Description:FIELD OF THE INVENTION
The present invention discloses a device for covid detection and a method thereof. More particularly, the present invention relates to a defect mode-based photonic crystal fiber (pcf) sensor device for covid-19 detection which utilizes a silica based photonic crystal fiber (PCF) sensor in a defect mode with higher sensitivity specificity, biocompatibility, functional simplicity and optical transparency. The present invention also relates to a method of detection of COVID with said device.
BACKGROUND OF THE INVENTION
The global covid-19 pandemic highlighted the critical need for rapid, accurate, and cost-effective diagnostic tools to control disease transmission. Standard testing methodologies, such as quantitative reverse transcription-polymerase chain reaction (QRT-PCR) for viral RNA extraction and identification from nasopharyngeal (np) and/or oropharyngeal (op) samples, are effective but often involve complex pre-analytical sample collection, preservation, and transport procedures.

The integrity and stability of viral RNA during these stages are paramount for test accuracy. While specialized transport media are commonly used, unconventional alternatives like phosphate buffered saline (PBS) and normal saline have demonstrated comparable efficacy in preserving viral RNA stability and integrity, offering practical and cost-effective solutions for sample storage and transport. The existing optical biosensors offer promising avenues for rapid detection due to their high sensitivity and potential for miniaturization. However, challenges remain in achieving sufficient sensitivity, specificity, and robustness for real-time, point-of-care diagnostics, especially for viral pathogens like SARS-COV-2.

Traditional optical fibers may lack the precise light manipulation capabilities required for highly sensitive refractive index changes indicative of viral presence. There is a continuous need for advanced sensor designs that can overcome these limitations, providing more reliable and robust sensing platforms for critical public health applications.
There are various patent and non-patent literature in this field of technology.
Reference for one such patent application no. KR-20240176615-A titled as “Fiber-optic sensor and system for SARS-CoV-2 spike protein detection”. The present prior art describes a fiber-optic sensor designed to detect the SARS-CoV-2 spike protein using a unique four-part system. It starts with an input unit (single-mode fiber) that introduces light into the sensor. This light then enters an interference unit (no-core fiber), which generates multi-mode interference patterns. Next, a crucial resonance unit (double-clad fiber with a long-period fiber grating) superimposes grating resonance onto the light, creating specific spectral signatures sensitive to external changes. Finally, an output unit (single-mode fiber) receives and transmits this processed light for analysis. The interplay of multi-mode interference and grating resonance allows the sensor to detect the presence of the SARS-CoV-2 spike protein, likely by changes in its unique spectral output when the protein binds to the sensor.
Another literature in the existing state of art is patent application no. US-20230082940-A1 titled as “Devices and methods for detection of severe acute respiratory syndrome coronavirus 2”. The cited prior art discloses a biosensor detects SARS-CoV-2 infection using a curved optical fiber probe. The probe's surface is coated with bioreceptor molecules that specifically bind to the virus's target molecule. The device works by measuring a proportional drop in light intensity that passes through the fiber when the virus binds. This detection is facilitated by plasmonic gold nanoparticles, which can either form the sensing surface or act as labels in a sandwich assay.
Reference for one such patent application no. CN-112730340-A titled as “Optical fiber sensor for quickly detecting novel coronavirus SARS-CoV-2”. The cited prior art describes an optical fiber sensor detects SARS-CoV-2 using a novel T-shaped aptamer that greatly improves the capture of the virus's N protein. The sensor supports two methods: a direct analysis method where the aptamer is fixed on the fiber, and a highly sensitive sandwich method. The sandwich method uses gold/silver nanosphere-aptamer conjugates for signal amplification and double aptamers for enhanced specificity. This approach offers high specificity, sensitivity, and speed, making it a valuable complement to existing nucleic acid detection techniques.
Another reference is made to non-patented document by MA Mollah, LF Abdulrazak as “Photonic crystal fiber plasmonic biosensor for SARS-CoV-2 particle quantification and detection”. This paper describes a compact and highly promising photonic sensor for SARS-CoV-2 diagnostics. Its superior sensitivity, particularly for viral RNA, combined with its compact design and rapid detection capabilities, makes it an excellent candidate for point-of-care (POC) COVID-19 testing. Such a device could enable quick and accurate diagnoses outside of traditional laboratory settings, facilitating faster public health responses and personalized healthcare.
The prior arts are restricted to well-equipped institutions with trained personnels. Moreover, existing technologies have only limiting quantitative analysis, expensive cost of operation and test result only detectable after three to six days post-infection.

In order to obviate the drawbacks in the existing state of the art, there is a pressing need of real-time monitoring, fast response times, and portable diagnostic equipment. Said system will avoid a one-size-fits-all approach and cater to each user’s needs and experiences.

