ABSTRACT
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.
ABSTRACT
We present a novel approach to improve self-referenced sensing based on multiple-resonance nanorod structures. The method employs the maximum likelihood estimation (MLE) alongside a linear response model (LM), relating the sensor response (shifts in resonance wavelengths) to the changes due to surface binding and bulk refractive index. We also provide a solution to avoid repetitive simulations, that have been previously needed to determine the adlayer thickness sensitivity when measuring biological samples of different refractive indices. The finite element method (FEM) was used to model the nanorod structure, and the nanoimprint lithography was employed to fabricate them. The standard deviation of the results based on the MLE method is lower than that associated with the LM results. The method can be applied to an extended number of resonances to achieve a higher accuracy and precision.
ABSTRACT
This paper presents a simple and accurate method (the projection method) to improve the signal to noise ratio of localized surface plasmon resonance (LSPR). The nanostructures presented in the paper can be readily fabricated by nanoimprint lithography. The finite difference time domain method is used to simulate the structures and generate a reference matrix for the method. The results are validated against experimental data and the proposed method is compared against several other recently published signal processing techniques. We also apply the projection method to biotin-streptavidin binding experimental data and determine the limit of detection (LoD). The method improves the signal to noise ratio (SNR) by one order of magnitude, and hence decreases the limit of detection when compared to the direct measurement of the transmission-dip. The projection method outperforms the established methods in terms of accuracy and achieves the best combination of signal to noise ratio and limit of detection.
