [24]. The attenuated total reflection (ATR) configured SPR biosensor renders in two modes of operation: Firstly, the angular investigation operating mode where the wavelength of the incident light is fixed, and the input entrance angle is changed and secondly the wavelength investigation operating mode where the entrance angle is fixed and the wavelength is changed [14]. Photonic crystal based Kretschmann [14] configuration SPR sensor in the angular interrogation scheme possesses numerous amenities over the prism coupled SPR sensor configuration in wavelength interrogation scheme [18]. Many researchers prefer the first scheme of operations because of its tightness, lightweight, billowy sensitivity and mechanical facility [25]. Consequently, this type of sensor gives the opportunity of being miniature and hence it facilitates the chemical or biological sensing applications [26]. Graphene is arranged like a honeycomb lattice and is of two-dimension graphite shows numerous properties namely low reluctance, superior carrier mobility, greater optical transparency, tenability, etc. [27-31]. The effectual excitement and propagation of surface plasmons with the graphene has been proved both experimentally and theoretically [28]. A large enhancement in the sensitivity of the SPR sensor become possible by using graphene as a detecting layer [26]. In Ref.[34], L. Wu, et. al, presented a highly sensitive SPR biosensor by using the graphene layer to enhance the sensitivity caused by the light absorbed by the graphene [35]. They reported, the sensitivity can be improved to 25% only using single graphene layer due to grapehe’s extraordinary optical absorption and plasmonic properties [34]. A higher optical absorption will lead to a significant effect of SPR signals [36-38]. In [36], Leiming Wu, et. al reported a SPR biosensor by using the MoS2–graphene hybrid structure to enhance the sensitivity to about 98.2% when the number of MoS2 layer is six. In literature [39], authors have also reported a SPR sensor based on MoS2–graphene hybrid structure with aluminum (Al) film in 2016. The performance of the biosensor can be enhanced by using this hybrid structure rather using only graphene or only MoS2 [40]. All of the design mentioned in this paragraph, were not show the effect of SNR and QF due to use hybrid structure. Because of adding different layers on metallic film, it increases undoubtly sensitivity but at the same time it reduces drastically SNR and QF along with increases fabrication complexity [12, 16, 41]. But a good sensor must have high sensitivity, SNR and QF as much as possible. So, till now,a newer approach which confirms very simple in structure along with high sensitivity, SNR and QF is still requird. In this article, we have used graphene tri sheets structure to confirm at a time, both high sensitivity, SNR & QF and simple optical structure. In this work, the SPR sensor with graphene tri layers as an plasmonic layer is excised widely for the detection of biomollecular hybridization. For the charged analytes graphene is awfully sensorial (ions, DNA, cells, etc.). As an electric field arises around the graphene dramatically, it becomes a model material for aristocratic performance sensors. The outcome of attaching graphene is researched and optimization is drawn to three graphene layers aiming to the enhancement of sensitivity (S), quality factor (QF) and signal to noise ratio (SNR). Hereafter, the SPR responses with the tri graphene layers are plotted and a comparison is drawn by sensitivity, signval to noise ratio, and quality factor among the existing deeds. Close observation is stretched out that the sensitivity of the sensor with optimized number layers of graphene is enhanced to a wishful value of 121.67 deg/RIU as well as with excellently improved SNR value of 2.21 and QF of 36.87 per RIU with respect to conventional SPR sensors. Finally, by efficiently incorporating the finite difference time domain (FDTD)
technique, the effect of insertion of the graphene ten layers on electric field distribution is analyzed with the help of a commercial Opti FDTD solution software.
2. Methodology 2.1. Frame Model of Proposed Sensor The proposed structure of SPR biosensor is fixed with four layers and the configuration is exhibited in Fig. 1. The entrance light is in the transverse magnetic (TM) polarization situation is one of the most significant criteria required for SPs excitation [25]. In the path of the incident, a polarizer is utilized to enliven the TM polarized light. As optical nonlinearity can be improved at low wavelength, the operating wavelength is chosen at 633 nm [42-44]. In all respects of the photon energy band, micro band optical change of state occurs because of the band shape of graphene [45], [46]. Consequently, the thorough sensitivity of the sensor is ameliorated with the small probable Kerr effect at the wavelength of 633 nm [47]. To design our proposed sensor in angle investigation scheme with Kretschmann layout, we availed the Fresnel ocular system which is smeared circumstantially in literature [43, 47, 24,48-51]. For providing additional momentum to the light, large wave vector photonic quartz required to be applied [2]. In order to meet up this criterion, we marked a prism with a high value of RI of (np) of 1.7786 such as SF11[47] and applied as a base layer. We specified a noble metal such as gold (nAu= 0.1838+i 3.4313, thickness, dAu =50 nm) layer as a second layer. The gold layer thickness is considered to 50 nm over the analysis to achieve superior quality factor and detection accuracy [24, 47]. Over and above, the SPR angle shows a fluctuating habit with thickness other than 50 nm that reveals trouble to search out a lasting sensing situation [25] because gold is marked as utmost compatible metal against to the corrosion and oxidation as well as excellent chemical fixity and greater optical responses [43, 47]. The resonant activation of photon and electron happens when the wavevector of the incident light stays imprisoned at the interface and declines in an exponential manner in the wry directions [43, 50]. The souse of the SPR is very responsive to the alteration in the complex RI of the metal ledge, contiguous to the dielectric medium and structural shapes [25, 43], which outcome strengthened sensitivity [25]. For the sake of accelerating the sensitivity change with standard detection accuracy (DA), we specified graphene as a third smear that has a highly complex RI ( ng=3.0 + i 1.1487 [50, 51]) as well as superior carrier mobility, greater optical transparency, extraordinary mechanical flexibility, mechanical potency [38-41], little resistivity, attunable conductivity [38]. Till the last, phosphate buffer saline (PBS) fluid with RI nb =1.34 is marked as an empty responding dielectric mean that pays the opportunity of higher adsorption of biomolecules [52, 53].
Fig 1. Schematic representation of a 4-smeared model of SPR biosensor The graphene-based biosensor adsorbs ssDNA biomolecules and produces a native increment in the RI at the surface of Graphene-Au [49]. In DNA hybridization as depicted in Fig. 2, when two single-stranded (ssDNA) DNA, representing the probe and target, are combined at the same place and form a double-stranded (dsDNA) helix shape which is demarked as complementary DNA mixing event. In this raised model, it interprets the characterization analytically of the sensor sothat perceiving of the hybridization of target DNAs to the probe DNAs which are pre-immobilized on graphene are made effectively. The SPR process for the proposed model is also capable of comparing single-base mismatched DNA events with complementary events.
single-strand DNA(Probe) p
p
5’
4 3 S 2 1
4 3 S 2 1
5
p
p 4 3 S 2 1
5
T
G
p 4 3 S 2 1
5
T
2 1 S 3 4
p
p
2 1 S 3 4
2 1 S 3 4
5
5 p
p
2 1 S 3 4
4 3 S 2 1
5
2 1 S 3 4
2 1 S 3 4
5 p
p
5
C
C 5
3’
p 4 3 S 2 1
5
T
G
G 5
p
p 4 3 S 2 1
5
T
C
C 3’
p 4 3 S 2 1
5
G 2 1 S 3 4
5
5 p
p
2 1 S 3 4
5
5’ p
Complementary DNA(target) (a) Perfectly Matched (dsDNA) Hybridization Event
single strand DNA(Probe) p
p
5’
4 3 S 2 1
4 3 S 2 1
5
4 3 S 2 1
5
T
G
p
p 5
T
p
2 1 S 3 4
p 4 3 S 2 1
5
p
p 4 3 S 2 1
5
T
C
C 3’
p 4 3 S 2 1
4 3 S 2 1
5
3’
5
T
G
G 5 p
2 1 S 3 4
2 1 S 3 4
5
5 p
p
2 1 S 3 4
2 1 S 3 4
5
p
C
p
Mismatched DNA(target)
2 1 S 3 4
5
2 1 S 3 4
2 1 3 S4
5
5 p
5’
p 2 1 S 3 4
5
5
p
p
(b) Mismatched DNA SNP Event
Fig 2. (a) Perfectly Matched ssDNA and C-DNA hybridization happened (Nitrogen base Adenine-Thymine relation with a di-hydrogen connection, Guanine-Cytosine (G-C) relation with a tri-hydrogen connection (b) Mismatched ssDNA and single based mismatched hybridization happened.
2.2 Mathematical Prototype for Proposed Sensor A monochromatic light source emits 633nm wavelength light, and the respective data are taken out in a spectrometer associated with a computer. At this time, the incident wave propagates continuously together through the x-direction as exhibited in Fig 1, with wave vector of the following equation [48,49]:
klight 2 633 n p sin in
(1)
Equation (1) represents the ingredient of light propagating parallel to the gold surface. As the outright entrance of p-polarized light has a relatively small wave vector, it becomes unable to stimulate SPW at the metaldielectric. Hence we need to incite light with a considerable incident angle. Here, θin represents the incident angle whereas np represents the RI of the prism. A fluctuation of molecules concentration in the dielectric sensing layer will create a little alteration in the RI close to the interface of plasmonic metal. Eventually, this alteration of RI will make a change in wavevector of the surface plasmons (KSPW), which may be determined by a process named attenuated total reflection (ATR). A simple description of SPW is given in Equation (2), where nAu denotes the RI of Au and the RI of graphene is denoted by ng [49,50]: k SPW
2
n 2Au n g2
633
n 2Au n g2
(2)
The majority of SPR applications connect with the real RI changes due to chemical or biochemical action [43] and therefore, Equation (3) is formed by considering real quantities only. If the wavevector of the incident light equals that of the SPW [54], resonated exhilaration of photon-electron recombining happens, which creates a shift of incident angle. If the wavevector of the incident light equals that of the SPW [54], resonated exhilaration of photon-electron recombining happens, which creates a shift of incident angle. The graphical representation of the reflectance with respect to the incident angle and also the plotting of the reflectance with respect to wavelength are celebrated as SPR curve [49, 55] and the spectrum of reflectance points out an immersion at the state of resonance [43].
This certain incident angle at which represents[48,49], as:
resonance occurred is acquainted as
SPR a sin
SPR angle and equation (3)
2 n s2 n Au 2 n 2p ( n Au n s2 )
(3)
The incident light generates an evanescent wave when passes through a prism and it is reflected from the prismgold adjacent surface. The expression for the intensity of reflection for p-polarized light is given below [24, 43, 47, 50]: Rp=|rp|2
(4)
Where,
rp
( F11 F12 n N )n1 ( F21 F22 n N ) ( F11 F12 n N )n1 ( F21 F22 n N )
(5) Through equation (7), F is destined as [43] 41 cos k Fij k 2 ink sin k
i sin k nk cos k
F11 F 21 ij
F12 F22
(6)
An explanation of the transverse RI nk, for the respective kth layer is paraded by the kinship [24]: 1/ 2
k (n p sin in ) 2 k nk cos k k2 k Correspondingly, the arbitrary phase constant βk for kth layer is also paraded by the kinship [24]: k
2
nk cos k ( z k z k 1 )
2
d k k (n p sin in ) 2
(7)
(8)
Suitably, the wave impedance of kth layer prevailed by zk [48]: zk
klight nk cos k
(9)
(2c / 633 ) k 2
Finally, the angle of entrance θk for kth layer can be represented in the following manner [48]: k a cos 1 (nk 1 / nk ) sin 2 in
(10)
Here, ϵk conveys the permittivity value for the kth layer and dk is the depth of kth layer (e,g, the layer thickness of graphene dg=L×0.34 nm, where L imparts layer number of graphene) respectively. The parameters signifying the performance of SPR sensors are mainly evaluated on the ground of its sensitivity, quality factor, and detection accuracy. The ratio of variation of SPR angle (ΔθSPR) to the variation of RI (ΔnS) is celebrated as sensitivity (S) whose unit is revealed as deg/RIU and mathematically can be assigned as [24,43,47]: SPR ; deg/RIU (11) S ns
Another but the highest significant parameter is signal to noise ratio (SNR) which is familiar with the name of detection accuracy can be ascertained from the SPR curve using the is given relation [47]. SPR ; dimensionless (12) SNR 0.5 Where Δθ0.5 represents the spectral width for 50% reflectivity of the SPR curve. The quality factor is adherent both on the spectral width and the sensitivity which can be represented as [47];
Q.F
SPR ; RIU-1 nS 0.5
(13)
Sensors that possess simultaneously exalted detection accuracy, superior sensitivity and improved quality factor are signified as a good sensor [46].