OBJECT OF THE INVENTION
The main object of the present invention is to provide a defect mode-based photonic crystal fiber (pcf) sensor device for covid-19 detection and a method thereof.

Another object of the invention is to provide a device for COVID detection utilizing a silica based photonic crystal fiber (PCF) sensor in a defect mode and give real time monitoring.

Yet another object of the invention is to provide a device and method capable of providing fast response for the detection of covid-19 analytes by using silica based photonic crystal fiber (PCF) sensor in a defect mode.
Yet another object of the invention is to provide a portable diagnostic device having simplicity in operation for the detection of covid-19 analytes.
Yet another object of the invention is to provide low-cost detection device with higher sensitivity specificity, biocompatibility, functional simplicity and optical transparency for detection of covid-19 analytes.

Yet another object of the invention is to provide a method for detection of covid-19 analytes which is quick and scalable.

SUMMARY OF THE INVENTION:
In order to obviate the drawbacks in the existing state of the art, the present invention provides a defect mode-based photonic crystal fiber (pcf) sensor device for covid-19 detection and method thereof. The novel device offers significant advantages, including enhanced sensitivity, improved specificity, superior biocompatibility, simplified functional operation, and excellent optical transparency. These attributes collectively obviate the drawbacks inherent in prior art COVID-19 detection methodologies.

A defect mode-based Photonic Crystal Fiber (PCF) sensor specifically engineered for enhanced detection of COVID-19 analytes. The sensor design incorporates a unique hexagonal lattice structure with three air hole layers, strategically modified to generate and enhance a defect mode. This defect mode significantly alters light propagation within the fiber, making the sensor highly sensitive to minute changes in the refractive index of the sample introduced into the central core.
The sensor features a central core for holding the COVID-19 sample analyte, surrounded by precisely arranged air holes of varying diameters. A key aspect of the invention is the creation of a defect by deleting three air holes from the second layer of the PCF, further enhanced by the insertion of two larger air holes within this defect region. This configuration, coupled with the circular core structure, allows for more reliable and robust sensing. The PCF is fabricated using fused silica as the cladding material, leveraging its low optical losses, transparency, chemical stability, and high-temperature resistance. The invention also encompasses the methodology for sample preparation using phosphate buffered saline (PBS) and the application of Finite Element Method (FEM) for accurate simulation and optimization of the sensor's performance, including the use of Perfectly Matched Layers (PML) to enhance simulation realism. The sensor is designed to detect COVID-19 by sensing the interaction of the analyte with S1-RBD, providing a direct measure of viral presence across various concentrations.

BRIEF DESCRIPTION OF DRAWINGS
Fig. 1 depicts the COVID-19 PCF design (a) Cross section 2D view (b) 3D view.
Fig. 2 depicts the Coarse mesh view of the proposed COVID-19 PCF sensor.
Fig. 3 depicts confinement of the electric field (a) Core (Analyte) Mode (b) Defect Mode (c) Coupling Mode.
Fig. 4 (b) depicts superimposition of docked complexes Silica with RBD (Receptor Binding Domain) of Spike protein.
Fig. 5 depicts diverse binding sites on the silica with the spike protein.
Fig. 6 depicts (a)Real (b)Imaginary part of Effective RI of the Analyte(core) mode vs Wavelength.
Fig. 7 depicts (a)Real (b)Imaginary part of Effective RI of the Defect mode vs Wavelength.
Fig. 8 depicts coupling between Analyte (core) and defect mode vs wavelength for threshold analyte concentration.
Fig. 9 depicts Loss of (a) Analyte (core) mode (b) defect mode vs wavelength.
Fig. 10 depicts propagation constant of (a) Analyte (core) mode (b) Defect mode vs Wavelength.
Fig. 11 depicts Transmittance of (a) COVID-19 Analyte (core) mode (b) Defect mode vs Wavelength.
Fig. 12 depicts V-parameter of (a)Analyte (core) mode (b) Defect mode vs Wavelength.
Fig. 13 depicts amplitude sensitivity of (a) Analyte (core) mode (b) defect mode vs wavelength.
Fig. 14 depicts Analyte RI Vs Resonance wavelength.
Fig. 15 depicts wavelength sensitivity of the proposed sensor vs Resonance wavelength.
Fig. 16 depicts Sensitivity Vs Concentration of the COVID-19 analyte samples.

DETAILED DESCRIPTION OF THE INVENTION WITH ILLUSTRATIONS AND EXAMPLES
While the invention has been disclosed with reference to certain embodiments, it will be understood by those skilled in the art that various changes may be made, and equivalents may be substituted without departing from the scope of the invention. In addition, many modifications may be made to adapt to a particular situation or material to the teachings of the invention without departing from its scope.

