Slotted photonic crystal fiber-based plasmonic biosensor

PCF Based Four-Channel SPR Biosensor With Wide Sensing Range

In this article, we have demonstrated a highly sensitive four-channel photonic crystal fiber (PCF) based surface plasmon resonance (SPR) biosensor which can detect four different analytes simultaneously. To ease practical implementation, four analyte sensing layers and plasmonic materials such as gold (Au) and gold (Au) with Tantalum Pentoxide (Ta2O5) are placed on the exterior of the four arms of the square shaped structure. The sensor's structure consists of only nine circular air holes, making it simple and easy to fabricate using currently available technologies. Finite element method (FEM) based numerical analysis is used to evaluate the sensing performance of the proposed sensor. With optimum structure parameters, the sensor achieves maximum wavelength sensitivity of 11000, 25000, 11000 and 25000 nm/RIU for Channel-1, Channel-2, Channel-3, and Channel-4 respectively. It shows maximum amplitude sensitivity of 803.732, 709.171, 803.827, 709.146 RIU -1 for Channel 1, 2, 3, and 4 respectively. It also shows maximum FOM of 232.55, 352.36, 231.57, 352.36 RIU -1 in Ch-1, Ch-2, Ch-3 and Ch-4 respectively. Moreover, the proposed sensor shows a wide range of refractive index sensing capability from 1.30 to 1.41. Due to multi-analyte detection capability, large sensing range, and excellent sensitivity the proposed sensor unfolds unrivalled capacity of detecting chemicals, carcinogenic agents, biomolecules, and other analytes.

Machine Learning Applications in Optical Fiber Sensing: A Research Agenda

The constant monitoring and control of various health, infrastructure, and natural factors have led to the design and development of technological devices in a wide range of fields. This has resulted in the creation of different types of sensors that can be used to monitor and control different environments, such as fire, water, temperature, and movement, among others. These sensors detect anomalies in the input data to the system, allowing alerts to be generated for early risk detection. The advancement of artificial intelligence has led to improved sensor systems and networks, resulting in devices with better performance and more precise results by incorporating various features. The aim of this work is to conduct a bibliometric analysis using the PRISMA 2020 set to identify research trends in the development of machine learning applications in fiber optic sensors. This methodology facilitates the analysis of a dataset comprised of documents obtained from Scopus and Web of Science databases. It enables the evaluation of both the quantity and quality of publications in the study area based on specific criteria, such as trends, key concepts, and advances in concepts over time. The study found that deep learning techniques and fiber Bragg gratings have been extensively researched in infrastructure, with a focus on using fiber optic sensors for structural health monitoring in future research. One of the main limitations is the lack of research on the use of novel materials, such as graphite, for designing fiber optic sensors. One of the main limitations is the lack of research on the use of novel materials, such as graphite, for designing fiber optic sensors. This presents an opportunity for future studies.

Plasmonic photonic biosensor: in situ detection and quantification of SARS-CoV-2 particles

We conceptualized and numerically investigated a photonic crystal fiber (PCF)-based surface plasmon resonance (SPR) sensor for rapid detection and quantification of novel coronavirus. The plasmonic gold-based optical sensor permits three different ways to quantify the virus concentrations inside patient's body based on different ligand-analyte conjugate pairs. This photonic biosensor demonstrates viable detections of SARS-CoV-2 spike receptor-binding-domain (RBD), mutated viral single-stranded ribonucleic acid (RNA) and human monoclonal antibody immunoglobulin G (IgG). A marquise-shaped core is introduced to facilitate efficient light-tailoring. Analytes are dissolved in sterile phosphate buffered saline (PBS) and surfaced on the plasmonic metal layer for realizing detection. The 1-pyrene butyric acid n-hydroxy-succinimide ester is numerically used to immobilize the analytes on the sensing interface. Using the finite element method (FEM), the proposed sensor is studied critically and optimized for the refractive index (RI) range from 1.3348-1.3576, since the target analytes RIs fluctuate within this range depending on the severity of the viral infection. The polarization-dependent sensor exhibits dominant sensing attributes for x-polarized mode, where it shows the average wavelength sensitivities of 2,009 nm/RIU, 2,745 nm/RIU and 1,984 nm/RIU for analytes: spike RBD, extracted coronavirus RNA and antibody IgG, respectively. The corresponding median amplitude sensitivities are 135 RIU^-1, 196 RIU^-1 and 140 RIU^-1, respectively. The maximum sensor resolution and figure of merit are found 2.53 × 10^-5 RIU and 101 RIU^-1, respectively for viral RNA detection. Also, a significant limit of detection (LOD) of 6.42 × 10^-9 RIU²/nm is obtained. Considering modern bioassays, the proposed compact photonic sensor will be well-suited for rapid point-of-care COVID testing.

