Machine learning enabled 2D photonic crystal biosensor for early cancer detection

Balaji, V.R; Ibrar Jahan, M.A; Sridarshini, T.; Geerthana, S.; Thirumurugan, Arun; Hegde, Gopalkrishna; Sitharthan, R.; Dhanabalan, Shanmuga Sundar

doi:10.1016/j.measurement.2023.113858

Cited by 7 publications

(1 citation statement)

References 26 publications

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“…High sensitivity is one of the important characteristics of biosensors. [1][2][3][4][5][6] The most common application of biosensors is in medical diagnosis and laboratory science.…”

mentioning

confidence: 99%

Optimization of Optical Biosensor Based on 1D Photonic Crystals with Metaheuristic Algorithms for Measuring Glucose Concentration

Al-Moliki,

Alqahtani

et al. 2024

ECS J. Solid State Sci. Technol.

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We aim to simulate an optimal optical biosensor based on one-dimensional crystal photonics, for measuring blood and urine glucose concentration. By optimizing the sensor structure through metaheuristic optimization algorithms, sensitivity was increased. To measure blood and urine glucose concentration, these materials are used as a defect layer in one-dimensional crystal photonics, consisting of three materials: magnesium fluoride (MgF2), borosilicate glass (BK7), and orphan iodide (LiI) with refractive indices of 37/ 1, 1/5, and 1/99. By changing the concentration of glucose, the refractive index of the defect layer changes, changing the optical properties of the defect layer in the photonic crystal and the spectrum of transmitted and reflected light. According to the amount of light absorption by glucose, a wavelength range of 900-2200 nm (near infrared) was used as the input light. The transfer matrix method was used to calculate multi-layer systems. This method is based on the definition of two matrices, the boundary matrix and the diffusion matrix, which can be used to directly apply the boundary conditions. By plotting the spectrum passing through the crystal using the transfer matrix method and determining the location of the peak in the spectrum, the sensitivity of the sensor was calculated for different concentrations of glucose in blood and urine. The sensitivity obtained before optimization was 530 nm/RIU, while after optimization it reached 842 nm/RIU

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“…High sensitivity is one of the important characteristics of biosensors. [1][2][3][4][5][6] The most common application of biosensors is in medical diagnosis and laboratory science.…”

mentioning

confidence: 99%

Optimization of Optical Biosensor Based on 1D Photonic Crystals with Metaheuristic Algorithms for Measuring Glucose Concentration

Al-Moliki,

Alqahtani

et al. 2024

ECS J. Solid State Sci. Technol.

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Advances in Photonic Crystal Research for Structural Color

Chen,

Wei,

Pan

et al. 2024

Adv Materials Technologies

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Structural color is a remarkable physical phenomenon that exists widely in nature. Unlike traditional color rendering methods, they are realized mainly through micro/nanostructures that interfere, diffract, scatter light, and exhibit long‐life and environmental‐friendly color effects. In nature, a few organisms use their color‐changing system to transmit information, such as courtship, warning, or disguise. Meanwhile, some natural inorganic minerals can also exhibit structural colors. Learning from nature, scientists have achieved large‐scale structural color design and manufacturing technology for artificial photonic crystals. Photonic crystals have a unique microstructure that forms a band gap under the action of the periodic potential field, consequently causing Bragg scattering due to the periodic arrangement of different refractive index media within them. Because of the apparent photonic band gap and the ability to form local photons at crystal defects, photonic crystals have been extensively studied in recent years and have broad application prospects in photonic fibers, optical computers, chips, and other fields. In this review, the research, properties, and applications of photonic crystals in recent years are presented, as well as insight into the future developments of photonic crystals.

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Hypercholesterolemia and Hyperglycemia Diagnosis by Photonic Crystal Biosensor

Rafiee

2024

Sens Imaging

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Machine learning enabled 2D photonic crystal biosensor for early cancer detection

Cited by 7 publications

References 26 publications

Optimization of Optical Biosensor Based on 1D Photonic Crystals with Metaheuristic Algorithms for Measuring Glucose Concentration

Optimization of Optical Biosensor Based on 1D Photonic Crystals with Metaheuristic Algorithms for Measuring Glucose Concentration

Advances in Photonic Crystal Research for Structural Color

Hypercholesterolemia and Hyperglycemia Diagnosis by Photonic Crystal Biosensor

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