Throughout the specification and claims, the following terms take the meanings explicitly associated herein unless the context clearly dictates otherwise. The meaning of “a”, “an”, and “the” include plural references. Additionally, a reference to the singular includes a reference to the plural unless otherwise stated or inconsistent with the disclosure herein.
Accordingly, the present invention provides a novel defect mode-based photonic crystal fiber (PCF) sensor device for the detection of COVID-19, and a method thereof. The inventive device and system are characterized by enhanced sensitivity, improved specificity, superior biocompatibility, simplified functional operation, and excellent optical transparency, thereby obviating drawbacks inherent in prior art COVID-19 detection methodologies.
The present invention also provides a system for detecting COVID-19,comprising the photonic crystal fiber (PCF) sensor device as described herein; a sample preparation unit configured to prepare a sample analyte, optionally utilizing phosphate buffered saline (PBS); and a detection unit operatively coupled to said PCF sensor device, said detection unit configured to measure changes in light propagation within the PCF sensor device and to process said measurements to determine the presence and concentration of COVID-19 in the sample analyte.
Photonic Crystal Fiber Sensors
Design
The defect mode-based PCF COVID-19 sensor is shown in 2D cross-sectional view in Figure 1 (a) and 3D in Figure 1 (b). The sensor has three hole layers, with three deleted from the second layer to generate the fault mode. Two bigger air holes (d3) is in the range of 1.8 - 2.2 µm, preferably of 2 µm diameter are inserted to enhance this defect mode. The size of the air holes in the third layer is in the range of 1.2 - 1.6 µm, preferably 1.5 µm (d2), whereas the center core holding the COVID-19 sample analyte is in the range of 0.5-0.8 µm, preferably 0.6 µm (d1). PCF's hexagonal lattice structures allow accurate light propagation modification and improving sensor performance. In Figure 1, the analyte of the core is yellow, the silica is grey, and the air holes are blue. Variations in air hole size and flaws affect COVID-19 analyte sensitivity. Table 1 shows all COVID-19 analyte concentrations and Refractive Indices (RI) [20]. The circular core PCF structure, coupled to the defect section, allows for more reliable and robust sensing. In present invention the FEM utilizes the fused silica as a lossless material.
Table 1: RIs of spike RBD at different molar concentrations

COVID-19 spike RBD glycoprotein
Molar Concentration
(nM) RI
0 1.3348 (PBS)
1.953125 1.335175a
3.90625 1.335550
7.8125 1.336300
15.625 1.337800
31.25 1.340800
62.5 1.346800

(Specifies the critical molar concentrations used to ascertain if an individual is COVID-19 positive or negative. Greater concentrations indicate the extent of the illness)
Phosphate buffered saline (PBS) and normal saline preserve the stability and integrity of viral RNA, yielding results comparable to those obtained with more commonly used transport medium. They describe practical and cost-effective ways to store and transport NP/OP samples throughout the epidemic. After dissolving in sterile PBS, analytes are introduced into the core for detection. Additionally, a Perfectly Matched Layer (PML) reduces surface non-physical radiation impacts. This layer carefully added post-convergence testing to improve simulation accuracy. PML at the border and light coupling from the PCF core absorb distributed evanescent fields beyond the computing region. Though not used in sensor fabrication, PML improves simulation realism. Importantly, mesh element size affects guided mode behavior.
Figure 2 shows a coarser mesh size, which sacrifices element count, improves calculations while properly mapping tiny air-holes. Convergence tests with optimal PML mesh size showed 3340 triangles, 514 edge elements, and 148 vertex elements, with a 162.3 µm² mesh area carefully examined throughout simulation. Figure 2 Coarse mesh view of the COVID-19 PCF sensor. Figure 3 Confinement of the Electric Field (a) Core (Analyte) Mode (b) Defect Mode (c) Coupling Mode. Fused silica is the primary PCF cladding material because to its low optical losses, transparency, and chemical stability. PCFs sustain high temperatures without affecting performance, and their simplicity of manufacture and compatibility with optical components simplify production and integration. Silica is appropriate for PCF cladding because of these qualities, enabling the construction of high-performance optical devices for many applications. Because of its advantages, in the present invention silica is used for cladding. Silica has excellent cladding properties, the COVID-19 sample is docked with S1-RBD, which is essential for detecting COVID-19 with silica. Table 2 lists the parameters that show the sample's different interaction with silica, including non-covalent bonds and S1-RBD ((Receptor Binding Domain) binding affinity.

