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Abstract
Two-dimensional materials, which can be used to modify sensor surfaces to increase sensor sensitivity, have important research in the field of sensors. In this paper, we design a highly sensitive D-shaped photonic crystal fiber sensor with graphene-MoS2 heterostructure for hemoglobin detection. The research utilized the finite element method and involved addition of different layers of graphene and MoS2 to the optical fiber sensing area, and it was determined that the hybrid nano-heterostructures made of monolayer graphene and bilayer MoS2 provided the greatest improvement in sensor performance. The sensor shows excellent detection performance in 1.33∼1.38 refractive index units. Using incident light in the wavelength ranges of 650 nm and 850 nm, the proposed sensor has a maximum wavelength sensitivity of 4700 nm/RIU, a maximum amplitude sensitivity of 327.5 RIU-1, and a resolution of 2.17×10−5 RIU. The range of hemoglobin concentrations detected with this sensor was 0 g/L∼241 g/L, with an average sensitivity of 0.7 nm/(g/L). A fiber biosensor was enhanced with graphene-MoS2 hybrid nanostructures, which exhibit excellent photoelectric properties and detection performance, enabling highly sensitive, highly accurate, and real-time hemoglobin detection. The result shows the significant research value and application prospects in the field of biomedical detection.
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1. Introduction
Surface plasmon resonance (SPR) is an electromagnetic effect resulting from the oscillation of free electrons caused by the total reflection of light at the boundary between metal and dielectric material [1]. Yablonovitch et al. and John S et al. first proposed photonic crystal fibers (PCF) [2,3]. PCF has periodic or non-periodic arrays of microcavity and is usually made of fused silica, polymers, or plastics. Recently, researchers have combined SPR and PCF to create powerful PCF-SPR sensors. These sensors detect target parameters such as temperature, humidity, magnetic field strength, pH, and concentration as the medium being monitored changes. Notably, biosensors are gaining popularity. Analytical devices that convert chemical data from physical and chemical detectors into usable electrical signals [4]. PCF-SPR sensors have many applications in biosensing because their properties match bioassay requirements DNA, viruses, glycans, proteins, lectins, antigens and antibody immune species [5–9]. Singh S et al. presented a PCF-SPR sensor for detecting phenolic compounds in aqueous solutions in 2013 [10]. In 2021, Nizar SM et al. proposed a circular PCF sensor that can detect both immunoglobulin G (IgG) and I immunoglobulin M (IgM) antibodies [9]. The sensor used the light-conducting properties of IgG and IgM at different RI to detect antibodies.
Two-dimensional materials have many innovative applications in the biomedical field due to their unique physical, chemical, and optoelectronic properties. For example, the large surface area can effectively access biological information and improve drug delivery efficiency; some 2D materials have SPR, which can be applied to sensing detection and Raman imaging [11]; graphene has excellent adsorption properties, which can immobilize target cells or adsorb macromolecular structures [12]; phosphorus-based nanomaterials such as black scales have important biomedical applications for their sensitivity, degradation, and responsiveness in biological systems applications [13]. In 2018, Dong Z J et al. proposed transferring graphene to poly-ethylene terephthalate (PET) to form a graphene planar electrode with a short sensing time and good stability. The design allows for the effective detection of dopamine [14]. In 2018, Shao Su et al. proposed using MoS2-Au@Pt nanocomposites as enzyme mimics to detect glucose efficiently [15].
Graphene is the most well-known two-dimensional material with excellent optoelectronic properties. Such as good optical transparency, low magnetoresistance, high carrier mobility, and tunability [16]. When applied to SPR, the more transferred charge strengthens the resonant coupling effect, enhancing the sensor properties. For bioassays like DNA and protein interactions in extreme dilution, graphene surfaces can identify fragrant chemicals by π-stacking forces [17]. MoS2 in transition metal disulfide compounds (TMDs) has gained attention with the study of two-dimensional materials. The direct energy band of the MoS2 monolayer is 1.8 eV [18]. Monolayer MoS2 has a higher light absorption (5%) than graphene (2.3%), and a higher work function (5.1 eV) than graphene (4.5 eV) [19]. Van der Waals pressures cause heterojunctions between thin layers of different 2D materials. The heterojunction will have different optoelectronic properties than a single material because the dielectric constant, absorption coefficient, and forbidden bandwidth of the two 2D materials are different [20]. Diverse materials formed heterojunctions can improve device performance.