3. Numerical Results and Discussions: The performance is explained by displaying the reflectance–angle of the incident landmark of the SPR sensor prior to the addition of a probe-DNA molecule (open sensor, present only PBS solution), as shown in Fig. 3. In Fig. 3, with the increment of RI of the sample medium the angle of resonance, also increases. The RI of the sample medium has a momentous influence on the reflectance and the SPR curve [12, 43]. To look into the way by which SPR angle shifts with the shifts of the RI of the sample solution, we have enumerated several SPR curves for different refractive indexes keeping the wavelength fixed value of 633 nm. The outcomes are in Fig. 3, is developed by using equation (3) and (4). Here, we present the variation of the RI with the change in dn concentration; this relation can be expressed as reported in [12,16, 55, 58] as ncom n prim ca where ca is the dc concentration of adsorbed molecules, nprim is the refractive index of PBS, and and dn is the rate of increase in dc RI because of adsorbate immobilization. Here the considered rate of increasing parameter value dn 0.182 dc
cm3/gm as in standard cases [53,55,58]. The addition of a probe changes the refractive index of the sensing dielectric, leading to the electron-rich molecules such as DNA molecules, shifting the SPR angle rightward. 100
Reflactance (%)
80
60
40
20
0 50
1.33 1.34 1.35 1.36 1.37 1.38 1.39
55
60
65
Incidence Angle (Deg) Fig. 3: The reflection intensity spectra with the various SRI. Inset: the relatedness between reflectance and resonance angle. SPR angle shifts rightward because of the increment of RI.
At first, we consider the payoff of the insertion of the layers of graphene, which alters the refractive index of the sample dielectric [43], leading to the rise of biomolecular concentration increases the SPR angle. The number of graphene layers has a momentous impact in enhancing the sensitivity of this promised SPR biosensor. Consequently, we look at the fluctuation in the incident angle with respect to the sensing layer refractive index for different graphene layers according to the equation (3) in Fig. 4. Fig. 4, exhibits the fluctuation of the refractive index with the change of incident angle in the case of graphene as well as without graphene layers (L=1, 2,3,-----10). According to Fig. 4, increasing the number of graphene layers increases the resonance angle [24,47]. So, the proposed SPR optical biosensor’s sensitivity enhances with graphene layers.
58.5
Incident Angle (θ)
[Deg.]
58 57.5 -
Conventional Conventional with single Graphene Sheet Conventional with three Graphene Sheet Conventional with six Graphene Sheet Conventional with nine Graphene Sheet
57 -
Conventional with ten Graphene Sheet
56.5 56 55.5 55 54.5 54 1.32 1.33
1.34
1.35
1.36
1.37
1.39
1.38
Refractive index (RI)
1.40
1.41
[RIU]
Fig 4. A graphical presentation of SPR angle vs. Refractive Index for different structures.
As a second factor, we determine how SPR angle shifts with the addition of graphene layers, we have enumerated SPR curves for several layers of graphene at a constant wavelength of 633 nm after the addition of 1000 nM probe-DNA molecules [47-50] (sensor, present both PBS solution and probe-DNA). The results are in Fig. 5. The momentous rightward shift of the SPR curve is a confession sign of proper orientation of generic mutated sequence interaction with probe-DNAs, as well as that clarifies the detection of DNA hybridization [4350]. It is due to the number of charge changes with the introduction of electron-rich DNA molecules on the surface of graphene, which motivates a variation in the values of propagation constant [43]. As, the adsorption of the biomolecules near the vicinity of the graphene layer, finally a variation in the SPR angle is happened as following the equation (3). From Fig. 5, the shifting of the SPR angle in rightward is observed when graphene is affixed with Au as BRE. Again, applying a single graphene layer SPR angle 54.60 degrees has been also reported and for using ten graphene layers (L=10), an SPR angle of 58.80 degrees has been obtained. Au/N*BP
100
Reflectance (%)
80 L=0 N=1 L=1 N=2 L=2 N=4 L=3 N=6 L=6 N=8 L=10 N=10
60
40
20
0 50
55
60
65
Incidence Angle (Deg) Fig.5. Graph of SPR conventional sensor (L=0) and for varied graphene layers based sensors prior to the adsorption of molecules at angular investigation scheme λ= 633 nm. In addition, from the reflectance curve (Fig. 5), it is appeared wider and shallower as the increase of graphene layers.
Since the number of graphene layer changes, the wave vector of the plasmon wave shift according to
equation (2) due to which the resonance condition satisfied at different incident angle [54]. The wave vector shift is due to the enlargement of the SP field into graphene layer with an other propagation velocity of SP waves smaller than in the sensing layer that leads to drop in the propagation velocity SP wave and eventually results in broaden SPR curve [54]. As a result, SPs become dropped. Thus, on increasing number of graphene layer, damping increases in SPs. Since spectral width (some times called, Δθ0.5,= FWHM (full width at half maximum)) is a linear function of damping, so spectral width (broadening) increases with increasing the number of graphene monolayer [43, 50, 54]. It has been observed from equations (12) and (13) that with the increase in spectral width linearly decreasing SNR and QF thereby, employing a limitation on the maximum number of graphene layers that may be used for high performance of the biosensor. The increment in the number of graphene layers affects largely the performance of the promised SPR sensor. Thirdly, using the equations (12)-(15), performance parameters are appraised in the form of quality factor (Q.F), signal to noise ratio (SNR), and sensitivity (S). We determine the sensitivity (S), SNR and Q.F and the outcome are presented in Table 1, where the distinction between the traditional SPR sensor and raised SPR sensor is focused. An observation in Table 1 shows that the traditional SPR biosensor reveals 85.00 deg/RIU of angular sensitivity. It is possible to enrich the angular sensitivity by affixing graphene layers. For these configurations, we determined ΔnS=0.06 by incorporating equation (12) when 1000 nM complementary target DNA is present in the sensor. The calculated angular sensitivities are 93.33 deg/RIU, 108.33 deg/RIU,…and 156.67 deg/RIU respectively. Table. 1. Sensitivity (S), Signal to Noise Ratio (SNR) along with quality factor (Q.F) for various graphene layers. No.
of
ϴ𝑠𝑝𝑅
ϴ0.5
layer (L)
Change of Change SPR
of Sensitivity
SNR
Q.F
angle spectral width (S)
(Δϴ𝑠𝑝𝑅)
(Δϴ0.5)
0
54.60
54.40
5.10
1.35
85.00
3.38 62.96
1
55.00
54.90
5.60
1.85
93.33
3.03 50.45
2
55.90
55.50
6.50
2.29
108.33
2.84 47.31
3
56.70
56.35
7.30
3.30
121.67
2.21 36.87
6
57.50
57.05
8.10
4.00
135.00
2.03 33.75
10
58.80
58.10
9.40
5.05
156.67
1.86 31.02
A realization upon Table 1 that the shifts of resonance angle toward greater value on the growth of the number of graphene layers [49]. Consequently, This rightward shift of resonance angle associated with an enlarged width of the SPR curve resembles the drastic fluctuation in the SPR motion induced by the coating of graphene on metal [48, 50]. The drastic fluctuation in the curve finally turns into the up-gradation of sensitivity [24]. This exalt sensitivity obtains on account of the switching of θSPR, which is caused by the absorption capability of biomolecules [39], powerful fluorescence appeasing capability of graphene [40]. Additionally, Table 1 represents the evaluated outcomes for SNR and Q.F for conventional as well as graphene-based raised SPR biosensor. The close observation of Table 1 pointed out that the gradual decrease has happened in SNR and Q. F. owing to the increased layer of graphene in the sensor.
200
4
150
3
100
2
50
0
1
2
3
4
5
6
7
8
9
Signal to Noise Ratio (SNR)
Sensitivity(S) [deg/RIU]
Sensitivity versus Graphene Layer SNR versus Graphene Layer
1 10
No. of Graphene Layers (L) 160
70
140
60
120
50
100
40
80
0
1
2
3
4
5
6
7
8
9
Quality Factor (QF)[/RIU]
Sensitivity(S) [deg/RIU]
Sensitivity versus Graphene Layer QF versus Graphene Layer
30 10
No. of Graphene Layers (L)
Fig. 6. Change of (a) the sensitivity and SNR, (b) the sensitivity and Q.F as the function of the graphene layers As a fourth factor, we evaluate the optimal number of graphene layers which secure the foremost sensitivity and enhance the SNR and QF of the raised biosensor. The number of graphene layers gradually has changed from 1 to 10. As shown in Fig. 6(a), the improved sensitivity as well as SNR can be obtained at a stage of graphene layer number is between 3 to 4 and in Fig. 4(b), the improved sensitivity as well as QF can be availed at the stage of the graphene layer number is between 2 to 3. Therefore, we choose the optimum graphene layer as 3 in the proposed SPR biosensor. Howsoever, the sensor structure with 3 graphene layers is still adoptable for DNA hybridization identification. Table.2. Comparison of change of SPR angle, sensitivity, SNR and QF with respect to design strategy among proposed sensor with other existing works References [56]
Layers Statistics Graphene layer with chromium substrate
Change of SPR
Sensitivit
angle (Δϴ𝑠𝑝𝑅)
y (S)
---
68.03
SNR
Q.F
---
9.691
[24]
Mono layer of
6.15
87.8
1.28
17.56
5.886
84.09
0.82
11.71
1:50
95.71
1.763
25.19
1.00
200
0.7692
11.51
7.30
121.67
2.21
36.87
graphene and MoS2 [57]
Mono ayer of graphene-MoS2 with TiO2 - SiO2
[58]
A monolayer of graphene and Tungsten Disulfide (WS2)
[59]
Six MoS2 and mono graphene layers
proposed
Tri layers of graphene
TM polarization the electric field produced due to the SPW along x-direction is specified in ref. [21] as: jk spw cosin z jk spw sin in x
E x E0 cos in e
k k 0 nk k 2c0 where spw , is the wave vector of SPW in layered media, 0 vector and E0 is the magnitude of the electric field.