Table 2 Docking score and energies of silica molecule complexed with S1 protein

Sr. No Complex Binding affinity
(kcal/mol) Spike residue Bond Distance (D-A) Donor (D) atom Acceptor (A) atom
1
Complex 1 -2.6 THR 345 3.23 3 [O] 120 [O]
ARG 346 3.09 133[N] 2[O]
ARG 346 3.45 136 [N] 2 [O]
TYR 451 3.25 2 [O] 1162 [O]
ARG 509 3.11 1741[N] 3 [O]
2 Complex 2 -2.5 PHE 347 3.05 3[O2] 146[O]
ASN 450 3.03 2[O2] 1147[O]
ASN 450 2.98 1146[N] 3[O]
3 Complex 3 -2.6 ARG 346 3.15 133[N] 3[O]
ARG 346 3.26 136[N] 3[O]
LEU 441 3.17 2[O2] 1061[O]
ASN 448 3.97 1121[N] 3[O]
ASN 450 3.94 3[O2] 1147[O]
4 Complex 4 -2.5 GLY 496 2.89 1610[N] 3[O]
TYR 505 2.96 2[O2] 1687[O]
5 Complex 5 -2.4 ARG 346 3.09 136[N] 2[O]
ASP 442 2.98 3[O] 1073[O]
ASN 448 3.16 1121[N] 2[O]

Mathematical Initialization:
In the present invention the PCF-COVID-19 sensor utilizes fused silica. The use of the Sellmeier equation facilitates the determination of the ideal refractive index (RI) for different wavelengths by establishing a connection between wavelength and RI. The formula is located below reference.
n^2 (λ)=1+(B_1 λ^2)/(λ^2-C_1 )+(B_2 λ^2)/(λ^2-C_2 )+(B_3 λ^2)/(λ^2-C_3 ) (1)
The RI of fused silica specified by using Sellmeier's equation, with constants B1, B2, B3, C1, C2, and C3 in Equation (1) found as 0.6961663, 0.4079426, 0.8974794, 0.0684043, 0.1162414, and 9.896161. Additionally, the yellow zone represents the 0.6 µm wide core area where the analyte is injected for measurement. Air holes are spaced apart by 1.1 µm, known as the pitch (Λ).
Confinement loss refers to the specific loss of light transmission that is unable to diffuse. The CL may be determined by height, diameter, air-hole structure, etc. Peak CL measurement evaluates PCF-COVID-19 sensor capabilities. The cladding region's heightened evanescent field affects the CL that improves sensitivity. CL (α) is measured using the formula below.
α(x,y)=8.686*2π/λ Im(n_eff )*10^6 (2)
The wave number in free space is K0=2π/λ, and the imaginary component of the RI is Im(neff). λ in µm represents the incident wavelength. A significant factor in designing and studying the PCF-COVID-19 sensor is the propagation constant, β. This parameter fully describes the electromagnetic wave's behavior in the complicated fiber structure. Propagation constant is crucial to PCF fiber performance optimization and understanding. Equation 3 calculates electromagnetic wave propagation constant.
β=n_eff 2π/λ (3)
Where neff is the effective refractive index and λ is the µm propagation wavelength. Transmittance is the fraction of incoming light that passes through fiber intact or scattered in PCF. It's crucial to PCF optical transmission performance and efficiency. Equation 4 [34] calculates PCF light transmission.
T_r (dB)=10X〖 log〗_10 (P_out/P_in ) (4)
Pin and Pout are maximum input and output power. Maximizing transmittance reduces confinement loss and ensures PCF-COVID-19 sensor performance. A PCF-sensor's "V parameter" is the normalized frequency parameter (Veff), which specifies the optical modes' guiding properties. Equation 5 yields the dimensionless Veff parameter.
V_eff=2π/λ √(n_1^2-n_2^2 ) (5)

The core and cladding have RIs of n1 and n2, respectively, where λ is the guided light wavelength in µm. A specified operational wavelength supports amplitude sensivity (AS), a modified inquiry approach. Since AS questioning does not need the spectral shift, it reduces rate and facility. AS is the most common sensor performance parameter. AS is calculated using this equation.
〖 S〗_a (〖RIU〗^(-1) )=1/α_c (∆α_c)/∆n (6)
CL is represented as αC, and its fluctuation is shown as ∆αc. Wavelength sensitivity (WS) is a well-defined term for resonance wavelength fluctuation in peak wavelength relative to analyte RI change. One important restriction of the wavelength interrogation technique for performance evaluation is the WS (Sλ).
S(λ)= Δλ/Δn (7)
Where Δn denotes the change in two distinct neighbouring RI and Δλ peak indicates the peak wavelength fluctuation.

