Multilayer Surface Plasmon Resonance Research Articles

Multi-layer SPR biosensor for in-Situ Amplified monitoring of the SARS-CoV-2 omicron (B.1.1.529) variant

This article represents an analysis of the performance of multi-layer surface plasmon resonance (SPR) biosensors in detecting the transferable human SARS-CoV-2 Omicron (B.1.1.529) variant. The proposed multi-layer SPR biosensor performance is enhanced by integrating fine-tuning prisms, plasmonic metals, and two-dimensional (2D) transition metal dichalcogenides (TMDs) materials. To evaluate the performance of the multi-layer SPR sensor, the transfer matrix method (TMM) is employed. In numerical result, the proposed (CaF2/Cu/BP/Graphene) structure demonstrates the most favorable sensitivity and detection accuracy, characterized by a 410° angle shift sensitivity/refractive index unit (RIU). Additionally, the sensor achieves a detection accuracy (DA) of 0.4713, a quality factor (QF) of 94.25 RIU−1, a figure of merit (FOM) of 91.87, and a combined sensitivity factor (CSF) of 90.36. The presented sensor is also capable of detecting target biomolecule binding interactions between ligands and analytes at a range of concentrations (from 0 nM to 1000 nM), implying its potential use for detecting the omicron virus strain. The outcomes highlight the effectiveness of the presented sensor for real time, and label free detection, particularly in identifying the Omicron viral strain. Eventually, this research promises advanced biosensor technology, crucial for rapid viral variant detection and diagnostics.

Highly sensitive Ag/BaTiO3/MoS2 nano composite layer based SPR sensor for detection of blood and cervical cancer

In this article, a nano-composite Ag/BaTiO3/MoS2 multilayer coating-based surface plasmon resonance (SPR) sensor with high sensitivity and figure of merit for the detection of cancer cells is analyzed. The proposed SPR biomedical sensor structure is built on the angular interrogation approach to utilizing the refractive index component, attenuated total reflection (ATR) analysis is employed to identify different kinds of cancer cells. The resonance angle varied as the refractive index (RI) of healthy and cancerous cells changed. Which ranged from 1.368 to 1.392 for increasing concentration in cervical (HeLa cells) and blood (Jurkat cells), RI 1.376 to 1.390 changes as the concentration of cancerous cells increases in healthy cells. The maximum estimated sensitivities for cervical (HeLa) and blood (Jurkat) cancer cells based on numerical data were 271.25 deg/RIU and 290.714 deg/RIU, respectively. The proposed BK7/Ag/BaTiO3/ MoS2has the ability to identify cancerous and healthy cells with the greatest overall sensitivity, as demonstrated by layered structures. Finally, the numerical results analyzed in this manuscript revealed a high degree of sensitivity and FoM compared to those of previous research studies.

Improved Differential Evolution Algorithm for Sensitivity Enhancement of Surface Plasmon Resonance Biosensor Based on Two-Dimensional Material for Detection of Waterborne Bacteria

Due to the large number of waterborne bacteria presenting in drinking water, their rapid and accurate identification has become a global priority. The surface plasmon resonance (SPR) biosensor with prism (BK7)-silver(Ag)-MXene(Ti3T2Cx)-graphene- affinity-sensing medium is examined in this paper, in which the sensing medium includes pure water, vibrio cholera (V. cholera), and escherichia coli (E. coli). For the Ag-affinity-sensing medium, the maximum sensitivity is obtained by E. coli, followed by V. cholera, and the minimum is pure water. Based on the fixed-parameter scanning (FPS) method, the highest sensitivity is 246.2 °/RIU by the MXene and graphene with monolayer, and with E. coli sensing medium. Therefore, the algorithm of improved differential evolution (IDE) is obtained. By the IDE algorithm, after three iterations, the maximum fitness value (sensitivity) of the SPR biosensor achieves 246.6 °/RIU by using the structure of Ag (61 nm)-MXene (monolayer)-graphene (monolayer)-affinity (4 nm)-E. coli. Compared with the FPS and differential evolution (DE) algorithm, the highest sensitivity is more accurate and efficient, and with fewer iterations. The performance optimization of multilayer SPR biosensors provides an efficient platform.

