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Design of THz photonic crystal fiber based biosensor for detection of brain tissues and behavior characterization with Machine learning approach

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Abstract

In this research, we proposed a Terahertz (THz) refractive index-based Hollow-Core Photonic Crystal Fiber (HC-PCF) biosensor for examining various brain cancerous tissues. Six design variants with cladding segments ranging from 4 to 16 are analyzed using the finite element method (FEM). The biosensor demonstrates high sensitivity (94.9 to 97.46%), minimal Effective Mode Loss (EML) of 0.00246 cm−1with an effective mode area of 2.84 × 10−8 m2 and a power core ranges from 93% to 95.9% for the 16-segment cladding. The second contribution involves applying machine learning (ML), utilizing Autoencoder Augmentation Network (AEAN) for data augmentation and Bayesian Ridge Regression Multioutput Regressor (BRRMOR) for rapid prediction of biosensing parameters. The effectiveness of the ML model is demonstrated with a high r2 score of 0.992 for unknown HC-PCF structures, showcasing computational efficiency compared to Finite Element Method simulations.

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The numerical data were created and analyzed in this study, and it is used for Machine Learning. Since it is not published yet, we cannot share the data. Once published, based on request the data can be shared.

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Acknowledgements

N. Ayyanar acknowledges SERB SURE, India, for providing financial assistantships through State University Research Excellence (SUR/2022/003424-G).

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Dhirajlal Gandhi College of Technology, Salem, India

    K. R. Deepa

  2. Department of Electrical and Electronics Engineering, Sona College of Technology, Salem, India

    S. Padma

  3. School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India

    S. Sridevi

  4. Department of Electronics and Communication Engineering, Thiagarajar College of Engineering, Madurai, India

    N. Ayyanar

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  1. K. R. Deepa
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  2. S. Padma
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  3. S. Sridevi
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  4. N. Ayyanar
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Contributions

K.R.D.; N.A. carried out the sensor designing, simulations, performed the graphical analysis and contributed to the final version of the manuscript. S.P. participated in the supervision and drafted the manuscript. S.S. designed the Machine Learning model and analyzed the data. All authors read and approved the final manuscript.

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Correspondence to K. R. Deepa.

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Deepa, K.R., Padma, S., Sridevi, S. et al. Design of THz photonic crystal fiber based biosensor for detection of brain tissues and behavior characterization with Machine learning approach. Opt Quant Electron 56, 430 (2024). https://doi.org/10.1007/s11082-023-06110-y

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