Statistical modelling of photonic crystal fibre based surface plasmon resonance sensors resonant peak wavelength for tolerance studies

Osifeso, Samuel and Chu, Suoda and Nakkeeran, K. (2021) Statistical modelling of photonic crystal fibre based surface plasmon resonance sensors resonant peak wavelength for tolerance studies. Sensors, 21 (19). 6603. ISSN 1424-8220

[thumbnail of Osifeso-etal-Sensors-2021-Statistical-modelling-of-photonic-crystal-fibre-based-surface-plasmon-resonance-sensors]
Preview
Text (Osifeso-etal-Sensors-2021-Statistical-modelling-of-photonic-crystal-fibre-based-surface-plasmon-resonance-sensors)
Osifeso_etal_Sensors_2021_Statistical_modelling_of_photonic_crystal_fibre_based_surface_plasmon_resonance_sensors.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo

Download (3MB)| Preview

    Abstract

    We report a statistical approach to model the resonant peak wavelength (RPW) equation(s) of a photonic crystal fibre (PCF)-based surface plasmon resonance (SPR) sensors in terms of the PCF structural parameters (air-hole diameter, pitch, core diameter and gold layer thickness) at various tolerance levels. Design of experiments (statistical tool) is used to investigate the role played by the PCF structural parameters for sensing performance evaluation—RPW, across three tolerance levels (±2%, ±5% and ±10%). Pitch of the hollow-core PCF was discovered to be the major influencing parameter for the sensing performance (RPW) of the PCF-based SPR sensor while the inner metal (gold) layer thickness and core diameter are the least contributing parameters. This novel statistical method to derive the sensing performance parameter(s) of the PCF-based SPR sensors can be applied effectively and efficiently in the designing, characterisation, tolerance analysis not only at the research level, but also in optical fibre sensor fabrication industry to improve efficiency and lower cost.