Numerical Analysis of Coronavirus Detection Using Photonic Crystal Fibre-Based SPR Sensor.

Coronavirus disease (COVID-19) is a worldwide health emergency caused by the coronavirus 2 (severe acute respiratory illness) (SARS-CoV-2). COVID-19 has a wide range of symptoms, making a definitive diagnosis difficult. The shortage of equipment for testing technology COVID-19 has resulted in long queues for COVID-19 testing, which is a major problem. COVID-19 testing is currently performed using sluggish and costly technology like single-photon emission computed tomography (SPECT), computed tomography (CT), positron emission tomography (PET), and enzyme-linked immunosorbent assay (ELISA). The gold standard test for diagnosing COVID-19 is real-time reverse transcriptase-polymerase chain reaction (RT-PCR), which necessitates highly skilled workers and has a lengthy turnaround time. However, rapid and affordable immunodiagnostic techniques (antigen or antibody tests) are also available with some trade off accuracy. Optical sensors are frequently employed in a variety of applications, because of their increased sensitivity, strong selectivity, rapid reaction times, and outstanding resolution. The use of photonic crystal fibre (PCF) is advantageous for the quick detection of the new coronavirus and is suggested with the use of a PCF-based (Au/BaTiO3/graphene) multilayered surface plasmon resonance (SPR) biosensor. The proposed sensor can quickly detect the COVID-19 virus in two different ligand-analyte environments: (i) the virus spike receptor-binding domain (RBD) as an analyte and monoclonal antibodies (mAbs) as a probe ligand, and (ii) monoclonal antibodies (IgG or IgM) as an analyte and the virus spike RBD as a probe ligand. The finite element method (FEM) is used to quantitatively examine the performance of the PCF-based multilayered SPR sensor.

Effect of 2-D nanomaterials on sensitivity of plasmonic biosensor for efficient urine glucose detection

This paper presents a multi-layered Kretschmann configuration-based Surface Plasmon Resonance (SPR) biosensor for the detection of urine glucose. The modelling, simulation, and analysis have been done by using Silver (Ag) and Gold (Au) layer on the low refractive index prism BK-7 separately, which created two structures: structure-I (BK7/Ag/Bio-sample) and structure-II (BK7/Au/Bio-sample). Urine samples from a non-diabetic person (0–15 mg/dL) and a diabetic person (.625 gm/dL, 1.25 gm/dL, 2.5 gm/dL, 5 gm/dL, and 10 gm/dL) with the corresponding refractive indices of 1.335, 1.336, 1.337, 1.338, 1.341, and 1.347, respectively, have been used as a bio-sample that has been put on the top layer of the sensor. An investigation was conducted to improve the performance parameters of the proposed plasmonic biosensor by layering different 2-D nanomaterials (graphene, BP) and TMDC materials (MoS2, MoSe2, WS2, and WSe2) over the silicon (Si) layer in both structures at a visible wavelength of 633 nm, using Transfer Matrix Method (TMM). With layer thickness optimization, Structure-I (BK7/Ag (56 nm/Si (3 nm)/WS2 (.8 nm)/Bio-sample) shows a sensitivity of 200 °/RIU which is enhanced up to 1.7 times that of the conventional biosensor (BK7/Ag/Bio-sample) and 1.3 times that of the BK7/Ag (56 nm)/Si (3 nm)/Bio-sample based biosensor. Whereas in Structure-II (BK7/Au (50 nm)/Si (3 nm)/BP (.53 nm)/Bio-sample) with optimised layer thickness, we obtained a sensitivity of 273.4°/RIU, which is enhanced up to 2.2 times that of the conventional biosensor (BK7/Au/Bio-sample) and 1.3 times that of the BK7/Au (50 nm)/Si (3 nm)/Bio-sample. Other performance parameters such as detection accuracy for Structure-I and Structure-II are .5617 degree−1 and .134 degree−1 respectively. The Figure of merit for Structure-I and Structure-II are 112.35/RIU and 36.89/RIU respectively. Therefore, we expect Structure-I (BK7/Ag (56 nm/Si (3 nm)/WS2 (.8 nm)/Bio-sample) and Structure-II (BK7/Au (50 nm)/Si (3 nm)/BP (.53 nm)/Bio-sample) have the potential to detect the glucose concentration with quick response and high sensitivity in terms of the resonance angle shift in SPR curves.