(14)
(0 0 )633
is a free-space wave
Further once more, in this segment, we used to evaluate electric field distribution by organizing the finite difference time domain (FDTD) procedure utilizing commercial software Opti FDTD multiphysics software. The FDTD is an amazing technique to explain Maxwell's equations in a nano film layer (Au-50 nm) by utilizing the YEE-algorithms. The FDTD method is a more feasible than others, for example, multiple-multiple or Green’s dynamic method in resolving Maxwell’s equations for complex geometries and dispersive media, for example, gold and silver [43]. The simulation was completed with the planer wave with the center wavelength of 633 nm. Surface plasmon polarition (SPP) excitation is performed utilizing angular interrogation method. The perfectly matched layer (PML) boundary condition was utilized in such a way, that waves go into the layers with generating minimum reflections (Rmin) [44]. Also, transmittance electric field intensity was accounted for utilizing DFT transmission monitor at 520 nm away from Au/graphene interface. The electric field distribution of the proposed biosensor structure with 10 graphene layers have been explained. The structure is resolved by subcell PML in all direction. The time steps and the FDTD spatial mesh are set to ∆t=∆/4C0 and ∆=λ/10, individually, to fulfill CFL stability criterion, where λ is the wavelength equivalents to 633 nm. Here, ∆x= ∆y= ∆z= ∆ = 63.3 nm. At last, the computational space is finished by a 15 nm perfectly matched layer (PML) cells according to the Fig 7(a). The outcome is acquired to run the simulation during 50,000 time steps so as to arrive field components at steady state.
DFT Monitor (Reflectance)
SF11 Prism (180 nm)
z
DFT Monitor (Transmittance)
y x
PML (15 nm)
PML (15 nm)
Planer Wave (633nm)
Gold (50 nm)
(a)
Graphene (3.4 nm)
PML (15 nm)
Sensing Layer (520 nm)
PML (15 nm)
1
(a) (b) Electric Field Intensity (|E 2| / |E0 2 |) [a.u]
0.8
0.2
0
0
Au (50nm)
Prism (SF11)
0.4
Graphene (3.40 nm)
0.6
Sensing medium (250 nm)
with Graphene without Graphene
300 350 400 450 250 100 50 150 200 Distance perpendicular to the interface [nm]
Fig. 7: (a) 2D Yee’s cell for the electric field distribution along x direction, (b) Normalized electric field intensity with graphene layers (solid black line) and without graphene layers (dash red line).
In Fig. 7 (b), it is seen that the normalized electric field can secure higher absorption of light to have huge SPW excitation and the numerical estimations of the electric field distribution in the design with graphene is more noteworthy. Thus, SPW excitations are more consolidated for the arrangement with graphene. The expansion of graphene over the gold layer can influence the field intensity which causes sensitivity enhancement by expanding the mobility of electrons. The electric field intensity ways to deal with its maximum value when the reflectance curve demonstrates the minimum value of reflectivity. For this situation, the most noteworthy excitation of SPs can happen. As can be obviously observed from Fig. 7 , the graphene layer enhances the field intensity and shows a peak as graphene additionally reflects remarkable electrical and optical properties and delivers high enthusiasm as a 2D material.
Conclusion In this presented work, a graphene tri layers based surface plasmon resonance (SPR) refractive index sensor is illustrated. The angular interrogation scheme has been utilized to analyze the reflection from the proposed sensor consisted of prism (SF11 glass), Gold (Au), graphene-based configuration. The effect of adding graphene layer has been investigated on factors of sensor sensitivity (S), signal to noise ratio (SNR), quality factor (QF), after then the number of graphene layers is optimized to three layers. Further, the SPR curves have been plotted and a comparison of sensor sensitivity, signal to noise ratio, quality factors have been made among the existing works at this optimal thickness. From the obtained results, we have observed the sensitivity of the optimized number of graphene layers based sensors is enriched to an excellent value of 121.67 deg-RIU-1 with improved SNR of 2.21and QF of 36.87 RIU-1 respect conventional SPR sensor. Afterward, the effect of electric field allocation on incorporating the graphene layer is made an analyzation utilizing the finite difference time domain (FDTD) mean with the help of the Opti FDTD solution commercial environment.
Acknowledgment: This work was supported by the Deanship of the Scientific Research (DSR), King Abdulaziz University Jeddah, under grant No. (DF-422-135-1441). The authors , therefore, gratefully acknowledge DSR technical and financial support.
References [1] K. Tamersit, F. Djeffal, Double-gate graphene nanoribbon field-effect transistor for DNA and gas sensing applications: simulation study and sensitivity analysis, IEEE Sens. J. 16(11), (2016) 4180-4191. [2] J. Homola, M. Piliarik, Surface Plasmon Resonance Based Sensors. Vol. 4 Ch. 2, 46–47 (Springer, 2006). [3] Q. Ouyang, S. Zeng, L. Jiang, L. Hong, G. Xu, X.-Q. Dinh, J. Qian, S. He, J. Qu, P. Coquet, K.-T. Yong, Sensitivity enhancement of transition metal dichalcogenides/silicon nanostructure-based surface plasmon resonance biosensor, Sci. Rep. 6 (2016) 28190.
[4] S. Zeng, D. Baillargeat, H.P. Ho, K.T. Yong, Nanomaterials enhanced surface plasmon resonance for biological and chemical sensing applications. Chem. Soc. Rev. 43 (2014) 3426-3452. [5] L. Xia, S. Yin, H. Gao, Q. Deng, C. Du, Sensitivity enhancement for surface plasmon resonance imaging biosensor by utilizing gold–silver bimetallicfilm configuration, Plasmonics 6 (2011) 245–250. [6] Priyabrata Pattnaik, Surface plasmon resonance, Appl. Biochem. Biotechnol. 126 (2) (2005) 79–92. [7] J. Nico, Marcel JE. Fischer, Surface plasmon resonance: a general introduction, Surface Plasmon Resonance, Humana Press, 2010, pp. 1–14. [8] Anna J. Tudos, BM Schasfoort Richard, Introduction to surface plasmon resonance, Handbook of Surface Plasmon Resonance, 2008, pp. 1–14. [9] Bo Liedberg, Claes Nylander, Ingemar Lunström, Surface plasmon resonance for gas detection and biosensing, Sensor. Actuator. 4 (1983) 299–304. [10] Fang-Fang Ren, Kah-Wee Ang, Junfeng Song, Qing Fang, Mingbin Yu, GuoQiang Lo, Dim-Lee Kwong, Surface plasmon enhanced responsivity in a waveguided germanium metal-semiconductor-metal photodetector, Appl. Phys. Lett. 97 (9) (2010) 091102. [11] Sachin K. Srivastava, Vikas Arora, Sameer Sapra, Banshi D. Gupta, Localized surface plasmon resonancebasedfiber optic U-shaped biosensor for the detection of blood glucose, Plasmonics 7 (2) (2012) 261–268. [12] Md. Biplob Hossain, Tarik Bin Abdul Akib, Lway Faisal Abdulrazak, Md. Masud Rana,“Numerical modeling of graphene-coated fiber optic surface plasmon resonance biosensor for BRCA1 and BRCA2 genetic breast cancer detection,”Opt. Eng.58(3), 037104 (2019), doi: 10.1117/1.OE.58.3.037104. [13] Yu A. Akimov, W.S. Koh, Resonant and non-resonant plasmonic nanoparticle enhancement for thin-film silicon solar cells, Nanotechnology 21 (23) (2010) 235201. [14] Erwin Kretschmann, Heinz Raether, Radiative decay of non radiative surface plasmons excited by light, Z. Naturforsch. 23 (12) (1968) 2135–2136. [15] Sandrine Filion-Côté, Philip JR. Roche, Amir M. Foudeh, Maryam Tabrizian, Andrew G. Kirk, Design and analysis of a spectro-angular surface plasmon resonance biosensor operating in the visible spectrum, Rev. Sci. Instrum. 85 (9) (2014) 093107. [16] Md. Biplob Hossain, Mehedi Hassan, Lway Faisal Abdulrazak, Md. Masud Rana, Md. Mohaiminul Islam, M. Saifur Rahman, Graphene-MoS2-Au-TiO2-SiO2 Hybrid SPR Biosensor for Formalin Detection: Numerical Analysis and Development, Advanced Materials Letters, 2019, 10. [17] Zhitao Lin, Leyong Jiang, Leiming Wu, Jun Guo, Xiaoyu Dai, Yuanjiang Xiang, Dianyuan Fan, Tuning and sensitivity enhancement of surface plasmon resonance biosensor with graphene covered Au-MoS2-Au Films, IEEE Photon. J. 8 (6) (2016) 1–8. [18] Md Biplob Hossain, Md Masud Rana, Lway Faisal Abdulrazak, Saikat Mitra, Mostafizur Rahman, Graphene-MoS2 with TiO2- SiO2layers based surface plasmon resonance biosensor: Numerical development for formalin detection, Biochemistry and Biophysics Reports 18 (2019) 100639. [19] Kandammathe Valiyaveedu Sreekanth, Shuwen Zeng, Ken-Tye Yong, Ting Yu, Sensitivity enhanced biosensor using graphene-based one-dimensional photonic crystal, Sensor. Actuator. B Chem. 182 (2013) 424– 428. [20] Rahman, M.S., Noor, S.S., Anower, M.S., Abdulrazak, L.F., Rahman, M.M. and Rikta, K.A. (2019) Design and Numerical Analysis of a Graphene-Coated Fi-ber-Optic SPR Biosensor Using Tungsten Disulfide. Photonics and Nanostruc-tures-Fundamentals and Applications, 33, 29-35. https://doi.org/10.1016/j.photonics.2018.11.005 [21] I. Pockrand, J.D. Swalen, J.G. Gordon II, M.R. Philpott, Surface plasmon spectroscopy of organic monolayer assemblies, Surf. Sci. 74 (1) (1978) 237–244. [22] I. Pockrand, Surface plasma oscillations at silver surfaces with thin transparent and absorbing coatings, Surf. Sci. 72 (3) (1978) 577–588.
[23] Otto S. Wolfbeis, Bernhard M. Weidgans, Fiber optic chemical sensors and biosensors: a view back, Optical Chemical Sensors, Springer, Dordrecht, 2006, pp. 17–44. [24] M. Saifur Rahman, Md Shamim Anower, Md Rabiul Hasan, Md Biplob Hossain, Md Ismail Haque, Design and numerical analysis of highly sensitive Au-MoS2-graphene based hybrid surface plasmon resonance biosensor, Optic Commun. 396 (2017) 36–43. [25] A.K. Mishra, S.K. Mishra, Eur. Phys. Lett. (2015). [26] M. Saifur Rahman, Md. Shamim Anower, Lway Faisal Abdulrazak. (2019) Mod-eling of a Fiber Optic SPR Biosensor Employing Tin Selenide (SnSe) Allotropes. Results in Physics, 15, Article ID: 102623. https://doi.org/10.1016/j.rinp.2019.102623 [27] Zao Yi, et. al., Tunable Graphene-based Plasmonic Perfect Metamaterial Absorber in the THz Region, Micromachines 2019, 10(3), 194. [28] Chunlian Cen, et. al., Terahertz wideband perfect absorber based on open loop with cross nested structure. Results in Physics 15 (2019) 102603 [29] C. Cen, et. al., Theoretical design of a triple-band perfect metamaterial absorber in the THz frequency range. Results in Physics 2019, 14, 102463. [30] M.B. Hossain, S. Muktadhir, Optik 127 (2016) 5841–5851. [31] MB Hossain, MS Muktadhir, MM Rana "Modeling graphene macroscopic and microscopic conductivity in the sub-cell FDTD method" International Conference on Electrical & Electronic Engineering (ICEEE), Rajshahi, Bangladesh, (2015) [32] C. Cen, et. al., Numerical investigation of a tunable dual-band metamaterial perfect absorber consisting of two-intersecting graphene nanorings arrays. Physics Letters A 2019, 383(24), 3030–3035 [33] C. Cen, et. al., Dual-Band Plasmonic Perfect Absorber Based on Graphene Metamaterials for Refractive Index Sensing Application. Micromachines 2019, 10, 443. [34] L. Wu, et. al., Highly sensitive graphene biosensors based on surface plasmon resonance, Opt. Express 18 (14) (2010) 14395–14400 [35] MM Rana, MB Hossain, MR Islam, YG Guo "Surface plasmon polariton propagation modeling for graphene parallel pair sheets using FDTD" Applied Superconductivity and Electromagnetic Devices (ASEMD), Shanghai, China, (2015) [36] Leiming Wu, Jun Guo, Xiaoyu Dai, Yuanjiang Xiang, Dianyuan Fan, Sensitivity Enhanced by MoS2– Graphene Hybrid Structure in Guided-Wave Surface Plasmon Resonance Biosensor Plasmonics, 2018, 13(1), 281–285. [37] MB Hossain, MM Rana, "An effective compact-FDTD wideband modeling of graphene conductivity", Int. conf. Electrical Engineering and Information Communication Technology (ICEEICT), Dhaka, Bangladesh (2015) [38] KN Shushama, MM Rana, R Inum, MB Hossain "Graphene coated fiber optic surface plasmon resonance biosensor for the DNA hybridization detection: Simulation analysis" Optics Communications, 383, pp. 186-190, (2017) [39] Leiming Wu, Yue Jia, Leyong Jiang, Jun Guo, Xiaoyu Dai, Yuanjiang Xian, and Dianyuan Fan, Sensitivity improved SPR biosensor based on the MoS2/graphene-aluminum hybrid structureJournal of Lightwave Technology, 2017, 35(1), 82-87.