Results
Refined Sensing Mechanism through Molecular Docking
Performance analysis of silica as cladding material for spike protein analyte Detection:
Five complexes of silica and S1-RBD formed by computational molecular docking research revealed silica's sensor cladding efficiency.
Figure 4 Superimposition of docked complexes Silica with RBD domain of Spike protein: Silica molecule and RBD protein side-chain atoms form a hydrogen bond (Figure 4). Analysis of silica's non-covalent interactions with spike-RBD (Receptor Binding Domain) is crucial for the biosensor analyte detection. Table 2 shows how intermolecular interactions were used to measure and assess the silica interface. Using spike residues THR 345, ARG 346, TYR 451, and ARG 509, complex 1 bound strongly at -2.6 kcal/mol. PHE 347 and ASN 450 spike residues gave Complex 2 a decreased binding affinity of -2.5 kcal/mol. Complex 3 spike residues ARG 346, LEU 441, ASN 448, and ASN 450 and bound Complex 1 at -2.6 kcal/mol. Complex 4's spike residues GLY 496 and TYR 505 allowed a -2.5 kcal/mol binding affinity. The spike residues ARG 346, ASP 442, and ASN 448 bound to Complex 5 at -2.4 kcal/mol. In our viral spike protein sensor application, silica works well as a cladding material. Silica nanoparticles can grab and immobilize spike proteins, enabling sensitive and selective detection, as shown by Complexes 1 and 3. The discovery of critical spike residues like ARG 346 and ASN 450 in these complexes shows how silica targets certain spike protein epitopes. Even though complexes 2, 4, and 5 have lesser binding affinities, silica and spike proteins interact.
Table 2 Docking score and energies of silica molecule complexed with S1 protein
Sr. No Complex Binding affinity (kcal/mol) Spike residue Bond Distance (D-A) Donor
(D) atom Acceptor (A) atom
1
Complex 1 -2.6 THR 345 3.23 3 [O] 120 [O]
ARG 346 3.09 133[N] 2[O]
ARG 346 3.45 136 [N] 2 [O]
TYR 451 3.25 2 [O] 1162 [O]
ARG 509 3.11 1741[N] 3 [O]
2 Complex 2 -2.5 PHE 347 3.05 3[O2] 146[O]
ASN 450 3.03 2[O2] 1147[O]
ASN 450 2.98 1146[N] 3[O]
3 Complex 3 -2.6 ARG 346 3.15 133[N] 3[O]
ARG 346 3.26 136[N] 3[O]
LEU 441 3.17 2[O2] 1061[O]
ASN 448 3.97 1121[N] 3[O]
ASN 450 3.94 3[O2] 1147[O]
4 Complex 4 -2.5 GLY 496 2.89 1610[N] 3[O]
TYR 505 2.96 2[O2] 1687[O]
5 Complex 5 -2.4 ARG 346 3.09 136[N] 2[O]
ASP 442 2.98 3[O] 1073[O]
ASN 448 3.16 1121[N] 2[O]

Figure 5 shows the diverse binding sites on the silica with the spike protein. Silicon can accommodate spike protein binding sites and distinguish viral strains with distinct spike protein sequences. Two to four connections are found at the spike-silica complex interface, compared to two hydrophobic interactions at the S1-RBD residues between 345th and 505th positions. Intermolecular interactions connected with interface representations. The results show that silica-based sensors can detect viral infections fast and sensitively. Experimental validation of these computational predictions and sensor design and manufacturing improvements will enable silica-based sensor systems to realize their diagnostic potential in clinical settings and beyond.