In this paper, we present a D-shaped PCF-SPR biosensor based on graphene-MoS2 heterostructures for the detection of hemoglobin concentrations. The graphene-MoS2 and heterostructures in this sensor not only enhance SPR by their own good optoelectronic properties, but also their good biological properties allow better recognition of biological information. This model is based on the finite element method, in which the refractive index (RI) of the fluid to be measured changes in response to the hemoglobin concentration within the fluid, and the sensor detects the change in hemoglobin concentration by detecting the change in RI.
2. Modeling and theoretical analysis
2.1 Structural design and principle of the sensor
Figure 1 depicts the structural model of the sensor described in this paper. The three-dimensional structure of the sensing fiber is depicted in Fig. 1(a). The core is cylindrical at first, then polished to form a D-shaped side throw plane. A two-dimensional cross-section of an optical fiber is shown in Fig. 1(b). The white holes in the fiber, as shown in the diagram, are air holes. The air holes are arranged in a regular hexagonal pattern, with a spacing of Λ = 2.5 um between adjacent holes. An air hole with a diameter of d1 = 0.66 um is directly above the center of the fiber, and it is flanked to the left and right by air holes with a diameter of d2 = 0.9 um. The air hole directly beneath the fiber's center has a diameter of d4 = 2.04 um, while the remaining air holes have a diameter of d3 = 1.2 um. Furthermore, the light grey is fused silica, the red is a titanium dioxide layer with a thickness of h4 = 10 nm, the yellow-low is a thin gold layer with a thickness of h3 = 35 nm, the blue and pink mixture is bilayer MoS2 with a thickness of h2 = 1.3 nm, and the black and white mixture is monolayer graphene with a thickness of h1 = 0.34 nm. The sensing area of the sensor is formed by these multiple layers.
Fig. 1. (a) Three-dimensional structural model; (b) Two-dimensional cross-section diagram; (c) Sensing area model.
2.2 Theoretical model of materials
The theoretical model of each material can be represented by the RI or dielectric constant, and the theoretical model of the same material under different wavelengths of light is also different. The RI of fused silica can be expressed in terms of the Sellmeier equation [21]. As a plasmonic metal, gold is an integral part of the SPR-PCF sensor. The dielectric constant of gold is modeled by Drude-Lorenz [1]. The TiO2 is sandwiched between gold and SiO2 as an adhesive layer to strengthen the bond and improve the SPR. The RI of TiO2 can be expressed as [22]:
The band gap of the material affects the properties of the material. Figure 2(a) and (b) depict the band structures of monolayer graphene and MoS2. The bandgap of monolayer MoS2 is a direct bandgap. The bandgap spacing shrinks as the number of MoS2 layers increases. From Fig. 2(d), the band gap spacing of MoS2 decreases with the increase of the number of MoS2 layers, and the band gap bit is 1.8 eV for a single layer and 1.24 eV for a double layer. Different band gaps have different degrees of electron confinement, which will change the intensity of the SPR and thus enhance the detection [23]. Because of the peculiarities of the structure, the complex refractive index of MoS2 varies for different layers and cannot be fully expressed by an equation. Recently, Xu et al. conducted testing experiments on 1 to 3 layers of MoS2 and obtained their complex RI [24]. As shown in Fig. 2(e), the real (n) and imaginary (k) parts of MoS2 with different layers have different wavelengths ranging from 400 nm to 850 nm. Figure 2(c) represents the band gap diagram of 1 to 3 layers of graphite, the graphene band gap is very small and can be considered as zero band gap. The zero band gap can help excite electrons from the valence to the conduction bands, resulting in a high intrinsic carrier concentration and conductivity. Therefore, graphene is also called a semi-metallic material. It can adsorb many electrons, due to the zero band gap, electrons are transferred from the surface of graphene very smooth, thus enhancing the SPR [25]. The complex RI of the monolayer graphene is [26]:
where C1 ≈ 5.446 um-1. In general, the RI of air is 1.Fig. 2. (a) Band structure of monolayer graphene; (b) Band structure and Brillouin zone of monolayer MoS2; (c) Band gap of 1 to 3 layers of graphene; (d) Band gap of 1 to 2 layers of MoS2; (e) Complex refractive index of 1 to 3 layers of MoS2.