[40] Leiming Wu Jun Guo Qingkai Wang Shunbin Lu, Xiaoyu Dai Yuanjiang Xiang Dianyuan FanSensitivity enhancement by using few-layer black phosphorus-graphene/TMDCs heterostructure in surface plasmon resonance biochemical sensorSensors and Actuators B: chemical, 2017, 249, 542-548. [41] M. B. Hossain, M. M. Rana, L. F. Abdulrazak, S. Mitra, and M. Rahman, “Design and analysis of grapheneMoS2 hybrid layer based SPR biosensor with TiO2-SiO2 nano film for formalin detection: numerical approach”, Optical and Quantum Electronics, 2019, 51(6): 195–207. [42] M. S. Rahman, M. S. Anower, and L. F. Abdulrazak, “Utilization of a phosphorene-graphene/TMDC heterostructure in a surface plasmon resonance-based fiber optic biosensor,” Photonics and NanostructuresFundamentals and Applications, 2019, 35(3): 100711. [43] M. B. Hossain, M. M. Islam, L. F. Abdulrazak, M. M. Rana, T. B. A. Akib, and M Hassan, “Graphenecoated optical fiber SPR biosensor for BRCA1 and BRCA2 breast cancer biomarker detection: a numerical design-based analysis,” Photonic Sensors, 2019, 9(4): 1–13. [44] M. O’Brien, K. Lee, R. Morrish, N.C. Berner, N. McEvoy, C.A. Wolden, G.S. Duesberg, Plasma assisted synthesis of WS2 for gas sensing applications, Chem. Phys. Lett. 615 (2014) 6–10. [45] Hossain, B., Tasnim, T., Abdulrazak, L.F., Rana, M. and Islam, R. (2019) A Nu-merical Approach to Design the Kretschmann Configuration Based Refractive Index Graphene-MoS2 Hybrid Layers with TiO2-SiO2 Nano for Formalin Detec-tion. Photonic Sensors, 1-13. https://doi.org/10.1007/s13320-019-0566-5 [46] J.B. Maurya, Y.K. Prajapati, V. Singh, J.P. Saini, R. Tripathi, Performance of graphene–MoS2 based surface plasmon resonance sensor using silicon layer, Opt. Quantum Electron. 47 (2015) 3599–3611. [47] M.S. Rahman, MS. Anower, M.K. Rahman, M.R.Hasan, M.B. Hossain, M.I. Haque, Modeling of highly sensitive MoS2-graphene hybrid based fiber optic SPR biosensor for sensing dna hybridization, Optik 140 (2017) 989–997 [48] M.B. Hossain, M. M. Rana,"DNA hybridization detection based on resonance frequency readout in graphene on Au SPR biosensor, Journal of sensors (2016) [49] M.B. Hossain, M. M. Rana, Graphene coated high sensitive surface plasmon resonance biosensor for sensing DNA hybridization, Sens. Lett. 14, (2016) 1–8. [50] KN Shushama, MM Rana, R Inum, MB Hossain, "Sensitivity enhancement of graphene coated surface plasmon resonance biosensor" Optical and Quantum Electronics 49 (11), 381, (2017) [51] MS Rahman, MB Hossain, MM Rana "Sensitivity enhancement of porous silicon based SPR sensor using graphene-M0S2 hybrid structure" International conf. on Electrical, Computer & Telecommunication Engineering (ICECTE), Dhaka, Bangladesh, (2015) [52] M. S. Rahman, M. S. Anower, L. F. Abdulrazak, and M. M. Rahman, “Modeling of a fiber-optic surface plasmon resonance biosensor employing phosphorene for sensing applications,” Optical Engineering, 2019, 58 (3): 037103. [53] L. Diéguez, N. Darwish, M. Mir, E. Martínez, M. Moreno, and J. Samitier, “Effect of the Refractive Index of Buffer Solutions in Evanescent Optical Biosensors,” Oct-2009. [54] Pradeep Kumar Maharana, Rajan Jha" Chalcogenide prism and graphene multilayer based surface plasmon resonance affinity biosensor for high performance", Sensors and Actuators B: chemical, 169 (2012) 161–166 [55] M. B. Hossain, M. M. R. Khan, M. S. Rahman, S. S. B. Badrudduza, M. M. Sabiha, et al., “GrapheneMoS2-Au-TiO2-SiO2 hybrid SPR biosensor: A new window for formalin detection,” Journal of Materials and Applications, 2019, 8(2): 51–58. [56] A. Verma, A. Prakash, R. Tripathi, Sensitivity enhancement of surface plasmon resonance biosensor using graphene and air gap, Opt. Commun. 357 (2015), 106–112 [57] Maurya, J. B.; Prajapati, Y.K.; Singh, V.; Saini, J. P., Sensitivity enhancement of surface plasmon resonance sensor based on graphene–MoS2 hybrid structure with TiO2–SiO2 composite layer. Appl Phys A, 2015, 121, 525.
[58] M. Saifur Rahmana, Md.Rabiul Hasan, Khaleda Akter Rikta, M.S. Anower, ‘A novel graphene coated surface plasmon resonance biosensor with tungsten disulfide (WS2) for sensing DNA hybridization’, Optical Materials 75 (2018) 567-573. [59] Hamid Vahed, Cyrus NadriSensitivity enhancement of SPR optical biosensor based on Graphene–MoS2 structure with nanocomposite layer, Optical Materials 88 (2019) 161–166.
High Performance Refractive Index SPR Sensor Modeling Employing Graphene Tri Sheets Highlights To illustrate a surface plasmon resonance (SPR) sensor based on graphene exciting configuration consists of Gold (Au), graphene, prism (SF11 glass) and sensing medium. To utilize angular interrogation method basically for the inspection of reflected light from the sensor for the enhancement of sensor sensitivity (S), signal to noise ratio (SNR), quality factor (QF). To optimize graphene layers to three. Thereafter, at these optimum layers, the SPR curves are plotted and comparison of sensor sensitivity, signal to noise ratio, quality factor is made among the existing works. It is observed that the sensitivity of the optimized graphene layers based sensor is enhanced to excellent value of 121.67 deg-RIU-1 with improved SNR of 2.21and QF of 36.87 RIU-1 respect conventional SPR sensor. The effect of electric field distribution on inserting graphene layer is analyzed incorporating the finite difference time domain (FDTD) technique by applying Opti FDTD solution multiphysics commercial software.
High Performance Refractive Index SPR Sensor Modeling Employing Graphene Tri Sheets This is to inform you that the revised research manuscript entitled above is submitted to your journal for considering to publish in your regular issue and this article is contributed by following authors:
Md. Biplob Hossain1*, Ibrahim Mustafa Mehedi2, M. Moznuzzaman1, Lway Faisal Abdulrazak3, Md. Amzad Hossain1 1Department
of Electrical and Electronic Engineering Jashore University of Science & Technology, Jashore, Bangladesh 2Center
Excellence in Intelligent Engineering Systems (CEIES) Electrical and Computer Engineering Department (ECE) King Abdulaziz University, Jeddah, Saudi Arabia 3 Department
of Computer Science Cihan University Slemani, Sulaimaniya, Iraq. Email: [email protected], [email protected], [email protected], [email protected], [email protected], * Corresponding Author: Dept. of Electrical and Electronic Engineering Jashore University of Science & Technology Jashore, Bangladesh [email protected]
Competing Interest All authors declare that they have no competing interests.
S2211-3797(19)32748-2 https://doi.org/10.1016/j.rinp.2019.102719 RINP 102719
To appear in:
Results in Physics
Received Date: Revised Date: Accepted Date:
12 September 2019 1 October 2019 1 October 2019
Please cite this article as: Biplob Hossain, Md., Mustafa Mehedi, I., Moznuzzaman, M., Faisal Abdulrazak, L., Amzad Hossain, Md., High Performance Refractive Index SPR Sensor Modeling Employing Graphene Tri Sheets, Results in Physics (2019), doi: https://doi.org/10.1016/j.rinp.2019.102719
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
© 2019 The Authors. Published by Elsevier B.V.
High Performance Refractive Index SPR Sensor Modeling Employing Graphene Tri Sheets Md. Biplob Hossain1*, Ibrahim Mustafa Mehedi2, M. Moznuzzaman1, Lway Faisal Abdulrazak3, Md. Amzad Hossain1 1Department
of Electrical and Electronic Engineering Jashore University of Science & Technology, Jashore, Bangladesh 2Center
Excellence in Intelligent Engineering Systems (CEIES) Electrical and Computer Engineering Department (ECE) King Abdulaziz University, Jeddah, Saudi Arabia 3 Department of Computer Science Cihan University Slemani, Sulaimaniya, Iraq.
Email: [email protected], [email protected], [email protected], [email protected], [email protected] * Corresponding Author: Dept. of Electrical and Electronic Engineering Jashore University of Science & Technology Jashore, Bangladesh [email protected]
Abstract: This article illustrates a graphene tri sheets based surface plasmon resonance (SPR) biosensor. The exciting configuration consists of Gold (Au), graphene, prism (SF11 glass) and sensing medium. The angular interrogation scheme is basically utilized owing to inspect the light reflection from the sensor. For sake of the augmentation of sensor sensitivity (S), signal to noise ratio (SNR), quality factor (QF), first of all, the impact of adding graphene layer is investigated and then the number of graphene layers are optimized to tri layers. According to that tri sheets, the SPR curves are sketched and comparison of sensor sensitivity, SNR, the quality factor is made among the existing works. It is audited that an extraordinary improvement of sensitivity to 121.67° RIU-1. The most effective graphene layers states with improved SNR of 2.21and QF of 36.87 RIU-1 respect conventional SPR sensor. After then, the electric field intensity on implanting graphene sheet is analyzed by incorporating the finite difference time domain (FDTD) method by applying the Opti FDTD multiphysiscs commercial software environment. The proposed design bears the advantages of high sensitivity, QF and SNR comparing with the existing sensors along with simple stricture, no need of plasmonic coatings of other dielectrics, compactness, light weight, real time fabrication flexibility due to avoid multi materials optical structure. Keywords: ATR; Quality factor; signal to noise ratio: Sensitivity ; FDTD method; Graphene; SPR.
