In this article, a hybrid ${\mathrm{TiO}}_2$/Au/graphene layer-based surface plasmon resonance (SPR) sensor with improved sensitivity and capability for cancer detection is presented. The finite element method (FEM) was used for numerical analysis. The proposed SPR biosensor was structured based on the angular analysis of the attenuated total reflection (ATR) method for the detection of various types of cancer using the refractive index component. The resonance angle shifted owing to the increment of normal and cancerous cells’ refractive index, which varied between 1.36 and 1.401 for six different types of normal and cancerous cells. According to numerical results, the obtained sensitivities for skin (basal), cervical (HeLa), adrenal gland (PC12), blood (Jurkat), and breast (MCF-7 and MDA-MB-231) cancer cells were 210 deg/RIU, 245.83 deg/RIU, 264.285 deg/RIU, 285.71 deg/RIU, 292.86 deg/RIU, and 278.57 deg/RIU, respectively. Furthermore, the detection accuracy (DA), figure of merits (FOM), and signal-to-noise ratio (SNR) were also obtained, with values of 0.263 deg⁻¹, 48.02 RIU⁻¹, and 3.84, respectively. Additionally, the distribution of the electric field and the propagation of the magnetic field for resonant and non-resonant conditions of the proposed structure were illustrated. It was found that an enhanced field was exhibited on the surface of the plasmonic material for resonant conditions. We also measured the penetration depth of 180 nm using decayed electric field intensity. Furthermore, the impact of using a ${\mathrm{TiO}}_2$/Au/graphene layer was demonstrated. We further conducted analyses of the effects of the thickness of the gold layer and the effects of additional graphene layers on overall sensitivities for six different types of cancer. The proposed T${\mathrm{iO}}_2$/Au/graphene layered structure exhibited the highest overall sensitivity in terms of detecting cancerous cells from healthy cells. Moreover, the proposed sensor was numerically analyzed for a wide range of biological solutions (refractive index 1.33–1.41), and the sensor linearity was calculated with a linear regression coefficient (R²) of 0.9858. Finally, numerical results obtained in this manuscript exhibited high sensitivity in comparison with previously reported studies.

In this paper, a highly sensitive graphene-based multiple-layer (BK₇/Au/PtSe₂/Graphene) coated surface plasmon resonance (SPR) biosensor is proposed for the rapid detection of the novel Coronavirus (COVID-19). The proposed sensor was modeled on the basis of the total internal reflection (TIR) technique for real-time detection of ligand-analyte immobilization in the sensing region. The refractive index (RI) of the sensing region is changed due to the interaction of different concentrations of the ligand-analyte, thus impacting surface plasmon polaritons (SPPs) excitation of the multi-layer sensor interface. The performance of the proposed sensor was numerically investigated by using the transfer matrix method (TMM) and the finite-difference time-domain (FDTD) method. The proposed SPR biosensor provides fast and accurate early-stage diagnosis of the COVID-19 virus, which is crucial in limiting the spread of the pandemic. In addition, the performance of the proposed sensor was investigated numerically with different ligand-analytes: (i) the monoclonal antibodies (mAbs) as ligand and the COVID-19 virus spike receptor-binding domain (RBD) as analyte, (ii) the virus spike RBD as ligand and the virus anti-spike protein (IgM, IgG) as analyte and (iii) the specific probe as ligand and the COVID-19 virus single-standard ribonucleic acid (RNA) as analyte. After the investigation, the sensitivity of the proposed sensor was found to provide 183.33°/refractive index unit (RIU) in SPR angle (θ_SPR) and 833.33THz/RIU in SPR frequency (SPRF) for detection of the COVID-19 virus spike RBD; the sensitivity obtained 153.85°/RIU in SPR angle and 726.50THz/RIU in SPRF for detection of the anti-spike protein, and finally, the sensitivity obtained 140.35°/RIU in SPR angle and 500THz/RIU in SPRF for detection of viral RNA. It was observed that whole virus spike RBD detection sensitivity is higher than that of the other two detection processes. Highly sensitive two-dimensional (2D) materials were used to achieve significant enhancement in the Goos-Hänchen (GH) shift detection sensitivity and plasmonic properties of the conventional SPR sensor. The proposed sensor successfully senses the COVID-19 virus and offers additional (1 + 0.55) × L times sensitivity owing to the added graphene layers. Besides, the performance of the proposed sensor was analyzed based on detection accuracy (DA), the figure of merit (FOM), signal-noise ratio (SNR), and quality factor (QF). Based on its performance analysis, it is expected that the proposed sensor may reduce lengthy procedures, false positive results, and clinical costs, compared to traditional sensors. The performance of the proposed sensor model was checked using the TMM algorithm and validated by the FDTD technique.