The sensor can detect organisms’ hemoglobin concentrations. When the hemoglobin concentration changes, so do the RI of the hemoglobin-containing blood, so a computational model of the hemoglobin concentration and its RI must be built. The equation for representing the hemoglobin concentration nH in this article is [27]:
where CH is the hemoglobin concentration, α = 0.1942 L/g is the coefficient of dependence of hemoglobin on the spectrum, nP denotes the RI of plasma, which is related to the wavelength λ of the incident light, and the expression for the RI of plasma is [28]:2.3 Sensor performance parameters
Constraint loss is a critical component of sensing performance analysis, and it is expressed in the equation as [29]:
3. Results and discussion
3.1 Relationship between mode analysis and dispersion
Dispersion relations and mode analysis are also necessary components of the sensor's study. As illustrated in Fig. 3(a)∼(c), the sensor operates in multiple modes at y-polarization for a medium with a RI of 1.37. The connection between the three modes and the dispersion spectrum is depicted in Fig. 3(d). As shown in Fig. 3(d), when two green lines intersect at a particular incident wavelength, their effective RI approaches unity, at which point the red solid line reaches its maximum and the limiting loss is maximum, resulting in the best resonant coupling. Insets I, II, and III in Fig. 3(d) correspond to the three modes depicted in Fig. 3(a), (b), and (c), respectively. In the same case, the X-polarization loss of the sensor is much lower than the loss of Y-polarization, so the proposed sensor model is detected under Y-polarized light.
Fig. 3. (a) SPP mode at Y-polarization; (b) Fiber core mode at Y-polarization; (c) Resonant coupling mode at Y-polarization; (d) Dispersion spectrum and mode analysis.
3.2 Different layers of graphene and MoS2 affect sensor performance
As shown in Figs. 4(a) and 4(d), to more clearly analyze the effect of graphene and molybdenum disulfide on the performance of the sensor, the researchers added graphene and molybdenum disulfide with different layers to the upper surface of the gold layer in the sensing area respectively. Figures 4(b) and 4(e) show the resonance loss curves of solutions with different refractive indices of 1.36, 1.37 and 1.38 detected by the sensors added with different layers of graphene and MoS2, respectively. Figures 4(c) and 4(d) show the corresponding amplitude sensitivity. The performance parameters of graphene and molybdenum disulfide added with different number of layers are plotted in Tables 1 and 2.
Fig. 4. (a) Sensing area diagram,(b) Loss spectrum curve, and (c) Amplitude sensitivity of 0 to 3 layers of graphene; (d) Sensing area diagram,(e) Loss spectrum curve, and (f) Amplitude sensitivity of 0 to 3 layers of MoS2.
Table 1. Performance parameters of adding different layers of graphene
Table 2. Performance parameters of adding different layers of MoS2
3.3 Graphene-MoS2 heterostructure sensor performance analysis
Through the above analysis, we compare and analyze the above model data, as shown in Fig. 5(a) and 5(b). So, we propose a more reasonable sensor model based on the addition of a bilayer of MoS2 to the gold surface followed by the addition of a monolayer of graphene on top of the MoS2. The sensing region composed of monolayer graphene and bilayer MoS2 makes optimal use of the inherent properties of each material, resulting in superior sensing and detection performance. The graphene-MoS2 heterostructure sensor's loss spectrum is depicted in Fig. 5(c). When the RI is between 1.37 and 1.38, the ${S_\lambda }$ is 4700 nm/RIU. The ${S_A}$ of the sensor is shown in Fig. 5(d), which also increases with RI. ${S_A}$ reaches a maximum value of 327.5 RIU-1. In comparison to the model without the graphene-MoS2 heterostructure, the maximum ${S_\lambda }$ and ${S_A}$ of the designed sensor model are increased by approximately 24% and 23%, respectively. To demonstrate the sensor's performance, we plotted the polynomial fitting curve for the resonant wavelength shown in Fig. 5(e). The fitted polynomial for the resonant wavelength y versus the refractive index x is y = 35893 x2 – 94224 x + 62488 for a refractive index range of 1.33 to 1.38, and the fitting curve has a correlation coefficient of R2 = 0.9994.
