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Journal of Computational Electronics

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17-06-2024

Tuning sensitivity of bimetallic, MXene and graphene-based SPR biosensors for rapid malaria detection: a numerical approach

Authors: Bhishma Karki, Arun Uniyal, Manoj Sharma, Ram Bharos Yadav, Parusharamulu Buduma

Published in: Journal of Computational Electronics | Issue 4/2024

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Abstract

The potential of surface plasmon resonance (SPR) biosensors to detect different biomolecules quickly and sensitively has attracted much attention. In this work, we use a numerical method to identify malaria phases by exploring the sensitivity adjustment of SPR sensors based on bimetallic, MXene and graphene layers. Effective treatment for malaria, a potentially fatal disease brought on by plasmodium parasites, depends on early identification. Innovative biosensing technologies are necessary since traditional diagnostic procedures frequently lack sensitivity and speed. The transfer matrix method is employed here in this study for reflectance calculation. The COMSOL software finds the electric field distribution across the various layers interfaces. The maximum sensitivity of 301.1667°/RIU has been attained for the proposed work.

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Title: Tuning sensitivity of bimetallic, MXene and graphene-based SPR biosensors for rapid malaria detection: a numerical approach
Authors: Bhishma Karki
Arun Uniyal
Manoj Sharma
Ram Bharos Yadav
Parusharamulu Buduma
Publication date: 17-06-2024
Publisher: Springer US
Published in: Journal of Computational Electronics / Issue 4/2024
Print ISSN: 1569-8025
Electronic ISSN: 1572-8137
DOI: https://doi.org/10.1007/s10825-024-02191-4

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Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

A feasibility study of microwave UAV imaging based on multi-station polarimetric radars

Advancing microwave ablation applicators: integrating computational modeling of a graphene-based applicator with machine learning for ablation zone prediction

Performance analysis of CsPbI3-based solar cells under light emitting diode illumination as an energy harvester for IoT and indoor photovoltaics

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Addressing multi-molecule field-coupled nanocomputing for neural networks with SCERPA

Donor-induced electrically charged defect levels: examining the role of indium and n-type defect-complexes in germanium