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All Journal Science and Technology Indonesia Emerging Science Journal
Marwan, Arip
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Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Environmental Science Materials Science & Nanotechnology Physics

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Numerical Study of Early Detection of Tuberculosis Infected with High Sensitivity Plasmonic Sensor Irawan, Dedi; Azhar; Ramadhan, Khaikal; Marwin, Azwir; Marwan, Arip
Science and Technology Indonesia Vol. 9 No. 1 (2024): January
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2024.9.1.94-102

Abstract

In this work, a photonic crystal fiber based on a plasmonic sensor for the early detection of tuberculosis has been designed with finite element analysis. The component is constructed with a substrate layer made of fused silica material, which is then coated with a thin film of TiO2 layer as an adhesive layer to strongly attach the Au layer with the silica fiber surface. The TiO2 layer has an optimal thickness of 45 nm, while the Au layer has a thickness of 50 nm. The sensor design has a refractive index (RI) detection range from 1.27 RIU to 1.37 RIU, it also shows a maximum wavelength sensitivity (WS), maximum amplitude sensitivity (AS), sensor resolution (SR), and sensor accuracy (SA) of 20,000 nm/RIU (x-polarized) and 17.000 nm/RIU( y-polarized), -211.38 1/RIU (x-polarized) and -211.211 1/RIU (y-polarized), 9.17 x 10−5 RIU (x-polarized) and 1 x 10−4 RIU (y-polarized), and 0.025/nm respectively. Tuberculosis exhibits a normal and infected RI range of 1.343 RIU to 1.351 RIU. Therefore, the proposed sensor design is capable of detecting four types of TB infections with high sensitivity.
Neural Networks in Optimizing the Performance of the Elliptical-Plasmonic Sensor Ramadhan, Khaikal; Syamsul, Andi M. N. F.; Marwan, Arip; Agustirandi, Beny; Yasir, Mhd; Christian, Hadi
Emerging Science Journal Vol 8, No 5 (2024): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-05-07

Abstract

In this work, we report the capability of a PCF-SPR sensor with an elliptical core, which has high sensitivity, and it is explained using a machine learning approach. The sensor component consists of fused silica as the background material, TiO2 as the adhesive material between the dielectric material and the plasmonic material, and Au was chosen as plasmonic material with optimal thicknesses of 35 nm for TiO2and 45 nm for Au. Numerical results show that the sensor component has a high sensitivity of 24,000 nm/RIU for four modes that have consistent shifts, including x-polarized, x-odd, y-polarized, and y-odd. Meanwhile, AS maximums were found of -91.82 1/RIU for x-polarized, -91.88 1/RIU for y-polarized, -90.98 1/RIU for x-odd, and -89.276 1/RIU for y-odd respectively, on the refractive index of the analyte of 1,365 RIU. The ML algorithm was used to optimize the sensor parameters, and it was found that the algorithm had a very low MSE of 0.00083; this result is better than the previous report work. Doi: 10.28991/ESJ-2024-08-05-07 Full Text: PDF
Co-Authors Agustirandi, Beny Azhar Christian, Hadi dedi irawan Marwin, Azwir Ramadhan, Khaikal Syamsul, Andi M. N. F. Yasir, Mhd