Plasmonic refractive index sensing in the early diagnosis of diabetes, anemia, and cancer: An exploration of biological biomarkers

Rahad, Rummanur; Rakib, A.K.M.; Haque, Md. Anwarul; Sharar, Shadman Shahriar; Sagor, Rakibul Hasan

doi:10.1016/j.rinp.2023.106478

Cited by 52 publications

(10 citation statements)

References 68 publications

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“…The shift in the resonant wavelengths is a consequence of the FP cavity-like structure responding to changes in n. This particular attribute underscores the practicality of MZI #6 in detecting variations in refractive index, particularly in the context of numerous biological applications. For example, it can distinguish cancerous skin cells (n=1.38) from healthy skin cells (n=1.36), as well as differentiate various components of blood, such as water (n=1.33), red blood cells (n=1.34), plasma (n=1.35), white blood cells (n=1.36), and hemoglobin (n=1.38) [54]. Figure 4 provides a clear representation of how the resonant wavelengths adapt in response to changes in the refractive index of biological components.…”

Section: Schematics Simulation Results and Spectrum Responses Of The ...mentioning

confidence: 99%

Plasmonic Mach-Zehnder Interferometers Based on Air-Gap Couplers

Wahsheh

2023

IEEE Photonics J.

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Mach-Zehnder interferometers (MZIs) are vital in optical biosensor applications and high-density integrated photonic circuits. In this research work, we theoretically investigate the design steps of MZIs, consisting of 3-dB plasmonic splitters sandwiched between two dielectric waveguides with an air-gap coupler at the interface from each side. The proposed MZI designs feature a compact size, ensuring high transmission coupling efficiency without introducing additional radiation or reflection losses, as observed in tapered, T-and Y-shaped splitters. The analytical results and simulations prove that the proposed MZI designs offer a broad spectrum range with a high fabrication tolerance and the ability to use them in all-optical plasmonic circuits.

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Section: Schematics Simulation Results and Spectrum Responses Of The ...mentioning

confidence: 99%

Plasmonic Mach-Zehnder Interferometers Based on Air-Gap Couplers

Wahsheh

2023

IEEE Photonics J.

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“…To show the efficiency of this sensor, concentrations from 5% to 20% were considered and the corresponding response diagram is shown in figure 10. You can use the equation ( 5) to determine the refractive index for different concentration level of glucose [37]…”

Section: Tmoke Response To the Concentration Level Of Glucose And Can...mentioning

confidence: 99%

Design of a high-resolution magneto-plasmonic biosensor for analyte detection

Abbasi,

Salehi,

Emami

2024

J. Opt.

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This paper introduces the design of a magneto-plasmonic refractometric sensor aimed at achieving high resolution. This sensor consists of arrays of gold nanowires and layers of SiO2 and Co6Ag94, where the analyte is placed on the gold nanowires. A p-polarized optical field with a wavelength of 631 nm is used to excite the structure, which is applied in the range of 1º to 45º. A magnetic field is applied to z-axis to create the magneto-optical effect. The reflected optical field of the samples is used to calculate the signal of the transverse magneto-optical Kerr effect (TMOKE), which shows significant changes in the refractive index of the samples and the direction of the magnetic field. The highest displacement is 4º. The highest value of the figure of merit (FoM) is 3611 RIU-1, and the maximum sensitivity is obtained as 71 º/RIU.

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“…DL learns rules for inputs and outputs from large amounts of data, enabling the construction of non-linear models for various applications. Deep learning optimization methods can be applied in the fields of metasurface device design, including sensor [22][23][24][25], demultiplexer [26,27], coupler [28,29], inferometer [30], etc, to improve their design efficiency.The use of neural networks to implement data-driven models provides a new approach for the design of electromagnetic structures [31][32][33][34][35][36], such as EIT [37], broadband absorption [38] and perfect absorption [39]. Deep learning uses neural networks to learn patterns in data, and after training and optimizing on a dataset of metasurfaces, neural networks can effectively predict the best metasurface design.…”

Section: Introductionmentioning

confidence: 99%

Optimized design for absorption metasurface based on autoencoder (AE) and BiLSTM-Attention-FCN-Net

Zhu,

Du,

Dong

et al. 2024

Phys. Scr.

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In order to speed up the process of optimizing design of metasurface absorbers, an improved design model for metasurface absorbers based on autoencoder (AE) and BiLSTM-Attention-FCN-Net (including bidirectional long-short-term memory network, attention mechanism, and fully-connection layer network) is proposed. The metasurface structural parameters can be input into the forward prediction network to predict the corresponding absorption spectra. Meantime, the metasurface structural parameters can be obtained by inputting the absorption spectra into the inverse prediction network. Specially, in the inverse prediction network, the bidirectional long-short-term memory (BiLSTM) network can effectively capture the context relationship between absorption spectral sequence data, and the attention mechanism can enhance the BiLSTM output sequence features, which highlight the critical feature information. After the training, the mean square error (MSE) value on the validation set of the reverse prediction network converges to 0.0046, R2 reaches 0.975, and our network can accurately predict the metasurface structure parameters within 1.5s with a maximum error of 0.03mm. Moreover, this model can achieve the optimal design of multi-band metasurface absorbers, including the single-band, dual-band, and three-band absorptions. The proposed method can also be extended to other types of metasurface optimization design.

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Plasmonic refractive index sensing in the early diagnosis of diabetes, anemia, and cancer: An exploration of biological biomarkers

Cited by 52 publications

References 68 publications

Plasmonic Mach-Zehnder Interferometers Based on Air-Gap Couplers

Plasmonic Mach-Zehnder Interferometers Based on Air-Gap Couplers

Design of a high-resolution magneto-plasmonic biosensor for analyte detection

Optimized design for absorption metasurface based on autoencoder (AE) and BiLSTM-Attention-FCN-Net

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