Extracted Findings - PCF Simulation:
The real and imaginary parts of the RI versus wavelength graph of PCF sensors, as shown in Figures 6 and 7, are crucial for understanding optical features, especially defect and core modes. This graph shows how the real and imaginary components of the RI fluctuate throughout wavelengths, revealing the material's absorption and dispersion capabilities. These differences directly affect the proposed sensor's COVID-19 analyte detection capability, making them crucial for sensing applications. The real part of the RI indicates light phase velocity inside the fiber, whereas the imaginary part represents light attenuation or absorption. We can assess the sensor's sensitivity to medium changes like analyte concentration or RI by examining these components. Figures 6 and 7 show significant patterns in the real and imaginary RI for defect and core modes. The resonance state may change with real part variations, altering the proposed sensor's sensitivity to COVID-19 analytes with varied concentrations. Changes in the imaginary component indicate fiber light absorption or loss, affecting the sensor's detection limit and sensitivity. In PCFs, "coupling between core and defect modes" refers to the complex interaction between guided modes in the fiber structure. PCFs' periodic air holes provide a photonic bandgap that limits wavelengths. However, isolated flaws enable defect modes to propagate inside this bandgap. The coupling phenomenon occurs when the core's directed modes and the defects supported modes overlap spatially. Through energy transfer and interaction between modes, this overlap causes optical phenomena including mode conversion and resonant coupling. Understanding and manipulating this coupling mechanism is crucial for using PCFs in sensing and customized control of the fiber's optical behavior and functions. Figure 8 illustrates the complex relationship between the sensor's electric field of the core and defect modes' basic effective RI. This visualization shows the intricacies of RI fluctuations in various modes and the outstanding guiding properties of the deliberately designed cladding holes. The graphic shows the sensor's amazing light-guiding capacity by showing core mode and defect mode RI fluctuations. Specifically for the threshold analyte concentration of 1.953125 nM, the figure reveals the resonance condition's state. The sensor's response to analyte concentrations within a wavelength range of 1.2 μm to 2.5 μm and a refractive index of 1.335175 is shown in the figure. Figure 8 helps comprehend and optimize core-defect mode coupling, improving the sensor's capabilities for many applications, including very sensitive analyte detection.
Figure 8 illustrates the complex relationship between the sensor's electric field of the core and defect modes' basic effective RI. This visualization shows the intricacies of RI fluctuations in various modes and the outstanding guiding properties of the deliberately designed cladding holes. The graphic shows the sensor's amazing light-guiding capacity by showing core mode and defect mode RI fluctuations. Specifically for the threshold analyte concentration of 1.953125 nM, the figure reveals the resonance condition's state. The sensor's response to analyte concentrations within a wavelength range of 1.2 μm to 2.5 μm and a refractive index of 1.335175 is shown in the figure. Figure 8 helps comprehend and optimize core-defect mode coupling, improving the sensor's capabilities for many applications, including very sensitive analyte detection.
The propagation constant versus wavelength graph in Figure 10 helps explain light transmission in PCF COVID-19 sensors. This graph shows how the propagation constant, which measures light propagation through the fiber, changes depending on wavelength. Graph irregularities indicate areas of increased or decreased light propagation efficiency, but the findings show none. Since it affects light transmission into the COVID-19 analyte sample and detection sensitivity, understanding this connection is essential for enhancing proposed sensor performance. The graph helps build and use the suggested PCF COVID-19 sensor for increased sensing with high sensitivity of 17282nm/RIU by pinpointing wavelength ranges where the sensor performs best. This picture shows the complex relationship between wavelength and light propagation in the proposed PCF COVID-19 sensor, advancing sensing technology for many applications.
The transmission versus wavelength graph of the proposed PCF-COVID-19 sensor reveals fiber optical performance and behavior. Figure 11 demonstrates PCF sensor light transmission at different wavelengths. Peaks and troughs on the graph reflect high and low transmission modes and resonance situations in the fiber structure. This link must be understood for the sensor to react sensitively and selectively to outside stimuli like RI or analyte concentration changes. Researchers can increase PCF sensor performance by detecting resonance frequencies via transmission spectrum analysis.