Computational Design of Highly-Sensitive Graphene-Based Multilayer SPR Biosensor

In this paper, we present a set of optimal graphene-based multilayer surface plasmon resonance (SPR) biosensors for highly sensitive detection of biomolecules. To optimize the biosensor structure, we employed a multi-objective gray wolf optimizer (MOGWO) to maximize the sensitivity and minimize the structure full width at half maximum (FWHM). The main advantages of the optimized structures are high sensitivity, low FWHM, as well as easy implementation. We developed an algorithm that enables us to achieve nine different optimized structures. The best sensitivity, FWHM and FOM are obtained equal to 264.6°/RIU (for the structure #5), 1.905° and 56.6/RIU (for the structure #8), respectively. The results of this paper pave the way for the development of highly-sensitive SPR biosensors.

Numerical approach to design the graphene-based multilayered surface plasmon resonance biosensor for the rapid detection of the novel coronavirus

In this article, a graphene-based multilayered surface plasmon resonance (SPR) biosensor of (BK7/WS2/Au/BaTiO3/Graphene) is proposed for the rapid detection of the novel coronavirus (COVID-19). The proposed SPR biosensor is designed based on the angular interrogation attenuated total reflection (ATR) method for rapid detection of the COVID-19 virus. The sensor’s surface plasmon polaritons (SPPs) and the sensing region refractive index (RI) are changed, owing to the interaction of various concentrated ligand-analytes. The specific ligand is mechanized with the proposed sensor surface and the target analyte that has flowed onto the sensing surface. The proposed sensor is capable of detecting the COVID-19 virus rapidly in two different ligand-analytes environments, such as: (i) the virus spike receptor-binding domain (RBD) as an analyte and monoclonal antibodies (mAbs) as a probe ligand, and (ii) the monoclonal antibodies (IgG or IgM) as an analyte and the virus spike RBD as a probe ligand. Due to the binding of the target ligand-analytes, the concentration level of the sensing region is incremented. As the increment in the concentration level, the RI of the sensing medium increases, therefore the change in RI causes the shift in the SPR angle resulting in the output reflectance intensity. The performance of the multilayered SPR sensor is analyzed numerically using the finite element method (FEM) method. Numerically, the proposed sensor provides the maximum angular shift sensitivity at 230.77 deg/refractive index unit (RIU), detection accuracy (DA) at 0.161 deg−1, and the figure of merits (FOM) is at 37.22 RIU−1. In addition, with each additional graphene layer number (L), the proposed sensor exhibits the angular shift sensitivity increment (1 + 0.7L) times. The novelty of the proposed multilayer (BK7/WS2/Au/BaTiO3/Graphene) sensor is highly angular sensitivity, and capable of detecting the COVID-19 virus rapidly without a false-positive report.