1. Introduction Surface plasmon resonance (SPR) technology-based biosensors have stretched out great eye as one of the prominent sensing technologies because of their hopeful applications in sundry venues such as detection of a biomolecule, pathological diagnostics, biochemical marking off, environmental trouble monitoring, etc.[1-3]. They have conducted a crucial indication in monitoring diversified interactions of biomolecules namely making bonds among the proteins and hybridization of DNA [4-5]. SPR, an optical spectacle, provides a label-free way of inspecting the interactions of binding between the analyte and biomolecule [6–9]. SPR has an augmentative interest in the various sectors of optoelectronics and optics. Besides that SPR is widely applied in the plasmonic detections [10], biomedical diagnosis [11], the light-emitting diode of organic materials [12], and optical solar cells [12-13], etc.
Surface Plasmons (SPs), materially are the charge density oscillations that are localized at the interfacing surface of a dielectric in any possible state either solid, gas or liquid and a metal (e.g. silver or gold) propagating on the interface [14]. The propagation of the SPs is very much dependent on the refractive index of the medium adjoining to the metal that shapes it a powerful tactic of tracking the changes in the refractive index of a sample for binding events and in this way, it becomes effective for biosensing applications [15]. When the settlement of a particular incident circumstance happens [16], surface plasmon wave (SPW) can get activated and the activation for SPR is basically guided by the prospect of the drastic dip in reflectance and a high numerical reflection [17]. The reflectance dip and the wave vector of SPR wave are the large-handed reactionaries to the changeability of the complex value of the refractive index (RI) of the metal ledge and the surroundings of the metal ledge, and their geometrical ground which depends on the excitation of the SPW [18]. Biosensors using the SP method possess rapid and extremely responsive to biomolecular detection [19] that makes it more convenient than fluorescence-based optical biosensors which require more time and have high molecular binding disorder [20]. Optical biosensors based on SPR technology have illustrious uses in biological and chemical detecting involving the measurings on the doping of an analyte a perplexing sample and the kinetics of biomolecular interactions [21-22]. Over the last several years, the architecture of SPR based biosensors have got thriving attention in the medical sector for diagnostic applications [23]. In very recent, the hybrid architecture SPR biosensors for medical diagnostics as well as optical interactions have a chemical action between adenine (A) and thymine (T) or between cytosine (C) and guanine (G) [24]. The attenuated total reflection (ATR) configured SPR biosensor renders in two modes of operation: Firstly, the angular investigation operating mode where the wavelength of the incident light is fixed, and the input entrance angle is changed and secondly the wavelength investigation operating mode where the entrance angle is fixed and the wavelength is changed [14]. Photonic crystal based Kretschmann [14] configuration SPR sensor in the angular interrogation scheme possesses numerous amenities over the prism coupled SPR sensor configuration in wavelength interrogation scheme [18]. Many researchers prefer the first scheme of operations because of its tightness, lightweight, billowy sensitivity and mechanical facility [25]. Consequently, this type of sensor gives the opportunity of being miniature and hence it facilitates the chemical or biological sensing applications [26]. Graphene is arranged like a honeycomb lattice and is of two-dimension graphite shows numerous properties namely low reluctance, superior carrier mobility, greater optical transparency, tenability, etc. [27-31]. The effectual excitement and propagation of surface plasmons with the graphene has been proved both experimentally and theoretically [28]. A large enhancement in the sensitivity of the SPR sensor become possible by using graphene as a detecting layer [26]. In Ref.[34], L. Wu, et. al, presented a highly sensitive SPR biosensor by using the graphene layer to enhance the sensitivity caused by the light absorbed by the graphene [35]. They reported, the sensitivity can be improved to 25% only using single graphene layer due to grapehe’s extraordinary optical absorption and plasmonic properties [34]. A higher optical absorption will lead to a significant effect of SPR signals [36-38]. In [36], Leiming Wu, et. al reported a SPR biosensor by using the MoS2–graphene hybrid structure to enhance the sensitivity to about 98.2% when the number of MoS2 layer is six. In literature [39], authors have also reported a SPR sensor based on MoS2–graphene hybrid structure with aluminum (Al) film in 2016. The performance of the biosensor can be enhanced by using this hybrid structure rather using only graphene or only MoS2 [40]. All of the design mentioned in this paragraph, were not show the effect of SNR and QF due to use hybrid structure. Because of adding different layers on metallic film, it increases undoubtly sensitivity but at the same time it reduces drastically SNR and QF along with increases fabrication complexity [12, 16, 41]. But a good sensor must have high sensitivity, SNR and QF as much as possible. So, till now,a newer approach which confirms very simple in structure along with high sensitivity, SNR and QF is still requird. In this article, we have used graphene tri sheets structure to confirm at a time, both high sensitivity, SNR & QF and simple optical structure. In this work, the SPR sensor with graphene tri layers as an plasmonic layer is excised widely for the detection of biomollecular hybridization. For the charged analytes graphene is awfully sensorial (ions, DNA, cells, etc.). As an electric field arises around the graphene dramatically, it becomes a model material for aristocratic performance sensors. The outcome of attaching graphene is researched and optimization is drawn to three graphene layers aiming to the enhancement of sensitivity (S), quality factor (QF) and signal to noise ratio (SNR). Hereafter, the SPR responses with the tri graphene layers are plotted and a comparison is drawn by sensitivity, signval to noise ratio, and quality factor among the existing deeds. Close observation is stretched out that the sensitivity of the sensor with optimized number layers of graphene is enhanced to a wishful value of 121.67 deg/RIU as well as with excellently improved SNR value of 2.21 and QF of 36.87 per RIU with respect to conventional SPR sensors. Finally, by efficiently incorporating the finite difference time domain (FDTD)
technique, the effect of insertion of the graphene ten layers on electric field distribution is analyzed with the help of a commercial Opti FDTD solution software.
2. Methodology 2.1. Frame Model of Proposed Sensor The proposed structure of SPR biosensor is fixed with four layers and the configuration is exhibited in Fig. 1. The entrance light is in the transverse magnetic (TM) polarization situation is one of the most significant criteria required for SPs excitation [25]. In the path of the incident, a polarizer is utilized to enliven the TM polarized light. As optical nonlinearity can be improved at low wavelength, the operating wavelength is chosen at 633 nm [42-44]. In all respects of the photon energy band, micro band optical change of state occurs because of the band shape of graphene [45], [46]. Consequently, the thorough sensitivity of the sensor is ameliorated with the small probable Kerr effect at the wavelength of 633 nm [47]. To design our proposed sensor in angle investigation scheme with Kretschmann layout, we availed the Fresnel ocular system which is smeared circumstantially in literature [43, 47, 24,48-51]. For providing additional momentum to the light, large wave vector photonic quartz required to be applied [2]. In order to meet up this criterion, we marked a prism with a high value of RI of (np) of 1.7786 such as SF11[47] and applied as a base layer. We specified a noble metal such as gold (nAu= 0.1838+i 3.4313, thickness, dAu =50 nm) layer as a second layer. The gold layer thickness is considered to 50 nm over the analysis to achieve superior quality factor and detection accuracy [24, 47]. Over and above, the SPR angle shows a fluctuating habit with thickness other than 50 nm that reveals trouble to search out a lasting sensing situation [25] because gold is marked as utmost compatible metal against to the corrosion and oxidation as well as excellent chemical fixity and greater optical responses [43, 47]. The resonant activation of photon and electron happens when the wavevector of the incident light stays imprisoned at the interface and declines in an exponential manner in the wry directions [43, 50]. The souse of the SPR is very responsive to the alteration in the complex RI of the metal ledge, contiguous to the dielectric medium and structural shapes [25, 43], which outcome strengthened sensitivity [25]. For the sake of accelerating the sensitivity change with standard detection accuracy (DA), we specified graphene as a third smear that has a highly complex RI ( ng=3.0 + i 1.1487 [50, 51]) as well as superior carrier mobility, greater optical transparency, extraordinary mechanical flexibility, mechanical potency [38-41], little resistivity, attunable conductivity [38]. Till the last, phosphate buffer saline (PBS) fluid with RI nb =1.34 is marked as an empty responding dielectric mean that pays the opportunity of higher adsorption of biomolecules [52, 53].
Fig 1. Schematic representation of a 4-smeared model of SPR biosensor The graphene-based biosensor adsorbs ssDNA biomolecules and produces a native increment in the RI at the surface of Graphene-Au [49]. In DNA hybridization as depicted in Fig. 2, when two single-stranded (ssDNA) DNA, representing the probe and target, are combined at the same place and form a double-stranded (dsDNA) helix shape which is demarked as complementary DNA mixing event. In this raised model, it interprets the characterization analytically of the sensor sothat perceiving of the hybridization of target DNAs to the probe DNAs which are pre-immobilized on graphene are made effectively. The SPR process for the proposed model is also capable of comparing single-base mismatched DNA events with complementary events.
single-strand DNA(Probe) p
p
5’
4 3 S 2 1
4 3 S 2 1
5
p
p 4 3 S 2 1
5
T
G
p 4 3 S 2 1
5
T
2 1 S 3 4
p
p
2 1 S 3 4
2 1 S 3 4
5
5 p
p
2 1 S 3 4
4 3 S 2 1
5
2 1 S 3 4
2 1 S 3 4
5 p
p
5
C
C 5
3’
p 4 3 S 2 1
5
T
G
G 5
p
p 4 3 S 2 1
5
T
C
C 3’
p 4 3 S 2 1
5
G 2 1 S 3 4
5
5 p
p
2 1 S 3 4
5
5’ p
Complementary DNA(target) (a) Perfectly Matched (dsDNA) Hybridization Event
single strand DNA(Probe) p
p
5’
4 3 S 2 1
4 3 S 2 1
5
4 3 S 2 1
5
T
G
p
p 5
T
p
2 1 S 3 4
p 4 3 S 2 1
5
p
p 4 3 S 2 1
5
T
C
C 3’
p 4 3 S 2 1
4 3 S 2 1
5
3’
5
T
G
G 5 p
2 1 S 3 4
2 1 S 3 4
5
5 p
p
2 1 S 3 4
2 1 S 3 4
5
p
C
p
Mismatched DNA(target)
2 1 S 3 4
5
2 1 S 3 4
2 1 3 S4
5
5 p
5’
p 2 1 S 3 4
5
5
p
p
(b) Mismatched DNA SNP Event
Fig 2. (a) Perfectly Matched ssDNA and C-DNA hybridization happened (Nitrogen base Adenine-Thymine relation with a di-hydrogen connection, Guanine-Cytosine (G-C) relation with a tri-hydrogen connection (b) Mismatched ssDNA and single based mismatched hybridization happened.