The v-parameter is a key indication of fiber mode propagation in PCF optics. The v-parameter graph in Figure 12 plotted versus wavelength is used to examine this connection. The PCF enters a single-mode regime when the v-parameter drops below 4.1, corresponding to particular wavelength ranges. Light energy is contained in a single guided mode throughout this transition, simplifying light transmission and improving analyte regime coherence. Optical sensing applications need understanding this critical threshold. Single-mode propagation minimizes dispersion and distortion, making PCFs with v-parameters < 4.1 suitable for long-distance high-fidelity light transmission. Single-mode PCFs are also vital for sensor and laser technologies that need precise light propagation control. The present invention emphasizes the v-parameter graph's diagnostic value for PCF design and optimization.
Figure 13 shows the sensor profile's dynamic sensitivity throughout wavelengths, with distinct peaks and troughs. These variations demonstrate the wavelength-dependent sensitivity of the proposed PCF COVID-19 sensor to analyte characteristics. Understanding this complex connection is crucial for improving sensor performance and customizing detection methods. PCF sensors can detect target analytes with high precision using their wavelength-dependent sensitivity. Thus, this graphical representation guides PCF-based sensing platform optimization for environmental monitoring, biological diagnostics, and COVID-19 sensing.
At resonance wavelengths of 1.25 μm, 1.30 μm, 1.35 μm, 1.40 μm, 1.45 μm, 1.50 μm, and 1.55 μm, the suggested structure shows similar amplitude sensitivities. These wavelengths have amplitude sensitivities of -4041 RIU-1, -1993 RIU-1, -1127 RIU-1, -1020 RIU-1, -803 RIU-1, -217 RIU-1, and -47 RIU-1. These sensitivity measurements show the sensor's responsiveness throughout the resonant wavelengths, exhibiting differing degrees of sensitivity within the measured range. The present invention examined PCF resonance wavelength and COVID-19 analyte RI. Figure 14 shows that the PCF's resonance wavelength shifted correspondingly with COVID-19 analyte RI. This phenomenon suggests that PCF-based sensing devices may detect COVID-19 analytes' RI fluctuations (Table 1), allowing label-free and extremely sensitive detection approaches. Understanding this link helps create a PCF biosensor for quick and precise detection of COVID-19 and additional SARS viruses with the same spike protein, advancing pandemic diagnostic technology
Table 3 Comparative Sensitivity Analysis of PCF Sensors for COVID-19 Detection
Type of sensor Class of virus Diagnosed molecules Sensitivity
(nm/RIU) Cladding material SPR Material Reference
D-shaped SPR-PCF sensor H5N1, H5N2, H9N2, H4N6, FAdV & IBV - 40,141.76 Silica Gold [28]
Photonic quasi crystal fiber-SPR-SENSOR H5N1, H5N2, H9N2, H4N6, FAdV & IBV - 1172 Silica Gold [2]
D-shaped –multi-layered SPR-PCF sensor SARS-CoV-2 Spike-protein-RBD 2380 Silica Gold, BaTiO3 & Graphene [27]
Proposed sensor SARS-CoV-2 Spike protein- RBD 17282 Silica - -
Compare noble metal SPR virus sensors in Table 3. It beats gold-detecting sensors. [27] and the COVID-19 sensor utilize PBS, whereas [28] and [2] use EID concentrations. Novel COVID-19 sensors outperform noble metal sensors at 17282 nm/RIU. Compare noble metal SPR virus sensors in Table 3. It beats gold-detecting sensors. [27] and the COVID-19 sensor utilize PBS, whereas 28 and 2 use EID concentrations. Novel COVID-19 sensors outperform noble metal sensors at 17282 nm/RIU. Gold sensors are 1172–40,141.76 nm/RIU sensitive. The sensor's sensitivity exceeds these values by a wide margin due to its simplicity, ease of production, and cost-effectiveness by employing silica instead of precious metals. The sensor can detect SARS-CoV-2's slight refractive index changes due to its great sensitivity. SARS-CoV-2 Spike protein RBD is detected by this sensor. Unlike sensors targeting viral components, this chemical target improves selectivity and lowers false positives and negatives. In Table 3, gold is a typical SPR material, yet the suggested sensor does not mention it, indicating material selection or sensor design innovation. Sensor may be more sensitive and perform better than Agarwal et al. [38]. The sensor's high sensitivity, specificity, and perhaps unique design and material may detect SARS-CoV-2. Its exceptional performance shows that our COVID-19 sensor might revolutionize viral detection, improving infectious disease diagnostic accuracy, sensitivity, and reliability. PCF's wavelength sensitivity and resonance wavelength are crucial to its optical behaviour and COVID-19 analyte detection in the suggested structure as shown in Figure 15. Wavelength sensitivity assesses fiber response to external stimuli, whereas resonance wavelength demonstrates PCF cladding constructive interference. Determine how wavelength sensitivity affects COVID-19 sample concentration. Since the pandemic is widespread, sensor accuracy and effectiveness must improve. Figure 16. Sample wavelength sensitivity increased with concentration from 0-1.95313 to 3.90625-7.8125 to 15.65, 15.65 to 31.25, and 31.25 to 62.5. Wavelength sensitivity closely linked with COVID-19 sample content. As COVID-19 sample concentration grew, resonance wavelengths prolonged and analytes changed. This habit has various causes. Light propagation affected by analyte concentration and molecular environment. Sample-cladding intermolecular interactions and analyte wavelength response may vary with concentration. Docking shows silica cladding-analyte interaction. Max sensor sensitivity is 17282 nm/RIU.

