Improved method for estimating adlayer thickness and bulk RI change for gold nanocrescent sensors

This paper presents a novel method employing the maximum likelihood estimation (MLE) technique alongside a nonlinear sensor response model to improve and extract more quantitative sensing results for localized surface plasmon resonance biosensors. The nonlinear response model treats the sensor response as a nonlinear function of the biomolecular adlayer thickness. This method makes use of the multiple resonance characteristic of nanocrescent structures in order to estimate the adlayer thickness and bulk refractive index (RI) change. Nanoimprint lithography is used here to fabricate the nanostructures. The finite element method (FEM) is used to model the nanocrescents and numerically validate the nonlinear-MLE method. Comparing to the established linear model, the proposed nonlinear-MLE method achieves 75% improvement in the limit of detection based on the estimated adlayer thickness and improves the bulk RI resolution by two orders of magnitude.