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DOI 10.1109/tnb.2023.3286269

Медицинская библиотека · IEEE transactions on nanobioscience · 2024

Multi-Disease Detection Using a Prism-Based Surface Plasmon Resonance Sensor: A TMM and FEM Approach.

Rumi Rabeya Bosrin, Paul Alok Kumar, Alyami Salem A, Moni Mohammad Ali

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

This research introduces a surface plasmon resonance (SPR)-based biosensor with multilayered structures for telecommunication wavelength in order to detect multiple diseases. The malaria and the chikungunya viruses are taken into account and the presence of these viruses are determined by examining several blood components in healthy and affected phases. Here, two distinct configurations (Al-BTO-Al-MoS2 and Cu-BTO-Cu-MoS2) are proposed and contrasted for the detection of numerous viruses. The performance characteristics of this work have been analyzed using Transfer Matrix Method (TMM) method and Finite Element Method (FEM) method under angle interrogation technique. From the TMM and FEM solutions, it is evident that the Al-BTO-Al-MoS2 structure provides the highest sensitivities of ~270 deg./RIU for malaria and ~262 deg./RIU for chikungunya viruses, with satisfactory detection accuracy of ~1.10 for malaria, ~1.64 for chikungunya, and quality factor of ~204.40 for malaria, ~208.20 for chikungunya. In addition, the Cu-BTO-Cu MoS2 structure offers the highest sensitivities of ~310 deg./RIU for malaria and ~298 deg./RIU for chikungunya, with satisfactory detection accuracy of ~0.40 for malaria, ~0.58 for chikungunya, and quality factor of ~89.85 for malaria, ~86.38 for chikungunya viruses. Therefore, the performance of the proposed sensors is analyzed using two distinct methods and gives around similar results. In a sum, this research could be utilized as a theoretical foundation and first step in the development of a real sensor.

Для цитирования: Rumi Rabeya Bosrin, Paul Alok Kumar, Alyami Salem A, Moni Mohammad Ali. Multi-Disease Detection Using a Prism-Based Surface Plasmon Resonance Sensor: A TMM and FEM Approach.. IEEE transactions on nanobioscience. 2024. DOI: 10.1109/tnb.2023.3286269.

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