Conclusion:
Coronavirus specimens' primary analyte is identified by PCF-COVID-19. A defect-based PCF-COVID-19 sensing approach worked for concentration refractive indices. This sensor detects RBD protein from SARS-CoV-2 spikes. This sensor detects lower concentrations and indicates COVID-19 over the threshold. Quantifies positive and negative coronavirus particles in a sample. Bio particle counters may be interesting for antibody and vaccination. The FEM numerically analyzed confinement loss curves and spectrum. The average spike protein wavelength sensitivity is 17282 nm/RIU. Protein spike amplitude sensitivity resembles -47 RIU-1. In low-resource hospitals, the sensor will outperform viral tests and be portable. Cheap without costly metals or elegance.

Advantages of Present Invention:
The present invention provides a defect mode-based photonic crystal fiber (PCF) sensor device, system, and method for COVID-19 detection, offering several significant advantages over existing technologies, including:
Enhanced Sensitivity: The strategic design incorporating a defect region with larger air holes significantly alters light propagation, rendering the sensor highly sensitive to minute changes in the refractive index of the sample analyte, thereby enabling detection of lower concentrations of COVID-19 analytes.
Improved Specificity: The sensor is specifically designed to detect the interaction of the COVID-19 sample analyte with S1-RBD, a crucial viral component, which enhances the specificity of detection and reduces the likelihood of false positives or negatives.
Superior Biocompatibility: The use of fused silica as the primary cladding material ensures excellent biocompatibility, making the device suitable for biological sample analysis.
Simplified Functional Operation: The design and methodology contribute to a simplified functional operation, which can lead to easier deployment and use.
Excellent Optical Transparency: Fused silica's inherent optical transparency, coupled with the optimized PCF structure, ensures efficient light transmission and detection.
Cost-Effectiveness and Ease of Production: By utilizing fused silica instead of costly noble metals (like gold, commonly used in SPR sensors), the invention offers a more economical and simpler manufacturing process.
Robust and Reliable Sensing: The circular core PCF structure, coupled with the precisely engineered defect section, allows for more reliable and robust sensing performance.
Label-Free Detection: The sensor's ability to detect refractive index fluctuations directly allows for label-free detection approaches, simplifying the testing process.
Portability: The inherent nature of PCF sensors and the absence of complex, bulky components suggest potential for portability, making it suitable for use in low-resource settings.
High Wavelength Sensitivity: The sensor demonstrates a high wavelength sensitivity indicating its strong response to changes in analyte concentration.
, Claims:1. A defect mode-based photonic crystal fiber (PCF) sensor device for covid-19 detection, comprising:
- a central core region configured to receive a sample analyte
- a cladding material comprising fused silica, concentrically surrounding said central core region;
- a plurality of air holes arranged in a hexagonal lattice pattern within said cladding material, forming at least three concentric layers around the central core;
wherein a defect mode is generated by deleting at least three air holes from a second layer of the plurality of air holes; and at least two larger air holes having a third diameter (d3) inserted within the region of the deleted air holes in the second layer, configured to enhance the defect mode within the PCF, said defect mode configured to significantly alter light propagation within the fiber, thereby rendering the device highly sensitive to minute changes in a refractive index of the sample analyte introduced into the central core, and further configured to detect COVID-19.
2. The sensor device as claimed in claim 1, wherein the first diameter (d1) of the central core is in the range of 0.5-0.8 µm.
3. The sensor device as claimed in claim 1, wherein air holes in a third layer, concentric to the second layer, have a second diameter (d2) is in the range of 1.2 - 1.6 µm.
4. The sensor device as claimed in claim 1, wherein the third diameter (d3) of the at least two larger air holes is in the range of 1.8 - 2.2 µm.
5. The sensor device as claimed in claim 1, wherein the sensor is configured to detect covid-19 by sensing the interaction of the covid-19 sample analyte with s1-rbd (receptor binding domain).
6. A method for detecting covid-19 using a defect mode-based photonic crystal fiber (pcf) sensor device, comprising the steps of:
- preparing a covid-19 sample by dissolving it in a sterile solution, preferably phosphate buffered saline (pbs) or normal saline;
- introducing the prepared covid-19 sample into a central circular core of a pcf sensor, the sensor comprising a silica backdrop material, a central circular core having a first diameter (d1), and a plurality of air holes arranged in a hexagonal lattice pattern with at least three concentric layers, wherein a defect mode is generated by deleting at least three air holes from a second layer and enhanced by inserting at least two larger air holes having a third diameter (d3) within the region of the deleted air holes; propagating light through the pcf sensor, wherein the light interacts with the covid-19 sample analyte via the enhanced defect mode; and detecting changes in the refractive index of the covid-19 sample analyte based on the light propagation characteristics, thereby indicating the presence and concentration of covid-19.
7. The method as claimed in claim 6, further comprising simulating the performance of the pcf sensor using the finite element method (fem), including the use of a perfectly matched layer (pml) to enhance simulation accuracy.
8. The method as claimed in claim 6, wherein the fem simulation utilizes a mesh comprising 3340 triangles, 514 edge elements, and 148 vertex elements, with a mesh area of 162.3 µm².
9. The method as claimed in claim 6, wherein the detection of covid-19 involves sensing the interaction between the covid-19 sample analyte and s1-rbd.