2.2 Mathematical Prototype for Proposed Sensor A monochromatic light source emits 633nm wavelength light, and the respective data are taken out in a spectrometer associated with a computer. At this time, the incident wave propagates continuously together through the x-direction as exhibited in Fig 1, with wave vector of the following equation [48,49]:
klight 2 633 n p sin in
(1)
Equation (1) represents the ingredient of light propagating parallel to the gold surface. As the outright entrance of p-polarized light has a relatively small wave vector, it becomes unable to stimulate SPW at the metaldielectric. Hence we need to incite light with a considerable incident angle. Here, θin represents the incident angle whereas np represents the RI of the prism. A fluctuation of molecules concentration in the dielectric sensing layer will create a little alteration in the RI close to the interface of plasmonic metal. Eventually, this alteration of RI will make a change in wavevector of the surface plasmons (KSPW), which may be determined by a process named attenuated total reflection (ATR). A simple description of SPW is given in Equation (2), where nAu denotes the RI of Au and the RI of graphene is denoted by ng [49,50]: k SPW
2
n 2Au n g2
633
n 2Au n g2
(2)
The majority of SPR applications connect with the real RI changes due to chemical or biochemical action [43] and therefore, Equation (3) is formed by considering real quantities only. If the wavevector of the incident light equals that of the SPW [54], resonated exhilaration of photon-electron recombining happens, which creates a shift of incident angle. If the wavevector of the incident light equals that of the SPW [54], resonated exhilaration of photon-electron recombining happens, which creates a shift of incident angle. The graphical representation of the reflectance with respect to the incident angle and also the plotting of the reflectance with respect to wavelength are celebrated as SPR curve [49, 55] and the spectrum of reflectance points out an immersion at the state of resonance [43].
This certain incident angle at which represents[48,49], as:
resonance occurred is acquainted as
SPR a sin
SPR angle and equation (3)
2 n s2 n Au 2 n 2p ( n Au n s2 )
(3)
The incident light generates an evanescent wave when passes through a prism and it is reflected from the prismgold adjacent surface. The expression for the intensity of reflection for p-polarized light is given below [24, 43, 47, 50]: Rp=|rp|2
(4)
Where,
rp
( F11 F12 n N )n1 ( F21 F22 n N ) ( F11 F12 n N )n1 ( F21 F22 n N )
(5) Through equation (7), F is destined as [43] 41 cos k Fij k 2 ink sin k
i sin k nk cos k
F11 F 21 ij
F12 F22
(6)
An explanation of the transverse RI nk, for the respective kth layer is paraded by the kinship [24]: 1/ 2
k (n p sin in ) 2 k nk cos k k2 k Correspondingly, the arbitrary phase constant βk for kth layer is also paraded by the kinship [24]: k
2
nk cos k ( z k z k 1 )
2
d k k (n p sin in ) 2
(7)
(8)
Suitably, the wave impedance of kth layer prevailed by zk [48]: zk
klight nk cos k
(9)
(2c / 633 ) k 2
Finally, the angle of entrance θk for kth layer can be represented in the following manner [48]: k a cos 1 (nk 1 / nk ) sin 2 in
(10)
Here, ϵk conveys the permittivity value for the kth layer and dk is the depth of kth layer (e,g, the layer thickness of graphene dg=L×0.34 nm, where L imparts layer number of graphene) respectively. The parameters signifying the performance of SPR sensors are mainly evaluated on the ground of its sensitivity, quality factor, and detection accuracy. The ratio of variation of SPR angle (ΔθSPR) to the variation of RI (ΔnS) is celebrated as sensitivity (S) whose unit is revealed as deg/RIU and mathematically can be assigned as [24,43,47]: SPR ; deg/RIU (11) S ns
Another but the highest significant parameter is signal to noise ratio (SNR) which is familiar with the name of detection accuracy can be ascertained from the SPR curve using the is given relation [47]. SPR ; dimensionless (12) SNR 0.5 Where Δθ0.5 represents the spectral width for 50% reflectivity of the SPR curve. The quality factor is adherent both on the spectral width and the sensitivity which can be represented as [47];
Q.F
SPR ; RIU-1 nS 0.5
(13)
Sensors that possess simultaneously exalted detection accuracy, superior sensitivity and improved quality factor are signified as a good sensor [46].
3. Numerical Results and Discussions: The performance is explained by displaying the reflectance–angle of the incident landmark of the SPR sensor prior to the addition of a probe-DNA molecule (open sensor, present only PBS solution), as shown in Fig. 3. In Fig. 3, with the increment of RI of the sample medium the angle of resonance, also increases. The RI of the sample medium has a momentous influence on the reflectance and the SPR curve [12, 43]. To look into the way by which SPR angle shifts with the shifts of the RI of the sample solution, we have enumerated several SPR curves for different refractive indexes keeping the wavelength fixed value of 633 nm. The outcomes are in Fig. 3, is developed by using equation (3) and (4). Here, we present the variation of the RI with the change in dn concentration; this relation can be expressed as reported in [12,16, 55, 58] as ncom n prim ca where ca is the dc concentration of adsorbed molecules, nprim is the refractive index of PBS, and and dn is the rate of increase in dc RI because of adsorbate immobilization. Here the considered rate of increasing parameter value dn 0.182 dc
cm3/gm as in standard cases [53,55,58]. The addition of a probe changes the refractive index of the sensing dielectric, leading to the electron-rich molecules such as DNA molecules, shifting the SPR angle rightward. 100
Reflactance (%)
80
60
40
20
0 50
1.33 1.34 1.35 1.36 1.37 1.38 1.39
55
60
65
Incidence Angle (Deg) Fig. 3: The reflection intensity spectra with the various SRI. Inset: the relatedness between reflectance and resonance angle. SPR angle shifts rightward because of the increment of RI.
At first, we consider the payoff of the insertion of the layers of graphene, which alters the refractive index of the sample dielectric [43], leading to the rise of biomolecular concentration increases the SPR angle. The number of graphene layers has a momentous impact in enhancing the sensitivity of this promised SPR biosensor. Consequently, we look at the fluctuation in the incident angle with respect to the sensing layer refractive index for different graphene layers according to the equation (3) in Fig. 4. Fig. 4, exhibits the fluctuation of the refractive index with the change of incident angle in the case of graphene as well as without graphene layers (L=1, 2,3,-----10). According to Fig. 4, increasing the number of graphene layers increases the resonance angle [24,47]. So, the proposed SPR optical biosensor’s sensitivity enhances with graphene layers.
58.5
Incident Angle (θ)
[Deg.]
58 57.5 -
Conventional Conventional with single Graphene Sheet Conventional with three Graphene Sheet Conventional with six Graphene Sheet Conventional with nine Graphene Sheet
57 -
Conventional with ten Graphene Sheet
56.5 56 55.5 55 54.5 54 1.32 1.33
1.34
1.35
1.36
1.37
1.39
1.38
Refractive index (RI)
1.40
1.41
[RIU]
Fig 4. A graphical presentation of SPR angle vs. Refractive Index for different structures.
As a second factor, we determine how SPR angle shifts with the addition of graphene layers, we have enumerated SPR curves for several layers of graphene at a constant wavelength of 633 nm after the addition of 1000 nM probe-DNA molecules [47-50] (sensor, present both PBS solution and probe-DNA). The results are in Fig. 5. The momentous rightward shift of the SPR curve is a confession sign of proper orientation of generic mutated sequence interaction with probe-DNAs, as well as that clarifies the detection of DNA hybridization [4350]. It is due to the number of charge changes with the introduction of electron-rich DNA molecules on the surface of graphene, which motivates a variation in the values of propagation constant [43]. As, the adsorption of the biomolecules near the vicinity of the graphene layer, finally a variation in the SPR angle is happened as following the equation (3). From Fig. 5, the shifting of the SPR angle in rightward is observed when graphene is affixed with Au as BRE. Again, applying a single graphene layer SPR angle 54.60 degrees has been also reported and for using ten graphene layers (L=10), an SPR angle of 58.80 degrees has been obtained. Au/N*BP
100
Reflectance (%)
80 L=0 N=1 L=1 N=2 L=2 N=4 L=3 N=6 L=6 N=8 L=10 N=10
60
40
20
0 50
55
60
65
Incidence Angle (Deg) Fig.5. Graph of SPR conventional sensor (L=0) and for varied graphene layers based sensors prior to the adsorption of molecules at angular investigation scheme λ= 633 nm. In addition, from the reflectance curve (Fig. 5), it is appeared wider and shallower as the increase of graphene layers.
Since the number of graphene layer changes, the wave vector of the plasmon wave shift according to
equation (2) due to which the resonance condition satisfied at different incident angle [54]. The wave vector shift is due to the enlargement of the SP field into graphene layer with an other propagation velocity of SP waves smaller than in the sensing layer that leads to drop in the propagation velocity SP wave and eventually results in broaden SPR curve [54]. As a result, SPs become dropped. Thus, on increasing number of graphene layer, damping increases in SPs. Since spectral width (some times called, Δθ0.5,= FWHM (full width at half maximum)) is a linear function of damping, so spectral width (broadening) increases with increasing the number of graphene monolayer [43, 50, 54]. It has been observed from equations (12) and (13) that with the increase in spectral width linearly decreasing SNR and QF thereby, employing a limitation on the maximum number of graphene layers that may be used for high performance of the biosensor. The increment in the number of graphene layers affects largely the performance of the promised SPR sensor. Thirdly, using the equations (12)-(15), performance parameters are appraised in the form of quality factor (Q.F), signal to noise ratio (SNR), and sensitivity (S). We determine the sensitivity (S), SNR and Q.F and the outcome are presented in Table 1, where the distinction between the traditional SPR sensor and raised SPR sensor is focused. An observation in Table 1 shows that the traditional SPR biosensor reveals 85.00 deg/RIU of angular sensitivity. It is possible to enrich the angular sensitivity by affixing graphene layers. For these configurations, we determined ΔnS=0.06 by incorporating equation (12) when 1000 nM complementary target DNA is present in the sensor. The calculated angular sensitivities are 93.33 deg/RIU, 108.33 deg/RIU,…and 156.67 deg/RIU respectively. Table. 1. Sensitivity (S), Signal to Noise Ratio (SNR) along with quality factor (Q.F) for various graphene layers. No.
of
ϴ𝑠𝑝𝑅
ϴ0.5
layer (L)
Change of Change SPR
of Sensitivity
SNR
Q.F
angle spectral width (S)
(Δϴ𝑠𝑝𝑅)
(Δϴ0.5)
0
54.60
54.40
5.10
1.35
85.00
3.38 62.96
1
55.00
54.90
5.60
1.85
93.33
3.03 50.45
2
55.90
55.50
6.50
2.29
108.33
2.84 47.31
3
56.70
56.35
7.30
3.30
121.67
2.21 36.87
6
57.50
57.05
8.10
4.00
135.00
2.03 33.75
10
58.80
58.10
9.40
5.05
156.67
1.86 31.02
A realization upon Table 1 that the shifts of resonance angle toward greater value on the growth of the number of graphene layers [49]. Consequently, This rightward shift of resonance angle associated with an enlarged width of the SPR curve resembles the drastic fluctuation in the SPR motion induced by the coating of graphene on metal [48, 50]. The drastic fluctuation in the curve finally turns into the up-gradation of sensitivity [24]. This exalt sensitivity obtains on account of the switching of θSPR, which is caused by the absorption capability of biomolecules [39], powerful fluorescence appeasing capability of graphene [40]. Additionally, Table 1 represents the evaluated outcomes for SNR and Q.F for conventional as well as graphene-based raised SPR biosensor. The close observation of Table 1 pointed out that the gradual decrease has happened in SNR and Q. F. owing to the increased layer of graphene in the sensor.