Polymer based surface plasmon resonance sensors: Theoretical study of sensing characteristics

There has been renewed interest in the area of surface plasmon resonance (SPR) for biosensing application. The analytical tools such as immunofluorescence, chromatography and mass spectroscopy are laboratory based and require considerable amount of time and expense and their overall use is complicated. SPR based sensing is a promising technique with the advantage of high sensitivity, small size, easy to use and not so expensive. Due to the need for easy processing and low cost sensing design, polymers can be considered as a favorable candidate for designing the SPR sensors. Ease of fabrication, disposability and cost-effectiveness are some of the merits of polymer materials that make them an ideal for the sensor. The present work investigates exclusively the effect of different polymeric materials on the sensitivity of SPR. Theoretical calculations are done in reflectance mode. Any change in refractive index of analyte results in the angular shift of reflectance dip that can be utilized to detect the presence of analyte. Different multilayer SPR configurations are modeled in Matlab to investigate the optical characteristics of the sensor. In addition, the optimal parameters of different layers corresponding to the highest sensitivity are explored. The performance of an SPR sensor is determined by its sensitivity (Sθ), FWHM and Rmin.

Improving the Sensitivity of SPR Sensors with Au–Ag alloys and 2D Materials — a Simulation‐Based Approach

AbstractPlasmonic‐based sensing revolves around the generation of plasmons as a result of light–matter interactions. Analytical and/or diagnostic technologies based on this principle are extremely successful and popular in the bio‐medical industry due to their high sensitivity as well as real‐time and label‐free sensing capabilities. Employing 2D multilayers as the main plasmonic substrate instead of pure metals is a relatively new concept that can provide advantages for the surface plasmon resonance (SPR) sensor. In this work, the gain in sensitivity of the Au–Ag based SPR sensors is evaluated by employing 2D materials like graphene, MoS2, and WS2 in a multilayer SPR system. The simulations calculate the sensitivity of such multi‐layered SPR structures and indicate that the use of WS2 in the modified system can lead to an increased sensitivity (1.53 times) as compared to the standard Au‐based Kretschmann configuration.

Surface Plasmon Resonance-Based Fiber-Optic Metallic Multilayer Biosensors.

Accurate and quick sensing of various biomolecules relevant to different health conditions is indispensable in modern diagnosis and treatment procedures. Different multilayer metallic surface plasmon resonance (SPR) biosensor configurations comprising Au, Ag, Al, and Cu are analyzed in this work by employing an N-layer matrix formalism as applied to the fixed-angle spectral SPR sensing methodology. Stringent standards for sensitivity, detection accuracy, and figure of merit (FOM) of the sensor configurations are set to analyze the relative merits of one configuration over another. It is observed that three- and four-layer configurations using Al and Cu provide the best FOM among all sensors that passed the set standard criteria. The highest FOM (1433.82/RIU) is observed for the four-layer Al/Cu/Al/Cu sensor for an analyte refractive index of 1.408. The sensors are best suited for detecting analytes with a refractive index range of 1.350–1.414.

Concentration sensor with multilayer thin film-coupled surface plasmon resonance

Concentration sensor with multilayer thin film-coupled surface plasmon resonance

Goos–Hänchen shift enhancement based on an improved differential evolution algorithm

The Goos–Hänchen (GH) shift is one of the important aspects to evaluate the performance of multilayer surface plasmon resonance (SPR) sensors. However, the conventional SPR sensor design procedure based on the fixed parameter scanning (FPS) method is complex and time-consuming, and makes it difficult to gain the optimized design. In this paper, in order to design the optimal GH-shift-based SPR sensor, an improved differential evolution (IDE) algorithm based on chaos mapping, fitness elimination mechanism, nonlinear scale factor, and cross probability control strategy is proposed. By using such an IDE algorithm, the Ag‐ITO‐TMDCs‐graphene structure can be optimized. By the IDE algorithm, after 9 iterations, the maximum fitness value is obtained in the Ag‐ITO‐ M o S 2 -graphene structure, the maximum GH shift is 16591 λ , and the sensitivity is 3.3 × 10 8 λ / R I U . Compared with the FPS method, the GH shift is increased 192 times, and the sensitivity is increased 25,707.6 times. Compared with the DE algorithm, the number of iterations and the efficiency of the IDE algorithm are enormously improved as well. Such an algorithm provides a new, to the best of our knowledge, approach for designing a multilayer SPR sensor.

