On the performance quantification of resonant refractive index sensors.

By Ian M. White, Xudong Fan. Optics Express, 2008

1,032 citations recorded by the source corpus.

Refractive index (RI) sensors based on optical resonance techniques are receiving a high degree of attention because of the need to develop simple, low-cost, high-throughput detection technologies for a number of applications. While the sensing mechanism of most of the reported RI sensors is similar, the construction is quite different from technique to technique. It is desirable to have a uniform mechanism for comparing the various RI sensing techniques, but to date there exists a degree of variation as to how the sensing performance is quantified. Here we set forth a rigorous definition for the detection limit of resonant RI sensors that accounts for all parameters that affect the detection performance. Our work will enable a standard approach for quantifying and comparing the performance of optical resonance-based RI sensors. Additionally, it will lead to design strategies for performance improvement of RI sensors.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/97efb30ab6e0782654d7a8c2635ead105adfbdb2

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Citations in the corpus

Hybrid photonic-crystal fiber (2017, background): “Therefore, the sensitivity which is one of the most important factor determining the performance of a sensor is defined as (White and Fan, 2008): S = ∂λr ∂nanalyte (11) When higher-order modes of the high-index fluid waveguide in the work of Wu et al. become leaky modes, their mode field expand,…”
Towards a Uniform Metrological Assessment of Grating-Based Optical Fiber Sensors: From Refractometers to Biosensors (2017, background): “In the third (and final) approach, the determination of LOD is based on the sensor resolution and on the surface sensitivity (Ssurface) [2,4,19], which is the RI change (∆n) divided by the surface density concentration (ρmax) of the target analyte, as expressed in the following equation:”
Photonic crystal resonances for sensing and imaging (2018, background): “same value of σblank) higher FOM sensors are favoured [24].”
Silicon Photonic Biosensors Using Label-Free Detection (2018, methodology): “That is because having a high 669 Q-factor (narrow FWHM) can filter the spectral noise effectively and lead to a low spectral deviation from the 670 actual extremum [57].”
Fluid-Filled Solid-Core Photonic Bandgap Fibers (2009, background): “[86], assuming is much larger than the spectrum analyser’s resolution, one has”