Fig. 5. (a) Comparison of loss spectrum curve of different models; (b) Comparison of amplitude sensitivity of different models; (c) Loss spectrum curve and (d) Amplitude sensitivity of graphene-MoS2 heterostructure fiber optic biosensor; (e) Resonant wavelength polynomial fit curve; (f) Relationship between sensor resonance fitting curve and hemoglobin concentration.
We propose a D-shaped PCF-SPR biosensor with enhanced sensitivity due to the graphene-MoS2 heterostructure, which has good detection performance when the RI of the medium to be measured is 1.33∼1.38. We replace the measuring medium with a computational model of blood containing hemoglobin. Figure 5(f) is the relationship between sensor resonance fitting curve and hemoglobin concentration. For a more concise analysis, we swap the relationship between RI and resonance wavelength in the fitted curve of the sensor's resonance peak and refit it, yielding a fitted curve equation for the resonance wavelength λ and the na of the medium to be measured as na = -1.2097×10−6 λ2 + 0.0021 λ + 0.47109, with R2 = 0.9980 as the correlation coefficient between λ and na. We've chosen blood with hemoglobin concentrations of 0 g/L, 80 g/L, 160 g/L, and 241 g/L. There is only one intersection between different concentrations of hemoglobin and the resonance fitting curve when the optical wavelength is between 682 nm and 850 nm. The hemoglobin concentration in that plasma is determined by the value of the hemoglobin concentration curve intersecting the fitted curve at that wavelength, allowing for hemoglobin concentration detection. At a resonance wavelength of 850 nm, the sensor's upper detection limit is calculated to be 241 g/L. A normal adult's hemoglobin concentration is 120∼160 g/L, and the sensor's effective detection range is 0∼241 g/L. In the effective detection range, the average sensitivity is calculated to be 0.7 nm/(g/L). Additionally, Table 3 contains a list of articles that use a sensor with similar detection conditions to the one described in this paper. In conclusion, the proposed optical fiber sensor is capable of detecting biological hemoglobin concentrations with high sensitivity.
Table 3. Performance comparison
Our proposed sensor fabrication process is simple, first pure silicon rods and hollow core silicon rods are put into jacket by stacking, then high temperature stretching is performed, the detection plane is polished, and finally TiO2 and gold layers are coated, and then the grown MoS2 and graphene are transferred to the sensing plane. The sensor is small, sensitive and reusable, and can be effectively used for hemoglobin detection. In addition, other biological information can also be detected with this sensor.
4. Conclusions
This paper presents a D-shaped PCF-SPR biosensor based on graphene-MoS2 heterostructures with outstanding sensitivity for detecting hemoglobin concentrations. The addition of graphene-MoS2 hybrid nanostructures in the sensing region increases the sensor's sensitivity for hemoglobin detection. The sensor is capable of exploring the measured medium with RI values of 1.33 to 1.38 when the light wavelength is between 650 nm and 850 nm. The maximum wavelength sensitivity of the sensor is 4700 nm/RIU and the maximum amplitude sensitivity is 327.5 RIU-1 with a resolution of 2.17×10−5 in the effective detection range, which is a 24% increase in wavelength sensitivity and a 23% increase in amplitude sensitivity compared to the model without the addition of graphene-MoS2. In the case of blood containing hemoglobin, the sensor can detect concentrations of hemoglobin between 0 g/L and 241 g/L, with a detection sensitivity of approximately 0.7 nm/(g/L). Two-dimensional materials and nanomaterials, can be used to modify sensor surfaces and demonstrated to increase sensor sensitivity. The proposed structure making full use of the optoelectronic properties of graphene and MoS2 shows promising prospects in the design of the application potential in the direction of biomedical detection.
Funding
National Natural Science Foundation of China (61765004, 62165004); Innovation Project of GUET Graduate Education (2022YCXS047,2021YCXS040); the Open Fund of Foshan University, Research Fund of Guangdong Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology (2020B1212030010).
Acknowledgments
We thank the National Natural Science Foundation of China, and the Innovation Project of Guangxi Graduate Education for partial funding.
Disclosures
The authors declare no conflicts of interest.
Data availability
Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.
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