Multi-layer optical fiber surface plasmon resonance biosensor based on a sandwich structure of polydopamine-MoSe2@Au nanoparticles-polydopamine.

An all-optical fiber multi-layer surface plasmon resonance (SPR) biosensor based on a sandwich structure of polydopamine-MoSe2@Au nanoparticles-polydopamine (PDA-MoSe2@AuNPs-PDA) was designed for the detection of specific immunoreactions. By optimizing the multi-layer structure and the ratio of MoSe2: AuNPs, a sensitivity of 5117.59 nm/RIU has been obtained, which is more than double that of the only Au-filmed optical fiber SPR sensor. A large surface area was produced by integrating the MoSe2 primitive unit cell and the AuNPs into a hybrid plasmonic nanostructure of MoSe2@AuNPs, leading to optical fiber SPR signal amplification. The nanostructure of MoSe2@AuNPs was surrounded by the PDA layer to guarantee the efficient immobilization of the protein molecules on the optical fiber by strong covalent bond. This biosensor achieved a detection limit of 54.05 ng/mL for detecting the goat-anti-rabbit IgG, which demonstrated enhancements of 12.1%, 23.3% and 184.6% in comparison with three reported SPR biosensors decorated with PDA-AuNPs-PDA, PDA and Cysteamine-MoSe2@AuNPs-Cysteamine nanostructure, respectively. This biosensor achieved favorable selectivity and outstanding sensitivity compared with the reported SPR immuno-sensors, which will provide a miniaturized, rapid-response and label-free optical fiber bio-sensing platform for clinical diagnosis in the future.

Multianalyte sensing analysis with multilayer photonic crystal fiber-based surface plasmon resonance sensor

In this work, we proposed multianalyte multichannel Photonic Crystal Fiber (PCF)-based Surface Plasmon Resonance sensor with gold- and silver-doped plasmonic layers. The Full Vectorial Finite Element Method (FV-FEM) with perfectly matched layers (PML) are employed for numerical analysis of the proposed sensor. The key propagation features, such as confinement loss, resonance condition, resolution, and sensitivity of the proposed sensor, have been reported for all possible refractive index variations. According to the spectral sensitivity analyses, the average sensitivities for fixed RI values are obtained as 4100 nm/RIU and 3820 nm/RIU for Ch1 and Ch2, respectively. On the other hand, results for varying RI values are obtained as 3600 nm/RIU and 3700 nm/RIU for Ch1 and Ch2, respectively. Moreover, the maximum average sensitivity of proposed sensor reaches to 4250 nm/RIU for varying RI at Ch2 and 4200 nm/RIU for varying RI at Ch1.

A novel method to improve the measurement accuracy of multilayer surface plasmon resonance sensor

In this paper, a novel method to improve the measurement accuracy of multilayer surface plasmon resonance (SPR) sensor is proposed. Based on the Kretschmann SPR sensor, the measurement layer is transferred from the outermost layer to the inside of the structure (in the form of prism-metal-measurement-dielectric layer), the new structure shows excellent linear relationship between the refractive index (RI) and the resonance wavelength with the linear fitting coefficient improved from 0.97048 to 0.99904, and the measurement error reduced by 96.75 %, which can greatly improves the measurement accuracy. In the simulation of the five-layer, six-layer and seven-layer structure, it is verified that the conclusion of four-layer structure is also applicable to multilayer structures, the detailed analysis and explanation are also discussed. As an example, magnetic fluid (MF) film is selected as the measurement layer to demonstrate the performance of the designed structure. Parameters of the structure were optimized by simulation, the optimal thickness of the MF layer is 120 nm and the optimal RI of dielectric layer is 1.35. With these optimized parameters, the measurement accuracy is greatly improved and the measurement sensitivity of magnetic field is 5nm/mT. The idea is also expected to be applied to other types of SPR sensors to achieve higher measurement accuracy.