200
4
150
3
100
2
50
0
1
2
3
4
5
6
7
8
9
Signal to Noise Ratio (SNR)
Sensitivity(S) [deg/RIU]
Sensitivity versus Graphene Layer SNR versus Graphene Layer
1 10
No. of Graphene Layers (L) 160
70
140
60
120
50
100
40
80
0
1
2
3
4
5
6
7
8
9
Quality Factor (QF)[/RIU]
Sensitivity(S) [deg/RIU]
Sensitivity versus Graphene Layer QF versus Graphene Layer
30 10
No. of Graphene Layers (L)
Fig. 6. Change of (a) the sensitivity and SNR, (b) the sensitivity and Q.F as the function of the graphene layers As a fourth factor, we evaluate the optimal number of graphene layers which secure the foremost sensitivity and enhance the SNR and QF of the raised biosensor. The number of graphene layers gradually has changed from 1 to 10. As shown in Fig. 6(a), the improved sensitivity as well as SNR can be obtained at a stage of graphene layer number is between 3 to 4 and in Fig. 4(b), the improved sensitivity as well as QF can be availed at the stage of the graphene layer number is between 2 to 3. Therefore, we choose the optimum graphene layer as 3 in the proposed SPR biosensor. Howsoever, the sensor structure with 3 graphene layers is still adoptable for DNA hybridization identification. Table.2. Comparison of change of SPR angle, sensitivity, SNR and QF with respect to design strategy among proposed sensor with other existing works References [56]
Layers Statistics Graphene layer with chromium substrate
Change of SPR
Sensitivit
angle (Δϴ𝑠𝑝𝑅)
y (S)
---
68.03
SNR
Q.F
---
9.691
[24]
Mono layer of
6.15
87.8
1.28
17.56
5.886
84.09
0.82
11.71
1:50
95.71
1.763
25.19
1.00
200
0.7692
11.51
7.30
121.67
2.21
36.87
graphene and MoS2 [57]
Mono ayer of graphene-MoS2 with TiO2 - SiO2
[58]
A monolayer of graphene and Tungsten Disulfide (WS2)
[59]
Six MoS2 and mono graphene layers
proposed
Tri layers of graphene
TM polarization the electric field produced due to the SPW along x-direction is specified in ref. [21] as: jk spw cosin z jk spw sin in x
E x E0 cos in e
k k 0 nk k 2c0 where spw , is the wave vector of SPW in layered media, 0 vector and E0 is the magnitude of the electric field.
(14)
(0 0 )633
is a free-space wave
Further once more, in this segment, we used to evaluate electric field distribution by organizing the finite difference time domain (FDTD) procedure utilizing commercial software Opti FDTD multiphysics software. The FDTD is an amazing technique to explain Maxwell's equations in a nano film layer (Au-50 nm) by utilizing the YEE-algorithms. The FDTD method is a more feasible than others, for example, multiple-multiple or Green’s dynamic method in resolving Maxwell’s equations for complex geometries and dispersive media, for example, gold and silver [43]. The simulation was completed with the planer wave with the center wavelength of 633 nm. Surface plasmon polarition (SPP) excitation is performed utilizing angular interrogation method. The perfectly matched layer (PML) boundary condition was utilized in such a way, that waves go into the layers with generating minimum reflections (Rmin) [44]. Also, transmittance electric field intensity was accounted for utilizing DFT transmission monitor at 520 nm away from Au/graphene interface. The electric field distribution of the proposed biosensor structure with 10 graphene layers have been explained. The structure is resolved by subcell PML in all direction. The time steps and the FDTD spatial mesh are set to ∆t=∆/4C0 and ∆=λ/10, individually, to fulfill CFL stability criterion, where λ is the wavelength equivalents to 633 nm. Here, ∆x= ∆y= ∆z= ∆ = 63.3 nm. At last, the computational space is finished by a 15 nm perfectly matched layer (PML) cells according to the Fig 7(a). The outcome is acquired to run the simulation during 50,000 time steps so as to arrive field components at steady state.
DFT Monitor (Reflectance)
SF11 Prism (180 nm)
z
DFT Monitor (Transmittance)
y x
PML (15 nm)
PML (15 nm)
Planer Wave (633nm)
Gold (50 nm)
(a)
Graphene (3.4 nm)
PML (15 nm)
Sensing Layer (520 nm)
PML (15 nm)
1
(a) (b) Electric Field Intensity (|E 2| / |E0 2 |) [a.u]
0.8
0.2
0
0
Au (50nm)
Prism (SF11)
0.4
Graphene (3.40 nm)
0.6
Sensing medium (250 nm)
with Graphene without Graphene
300 350 400 450 250 100 50 150 200 Distance perpendicular to the interface [nm]
Fig. 7: (a) 2D Yee’s cell for the electric field distribution along x direction, (b) Normalized electric field intensity with graphene layers (solid black line) and without graphene layers (dash red line).
In Fig. 7 (b), it is seen that the normalized electric field can secure higher absorption of light to have huge SPW excitation and the numerical estimations of the electric field distribution in the design with graphene is more noteworthy. Thus, SPW excitations are more consolidated for the arrangement with graphene. The expansion of graphene over the gold layer can influence the field intensity which causes sensitivity enhancement by expanding the mobility of electrons. The electric field intensity ways to deal with its maximum value when the reflectance curve demonstrates the minimum value of reflectivity. For this situation, the most noteworthy excitation of SPs can happen. As can be obviously observed from Fig. 7 , the graphene layer enhances the field intensity and shows a peak as graphene additionally reflects remarkable electrical and optical properties and delivers high enthusiasm as a 2D material.
Conclusion In this presented work, a graphene tri layers based surface plasmon resonance (SPR) refractive index sensor is illustrated. The angular interrogation scheme has been utilized to analyze the reflection from the proposed sensor consisted of prism (SF11 glass), Gold (Au), graphene-based configuration. The effect of adding graphene layer has been investigated on factors of sensor sensitivity (S), signal to noise ratio (SNR), quality factor (QF), after then the number of graphene layers is optimized to three layers. Further, the SPR curves have been plotted and a comparison of sensor sensitivity, signal to noise ratio, quality factors have been made among the existing works at this optimal thickness. From the obtained results, we have observed the sensitivity of the optimized number of graphene layers based sensors is enriched to an excellent value of 121.67 deg-RIU-1 with improved SNR of 2.21and QF of 36.87 RIU-1 respect conventional SPR sensor. Afterward, the effect of electric field allocation on incorporating the graphene layer is made an analyzation utilizing the finite difference time domain (FDTD) mean with the help of the Opti FDTD solution commercial environment.
Acknowledgment: This work was supported by the Deanship of the Scientific Research (DSR), King Abdulaziz University Jeddah, under grant No. (DF-422-135-1441). The authors , therefore, gratefully acknowledge DSR technical and financial support.
References [1] K. Tamersit, F. Djeffal, Double-gate graphene nanoribbon field-effect transistor for DNA and gas sensing applications: simulation study and sensitivity analysis, IEEE Sens. J. 16(11), (2016) 4180-4191. [2] J. Homola, M. Piliarik, Surface Plasmon Resonance Based Sensors. Vol. 4 Ch. 2, 46–47 (Springer, 2006). [3] Q. Ouyang, S. Zeng, L. Jiang, L. Hong, G. Xu, X.-Q. Dinh, J. Qian, S. He, J. Qu, P. Coquet, K.-T. Yong, Sensitivity enhancement of transition metal dichalcogenides/silicon nanostructure-based surface plasmon resonance biosensor, Sci. Rep. 6 (2016) 28190.
[4] S. Zeng, D. Baillargeat, H.P. Ho, K.T. Yong, Nanomaterials enhanced surface plasmon resonance for biological and chemical sensing applications. Chem. Soc. Rev. 43 (2014) 3426-3452. [5] L. Xia, S. Yin, H. Gao, Q. Deng, C. Du, Sensitivity enhancement for surface plasmon resonance imaging biosensor by utilizing gold–silver bimetallicfilm configuration, Plasmonics 6 (2011) 245–250. [6] Priyabrata Pattnaik, Surface plasmon resonance, Appl. Biochem. Biotechnol. 126 (2) (2005) 79–92. [7] J. Nico, Marcel JE. Fischer, Surface plasmon resonance: a general introduction, Surface Plasmon Resonance, Humana Press, 2010, pp. 1–14. [8] Anna J. Tudos, BM Schasfoort Richard, Introduction to surface plasmon resonance, Handbook of Surface Plasmon Resonance, 2008, pp. 1–14. [9] Bo Liedberg, Claes Nylander, Ingemar Lunström, Surface plasmon resonance for gas detection and biosensing, Sensor. Actuator. 4 (1983) 299–304. [10] Fang-Fang Ren, Kah-Wee Ang, Junfeng Song, Qing Fang, Mingbin Yu, GuoQiang Lo, Dim-Lee Kwong, Surface plasmon enhanced responsivity in a waveguided germanium metal-semiconductor-metal photodetector, Appl. Phys. Lett. 97 (9) (2010) 091102. [11] Sachin K. Srivastava, Vikas Arora, Sameer Sapra, Banshi D. Gupta, Localized surface plasmon resonancebasedfiber optic U-shaped biosensor for the detection of blood glucose, Plasmonics 7 (2) (2012) 261–268. [12] Md. Biplob Hossain, Tarik Bin Abdul Akib, Lway Faisal Abdulrazak, Md. Masud Rana,“Numerical modeling of graphene-coated fiber optic surface plasmon resonance biosensor for BRCA1 and BRCA2 genetic breast cancer detection,”Opt. Eng.58(3), 037104 (2019), doi: 10.1117/1.OE.58.3.037104. [13] Yu A. Akimov, W.S. Koh, Resonant and non-resonant plasmonic nanoparticle enhancement for thin-film silicon solar cells, Nanotechnology 21 (23) (2010) 235201. [14] Erwin Kretschmann, Heinz Raether, Radiative decay of non radiative surface plasmons excited by light, Z. Naturforsch. 23 (12) (1968) 2135–2136. [15] Sandrine Filion-Côté, Philip JR. Roche, Amir M. Foudeh, Maryam Tabrizian, Andrew G. Kirk, Design and analysis of a spectro-angular surface plasmon resonance biosensor operating in the visible spectrum, Rev. Sci. Instrum. 85 (9) (2014) 093107. [16] Md. Biplob Hossain, Mehedi Hassan, Lway Faisal Abdulrazak, Md. Masud Rana, Md. Mohaiminul Islam, M. Saifur Rahman, Graphene-MoS2-Au-TiO2-SiO2 Hybrid SPR Biosensor for Formalin Detection: Numerical Analysis and Development, Advanced Materials Letters, 2019, 10. [17] Zhitao Lin, Leyong Jiang, Leiming Wu, Jun Guo, Xiaoyu Dai, Yuanjiang Xiang, Dianyuan Fan, Tuning and sensitivity enhancement of surface plasmon resonance biosensor with graphene covered Au-MoS2-Au Films, IEEE Photon. J. 8 (6) (2016) 1–8. [18] Md Biplob Hossain, Md Masud Rana, Lway Faisal Abdulrazak, Saikat Mitra, Mostafizur Rahman, Graphene-MoS2 with TiO2- SiO2layers based surface plasmon resonance biosensor: Numerical development for formalin detection, Biochemistry and Biophysics Reports 18 (2019) 100639. [19] Kandammathe Valiyaveedu Sreekanth, Shuwen Zeng, Ken-Tye Yong, Ting Yu, Sensitivity enhanced biosensor using graphene-based one-dimensional photonic crystal, Sensor. Actuator. B Chem. 182 (2013) 424– 428. [20] Rahman, M.S., Noor, S.S., Anower, M.S., Abdulrazak, L.F., Rahman, M.M. and Rikta, K.A. (2019) Design and Numerical Analysis of a Graphene-Coated Fi-ber-Optic SPR Biosensor Using Tungsten Disulfide. Photonics and Nanostruc-tures-Fundamentals and Applications, 33, 29-35. https://doi.org/10.1016/j.photonics.2018.11.005 [21] I. Pockrand, J.D. Swalen, J.G. Gordon II, M.R. Philpott, Surface plasmon spectroscopy of organic monolayer assemblies, Surf. Sci. 74 (1) (1978) 237–244. [22] I. Pockrand, Surface plasma oscillations at silver surfaces with thin transparent and absorbing coatings, Surf. Sci. 72 (3) (1978) 577–588.
