Probabilistic evaluation of surface-enhanced localized surface plasmon resonance biosensing.
In this paper, we investigate detection characteristics of localized surface plasmon resonance biosensing based on a probabilistic Poisson distribution of target molecules. The model uses random nanoislands for localization of near-fields in three detection scenarios of non-specific, non-colocalized, and colocalized detection. Optical signatures were found to increase monotonically with target concentration and size regardless of the detection scenarios. The signatures were largest in colocalized detection of target interactions to localized fields, followed by non-colocalized and non-specific detection. The confidence interval was the narrowest in the colocalized detection due to the increased spatial certainty by localization. Based on the relative confidence interval, it was found that limit of detection can be enhanced by more than four orders of magnitude through colocalization.
Heejin
H
Yang
Wonju
W
Lee
Taewon
T
Hwang
Donghyun
D
Kim
D016001:Confidence Intervals; D008962:Models, Theoretical; D053758:Nanoparticles / Q000648:ultrastructure; D009716:Numerical Analysis, Computer-Assisted; D055620:Optical Phenomena; D011336:Probability; D020349:Surface Plasmon Resonance / Q000379:methods*