Abstract
We study a SOI hybrid plasmonic waveguide (Silicon – slot – metal) micro-ring resonator for bulk and affinity sensing applications. The opto-geometric parameters of the sensors have been optimized to enhance the affinity sensitivity by maximizing the modal field confinement in the sensing (slot) region. Keeping the practicality aspect in view, we have performed the simulations by considering a specific case of β-Lactoglobulin protein molecules in liquid phase as an example. The maximum attained bulk refractive index sensitivity is 555 nm/RIU with a figure of merit of 154.16 RIU−1 when 10% β-Lactoglobulin molecules are present in the sample. A more realistic approach has been proposed for investigation of affinity sensing with the results further compared to the existing approach. Effect of varied thickness of biomolecule adlayer in the slot region, in which the modal electric field is immensely confined, has been studied. We observe that with increasing adlayer thickness, the surface sensitivity increases exponentially and a very high affinity sensitivity of 0.97 nm/nm has been observed when the biomolecules are immobilized over the entire slot region. Our study may find direct application in quantitative detection of β-Lactoglobulin protein molecules in bio-sample, and in designing highly sensitive photonic biosensors for specific detection of biomolecules by incorporating appropriate immobilization schemes.
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The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
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This work has been carried out in Indian Institute of Technology, Kanpur.
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This work was supported by Science and Engineering Research Board, Govt. of India via project no. EMR/2016/007936.
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Soumya Kumari: Performed simulations, Data collection, Data curation, Writing - Original draft.
Saurabh Mani Tripathi: Conceptualization, Writing – Review and Editing.
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Kumari, S., Tripathi, S.M. Hybrid Plasmonic SOI Ring Resonator for Bulk and Affinity Bio - sensing Applications. Silicon 14, 11577–11586 (2022). https://doi.org/10.1007/s12633-022-01877-3
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DOI: https://doi.org/10.1007/s12633-022-01877-3