Modeling of the SPR resolution enhancement for conventional and nanoparticle inclusive sensors by using statistical hypothesis testing.

This paper describes a statistical approach that improves the detection accuracy in simulated experimental surface plasmon resonance (SPR) systems operated in a conventional angular readout scheme. Two SPR system have been investigated: a conventional one and a second one, containing absorbing metallic nanoparticles within the sensing layer. The modified Maxwell-Garnett model that optimally describes the experimental literature results was applied to modeling of the nanoparticle-inclusive sensor. Statistical hypothesis testing was then used to determine the limit of detection of the analyte and nanoparticles. Analyte concentrations as low as 1 pM, corresponding to the refractive index change of 4x10(-8) have been detected with optimized metal layers operated close to the nanoparticle absorption maximum. This is about one order of magnitude smaller than the values obtained in conventional SPR systems with nanoparticles and comparable to the phase-sensitive surface plasmon resonance detection.