This paper provides a simple hybrid design and numerical analysis of the graphene-coated fiber-optic surface plasmon resonance (SPR) biosensor for breast cancer gene-1 early onset (BRCA1) and breast cancer gene-2 early onset (BRCA2) genetic breast cancer detection. Two specific mutations named 916delTT and 6174delT in the BRCA1 and BRCA2 are selected for numerical detection of breast cancer. This sensor is based on the technique of the attenuated total reflection (ATR) method to detect deoxyribonucleic acid (DNA) hybridization along with individual point mutations in BRCA1 and BRCA2 genes. We have numerically shown that momentous changes present in the SPR angle (minimum: 135% more) and surface resonance frequency (SRF) (minimum: 136% more) for probe DNA with various concentrations of target DNA corresponding to a mutation of the BRCA1 and BRCA2 genes. The variation of the SPR angle and SRF for mismatched DNA strands is quite negligible, whereas that for complementary DNA strands is considerable, which is essential for proper detection of genetic biomarkers (916delTT and 6174delT) for early breast cancer. At last, the effect of electric field distribution in inserting graphene layer is analyzed incorporating the finite difference time domain (FDTD) technique by using Lumerical FDTD solution commercial software. To the best of our knowledge, this is the first demonstration of such a highly efficient biosensor for detecting BRCA1 and BRCA2 breast cancer. Therefore, the proposed biosensor opens a new window toward the detection of breast cancers.

This paper presents a performance comparison of heterostructure surface plasmon resonance (SPR) biosensors for the application of Novel Coronavirus SARS-CoV-2 diagnosis. The comparison is performed and compared with the existing literature based on the performance parameters in terms of several prisms such as BaF₂, BK₇, CaF₂, CsF, SF₆, and SiO₂, several adhesion layers such as TiO₂, Chromium, plasmonic metals such as Ag, Au, and two-dimensional (2D) transition metal dichalcogenides materials such as BP, Graphene, PtSe₂ MoS₂, MoSe₂, WS₂, WSe₂. To study the performance of the heterostructure SPR sensor, the transfer matrix method is applied, and to analyses, the electric field intensity near the graphene-sensing layer contact, the finite-difference time-domain approach is utilized. Numerical results show that the heterostructure comprised of CaF₂/TiO₂/Ag/BP/Graphene/Sensing-layer has the best sensitivity and detection accuracy. The proposed sensor has an angle shift sensitivity of 390°/refractive index unit (RIU). Furthermore, the sensor achieved a detection accuracy of 0.464, a quality factor of 92.86/RIU, a figure of merit of 87.95, and a combined sensitive factor of 85.28. Furthermore, varied concentrations (0–1000 nM) of biomolecule binding interactions between ligands and analytes have been observed for the prospects of diagnosis of the SARS-CoV-2 virus. Results demonstrate that the proposed sensor is well suited for real-time and label-free detection particularly SARS-CoV-2 virus detection.

A numerical illustration of a hybrid design and numerical analysis of graphene-coated fiber-optic surface plasmon resonance (SPR) biosensor for BRCA-1 and BRCA-2 genetic breast cancer detection is provided. Two specific mutations named 916delTT in BRCA-1 gene and 6174delT in BRCA-2 gene are being selected for detection of breast cancer numerically. This sensor is based on attenuated total reflection (ATR) method to detect individual point mutations in BRCA-1 and BRCA-2 genes. Based on the numerically obtained results, a momentous change is present in the SPR angle (minimum 35% more) and surface resonance frequency (SRF) (minimum 36% more) for probe DNA with various concentrations of target DNA corresponding to the mutation of the BRCA-1 and BRCA-2 genes. The variation of the SPR angle and SRF for mismatched DNA strands in BRCA-1 and BRCA-2 genes is quite negligible, whereas that for complementary DNA strands is considerable. This considerable change is essential for proper detection of genetic biomarkers (916delTT and 6174delT) for early breast cancer. To the best of our knowledge, this is the first demonstration of such an adept biosensor for detecting BRCA1 and BRCA2 genetic breast cancer. Here, we used graphene as bimolecular acknowledgement element for improving sensor performance. At the end of the article, the performance in terms of sensitivity is analyzed. Therefore, the proposed biosensor opens a window toward detection of early detection of BRCA-1 and BRCA-2 genetic breast cancers.