Theoretical Investigation of Multilayer Ti3C2Tx MXene as the Plasmonic Material for Surface Plasmon Resonance Sensors in Near Infrared Region

The multilayer Ti <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> MXene-based surface plasmon resonance (SPR) sensors are theoretically discussed with high figure of merit (FOM) (304 RIU-1) in near infrared region. The result shows that the multilayer Ti <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> MXene, a metallike material, can be used to produce a strong SPR signal and further applied to detect the change in refractive index of sensing medium. Comparing to the conventional SPR sensor based on Au thin film (50 nm) at the visible range, the FOM of the proposed MXene-based SPR sensor has been improved by 7.8 times. Our study demonstrates that the multilayer Ti <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> MXene can be developed as a new surface plasmon polariton (SPP) material to apply in SPR sensor.

Theoretical study of modulated multi-layer SPR device for improved refractive index sensing

In the present work, a theoretical investigation of Surface Plasmon Resonance (SPR) properties of a multilayer film (Au-SiO2-Au) coated on a glass prism is being carried out. In this multilayer structure, each interface corresponds to multiple SPR modes. To obtain the maximum reflection dips in the SPR modes, the thickness of SiO2 layer is optimized by varying it from 100-600 nm. Our calculation also reveals that SPR mode corresponding to Au-ambient interface is very sensitive to the changes in the surrounding medium, least affecting other SPR modes. The sensing performance of the proposed nano-plasmonic sensor is theoretically calculated using bulk refractive index sensing. Such multilayer SPR sensing device has advantages over conventional SPR devices in terms of their bulk sensitivity and self-referencing, claiming itself as a potential candidate for the development of highly sensitive biological sensor.

Multilayer with periodic grating based high performance SPR waveguide sensor

We propose a high performance periodic grating coupled multi-layered surface plasmon resonance (SPR) waveguide based on Al+Au. High sensitivity is obtained by using grating filled with silver instead of air. Further sensor's performance is analysed by optimising width and thickness of SPR active metal layer as well as grating period also. Using finite difference time domain (FDTD) method, we have shown that sensitivity and detection accuracy can be improvised using appropriate multi-layered grating configuration.

Numerical investigation of a grating and graphene-based multilayer surface plasmon resonance biosensor

A multilayer surface plasmon resonance biosensor (SPRB) incorporating a grating-graphene configuration is investigated for enhanced sensitivity. The numerical analysis of the impact of integrating a periodic array of subwavelength grating on top of a layer of graphene sheet for improving sensitivity is presented. The result of monitoring the biomolecular interactions of DNA hybridization is compared against the outcome of the conventional SPRB, a graphene-based multilayer SPRB, and a multilayer layer grating SPRB, and is mathematically validated. It is demonstrated that the inclusion of a grating and graphene layer on top of the gold thin film is an excellent candidate for a highly sensitive SPRB. To achieve further enhancement of sensitivity, the subwavelength grating is numerically optimized against its geometry including grating configurations (rectangular, sinusoidal, and triangular), grating depth, volume factor, and grating period.

Simulation and Analysis of a Sub-Wavelength Grating Based Multilayer Surface Plasmon Resonance Biosensor

This paper presents a subwavelength grating based multilayer surface plasmon resonance biosensor (SPRB) which includes a periodic array of subwavelength grating on top of a layer of graphene sheet in the biosensor. The proposed biosensor is named grating-graphene SPRB (GG-SPRB). The aim of the proposed multilayer structure is to improve the sensitivity of the SPRB through monitoring of the biomolecular interactions of DNA hybridization. Significant sensitivity improvement is obtained for the GG-SPRB compared with the conventional SPRB. The result of the numerical investigation of the GG-SPRB is presented and compared with a theoretically developed multilayer matrix formalism, and a good agreement has been observed. In addition, an optimization of the grating dimensions including volume factor, grating depth, grating angle, grating period, and grating geometry (e.g., rectangular, sinusoidal and triangular) is presented. The outcome of the investigation presented in this paper identifies desired functioning conditions corresponding to the best design parameters for the GG-SPRB.