High index core flat fiber surface plasmon resonance bio-sensor

Due to tremendous design flexibility and ease of light control capability, the photonic crystal fiber offers efficient, flexible, and miniaturized plasmonic biosensors with attractive features. In this work, a high index (GeO₂ doped silica) core flat fiber is proposed and analyzed for RI sensing ranging from 1.53 to 1.60. A rectangular analyte channel is created on top of a flat fiber to better handle the liquid analyte. To introduce the plasmonic effect, TiO₂ and gold are deposited to the analyte channel. The sensing performance is carried out for two operating wavelengths, as two peaks are obtained for each analyte. The second operating wavelength shows better sensing performance than the first one. However, the proposed sensor offers average wavelength sensitivity of 5000 nm/RIU with a sensor resolution of 2×10^-05 RIU. In addition, the proposed sensor shows identical linearity, which is quite rare in prior sensors. Moreover, the proposed flat sensor provides outstanding detection accuracy of 0.01nm^-1, detection limit of 79.28 nm, signal to noise ratio of -4.1497dB, and figure of merit of 50RIU^-1. Owing to outstanding sensing performance and a unique detection range, this sensor can be effectively used in biological and organic analyte sensing applications.

Highly Sensitive Plasmonic Waveguide Biosensor Based on Phase Singularity-Enhanced Goos-Hänchen Shift

The detection for small molecules with low concentrations is known to be challenging for current chemical and biological sensors. In this work, we designed a highly sensitive plasmonic biosensor based on the symmetric metal cladding plasmonic waveguide (SMCW) structure for the detection of biomolecules. By precisely designing the configuration and tuning the thickness of the guiding layer, ultra-high order modes can be excited, which generates a steep phase change and a large position shift from the Goos−Hänchen effect (with respect to refractive index changes). This position shift is related to the sharpness of the optical phase change from the reflected signal of the SPR sensing substrate and can be directly measured by a position sensor. Based on our knowledge, this is the first experimental study done using this configuration. Experimental results showed a lateral position signal change > 90 µm for glycerol with a sensitivity figure-of-merit of 2.33 × 104 µm/RIU and more than 15 µm for 10−4 M biotin, which is a low molecular weight biomolecule (less than 400 Da) and difficult to be detected with traditional SPR sensing techniques. Through integrating the waveguide with a guiding layer, a strong improvement in the electric field, as well as sensitivity have been achieved. The lateral position shift has been further improved from 14.17 µm to 284 µm compared with conventional SPR substrate with 50 nm gold on single side. The as-reported sensing technique allows for the detection of ultra-small biological molecules and will play an important role in biomedical and clinical diagnostics.

Graphene-Coated Highly Sensitive Photonic Crystal Fiber Surface Plasmon Resonance Sensor for Aqueous Solution: Design and Numerical Analysis

This paper presents the design and analysis of a surface plasmon resonance (SPR) sensor in a photonic crystal fiber (PCF) platform, where graphene is used externally to attain improved sensing performance for an aqueous solution. The performance of the proposed sensor was analyzed using the finite element method-based simulation tool COMSOL Multiphysics. According to the simulation results, the proposed sensor exhibits identical linear characteristics as well as a very high figure of merit (FOM) of 2310.11 RIU−1 in the very low detection limit of 10−3. The analysis also reveals the maximum amplitude sensitivity of 14,847.03 RIU−1 and 7351.82 RIU−1 for the x and y polarized modes, respectively, which are high compared to several previously reported configurations. In addition, the average wavelength sensitivity is 2000 nm/RIU which is comparatively high for the analyte refractive index (RI) ranging from 1.331 to 1.339. Hence, it is highly expected that the proposed PCF-based SPR sensor can be a suitable candidate in different sensing applications, especially for aqueous solutions.