[23] Otto S. Wolfbeis, Bernhard M. Weidgans, Fiber optic chemical sensors and biosensors: a view back, Optical Chemical Sensors, Springer, Dordrecht, 2006, pp. 17–44. [24] M. Saifur Rahman, Md Shamim Anower, Md Rabiul Hasan, Md Biplob Hossain, Md Ismail Haque, Design and numerical analysis of highly sensitive Au-MoS2-graphene based hybrid surface plasmon resonance biosensor, Optic Commun. 396 (2017) 36–43. [25] A.K. Mishra, S.K. Mishra, Eur. Phys. Lett. (2015). [26] M. Saifur Rahman, Md. Shamim Anower, Lway Faisal Abdulrazak. (2019) Mod-eling of a Fiber Optic SPR Biosensor Employing Tin Selenide (SnSe) Allotropes. Results in Physics, 15, Article ID: 102623. https://doi.org/10.1016/j.rinp.2019.102623 [27] Zao Yi, et. al., Tunable Graphene-based Plasmonic Perfect Metamaterial Absorber in the THz Region, Micromachines 2019, 10(3), 194. [28] Chunlian Cen, et. al., Terahertz wideband perfect absorber based on open loop with cross nested structure. Results in Physics 15 (2019) 102603 [29] C. Cen, et. al., Theoretical design of a triple-band perfect metamaterial absorber in the THz frequency range. Results in Physics 2019, 14, 102463. [30] M.B. Hossain, S. Muktadhir, Optik 127 (2016) 5841–5851. [31] MB Hossain, MS Muktadhir, MM Rana "Modeling graphene macroscopic and microscopic conductivity in the sub-cell FDTD method" International Conference on Electrical & Electronic Engineering (ICEEE), Rajshahi, Bangladesh, (2015) [32] C. Cen, et. al., Numerical investigation of a tunable dual-band metamaterial perfect absorber consisting of two-intersecting graphene nanorings arrays. Physics Letters A 2019, 383(24), 3030–3035 [33] C. Cen, et. al., Dual-Band Plasmonic Perfect Absorber Based on Graphene Metamaterials for Refractive Index Sensing Application. Micromachines 2019, 10, 443. [34] L. Wu, et. al., Highly sensitive graphene biosensors based on surface plasmon resonance, Opt. Express 18 (14) (2010) 14395–14400 [35] MM Rana, MB Hossain, MR Islam, YG Guo "Surface plasmon polariton propagation modeling for graphene parallel pair sheets using FDTD" Applied Superconductivity and Electromagnetic Devices (ASEMD), Shanghai, China, (2015) [36] Leiming Wu, Jun Guo, Xiaoyu Dai, Yuanjiang Xiang, Dianyuan Fan, Sensitivity Enhanced by MoS2– Graphene Hybrid Structure in Guided-Wave Surface Plasmon Resonance Biosensor Plasmonics, 2018, 13(1), 281–285. [37] MB Hossain, MM Rana, "An effective compact-FDTD wideband modeling of graphene conductivity", Int. conf. Electrical Engineering and Information Communication Technology (ICEEICT), Dhaka, Bangladesh (2015) [38] KN Shushama, MM Rana, R Inum, MB Hossain "Graphene coated fiber optic surface plasmon resonance biosensor for the DNA hybridization detection: Simulation analysis" Optics Communications, 383, pp. 186-190, (2017) [39] Leiming Wu, Yue Jia, Leyong Jiang, Jun Guo, Xiaoyu Dai, Yuanjiang Xian, and Dianyuan Fan, Sensitivity improved SPR biosensor based on the MoS2/graphene-aluminum hybrid structureJournal of Lightwave Technology, 2017, 35(1), 82-87.
[40] Leiming Wu Jun Guo Qingkai Wang Shunbin Lu, Xiaoyu Dai Yuanjiang Xiang Dianyuan FanSensitivity enhancement by using few-layer black phosphorus-graphene/TMDCs heterostructure in surface plasmon resonance biochemical sensorSensors and Actuators B: chemical, 2017, 249, 542-548. [41] M. B. Hossain, M. M. Rana, L. F. Abdulrazak, S. Mitra, and M. Rahman, “Design and analysis of grapheneMoS2 hybrid layer based SPR biosensor with TiO2-SiO2 nano film for formalin detection: numerical approach”, Optical and Quantum Electronics, 2019, 51(6): 195–207. [42] M. S. Rahman, M. S. Anower, and L. F. Abdulrazak, “Utilization of a phosphorene-graphene/TMDC heterostructure in a surface plasmon resonance-based fiber optic biosensor,” Photonics and NanostructuresFundamentals and Applications, 2019, 35(3): 100711. [43] M. B. Hossain, M. M. Islam, L. F. Abdulrazak, M. M. Rana, T. B. A. Akib, and M Hassan, “Graphenecoated optical fiber SPR biosensor for BRCA1 and BRCA2 breast cancer biomarker detection: a numerical design-based analysis,” Photonic Sensors, 2019, 9(4): 1–13. [44] M. O’Brien, K. Lee, R. Morrish, N.C. Berner, N. McEvoy, C.A. Wolden, G.S. Duesberg, Plasma assisted synthesis of WS2 for gas sensing applications, Chem. Phys. Lett. 615 (2014) 6–10. [45] Hossain, B., Tasnim, T., Abdulrazak, L.F., Rana, M. and Islam, R. (2019) A Nu-merical Approach to Design the Kretschmann Configuration Based Refractive Index Graphene-MoS2 Hybrid Layers with TiO2-SiO2 Nano for Formalin Detec-tion. Photonic Sensors, 1-13. https://doi.org/10.1007/s13320-019-0566-5 [46] J.B. Maurya, Y.K. Prajapati, V. Singh, J.P. Saini, R. Tripathi, Performance of graphene–MoS2 based surface plasmon resonance sensor using silicon layer, Opt. Quantum Electron. 47 (2015) 3599–3611. [47] M.S. Rahman, MS. Anower, M.K. Rahman, M.R.Hasan, M.B. Hossain, M.I. Haque, Modeling of highly sensitive MoS2-graphene hybrid based fiber optic SPR biosensor for sensing dna hybridization, Optik 140 (2017) 989–997 [48] M.B. Hossain, M. M. Rana,"DNA hybridization detection based on resonance frequency readout in graphene on Au SPR biosensor, Journal of sensors (2016) [49] M.B. Hossain, M. M. Rana, Graphene coated high sensitive surface plasmon resonance biosensor for sensing DNA hybridization, Sens. Lett. 14, (2016) 1–8. [50] KN Shushama, MM Rana, R Inum, MB Hossain, "Sensitivity enhancement of graphene coated surface plasmon resonance biosensor" Optical and Quantum Electronics 49 (11), 381, (2017) [51] MS Rahman, MB Hossain, MM Rana "Sensitivity enhancement of porous silicon based SPR sensor using graphene-M0S2 hybrid structure" International conf. on Electrical, Computer & Telecommunication Engineering (ICECTE), Dhaka, Bangladesh, (2015) [52] M. S. Rahman, M. S. Anower, L. F. Abdulrazak, and M. M. Rahman, “Modeling of a fiber-optic surface plasmon resonance biosensor employing phosphorene for sensing applications,” Optical Engineering, 2019, 58 (3): 037103. [53] L. Diéguez, N. Darwish, M. Mir, E. Martínez, M. Moreno, and J. Samitier, “Effect of the Refractive Index of Buffer Solutions in Evanescent Optical Biosensors,” Oct-2009. [54] Pradeep Kumar Maharana, Rajan Jha" Chalcogenide prism and graphene multilayer based surface plasmon resonance affinity biosensor for high performance", Sensors and Actuators B: chemical, 169 (2012) 161–166 [55] M. B. Hossain, M. M. R. Khan, M. S. Rahman, S. S. B. Badrudduza, M. M. Sabiha, et al., “GrapheneMoS2-Au-TiO2-SiO2 hybrid SPR biosensor: A new window for formalin detection,” Journal of Materials and Applications, 2019, 8(2): 51–58. [56] A. Verma, A. Prakash, R. Tripathi, Sensitivity enhancement of surface plasmon resonance biosensor using graphene and air gap, Opt. Commun. 357 (2015), 106–112 [57] Maurya, J. B.; Prajapati, Y.K.; Singh, V.; Saini, J. P., Sensitivity enhancement of surface plasmon resonance sensor based on graphene–MoS2 hybrid structure with TiO2–SiO2 composite layer. Appl Phys A, 2015, 121, 525.
[58] M. Saifur Rahmana, Md.Rabiul Hasan, Khaleda Akter Rikta, M.S. Anower, ‘A novel graphene coated surface plasmon resonance biosensor with tungsten disulfide (WS2) for sensing DNA hybridization’, Optical Materials 75 (2018) 567-573. [59] Hamid Vahed, Cyrus NadriSensitivity enhancement of SPR optical biosensor based on Graphene–MoS2 structure with nanocomposite layer, Optical Materials 88 (2019) 161–166.
High Performance Refractive Index SPR Sensor Modeling Employing Graphene Tri Sheets Highlights To illustrate a surface plasmon resonance (SPR) sensor based on graphene exciting configuration consists of Gold (Au), graphene, prism (SF11 glass) and sensing medium. To utilize angular interrogation method basically for the inspection of reflected light from the sensor for the enhancement of sensor sensitivity (S), signal to noise ratio (SNR), quality factor (QF). To optimize graphene layers to three. Thereafter, at these optimum layers, the SPR curves are plotted and comparison of sensor sensitivity, signal to noise ratio, quality factor is made among the existing works. It is observed that the sensitivity of the optimized graphene layers based sensor is enhanced to excellent value of 121.67 deg-RIU-1 with improved SNR of 2.21and QF of 36.87 RIU-1 respect conventional SPR sensor. The effect of electric field distribution on inserting graphene layer is analyzed incorporating the finite difference time domain (FDTD) technique by applying Opti FDTD solution multiphysics commercial software.
High Performance Refractive Index SPR Sensor Modeling Employing Graphene Tri Sheets This is to inform you that the revised research manuscript entitled above is submitted to your journal for considering to publish in your regular issue and this article is contributed by following authors:
Md. Biplob Hossain1*, Ibrahim Mustafa Mehedi2, M. Moznuzzaman1, Lway Faisal Abdulrazak3, Md. Amzad Hossain1 1Department
of Electrical and Electronic Engineering Jashore University of Science & Technology, Jashore, Bangladesh 2Center
Excellence in Intelligent Engineering Systems (CEIES) Electrical and Computer Engineering Department (ECE) King Abdulaziz University, Jeddah, Saudi Arabia 3 Department
of Computer Science Cihan University Slemani, Sulaimaniya, Iraq. Email: [email protected], [email protected], [email protected], [email protected], [email protected], * Corresponding Author: Dept. of Electrical and Electronic Engineering Jashore University of Science & Technology Jashore, Bangladesh [email protected]
Competing Interest All authors declare that they have no competing interests.