Calibration of Surface Plasmon Resonance Refractometers Using Locally Weighted Parametric Regression

Morlet Wavelet Filtering and Phase Analysis to Reduce the Limit of Detection for Thin Film Optical Biosensors

The ultimate detection limit of optical biosensors is often limited by various noise sources, including those introduced by the optical measurement setup. While sophisticated modifications to instrumentation may reduce noise, a simpler approach that can benefit all sensor platforms is the application of signal processing to minimize the deleterious effects of noise. In this work, we show that applying complex Morlet wavelet convolution to Fabry-Pérot interference fringes characteristic of thin film reflectometric biosensors effectively filters out white noise and low-frequency reflectance variations. Subsequent calculation of the average difference in extracted phase between the filtered analyte and reference signals enables a significant reduction in the limit of detection (LOD). This method is applied on experimental data sets of thin film porous silicon sensors (PSi) in buffered solution and complex media obtained from two different laboratories. The demonstrated improvement in the LOD achieved using wavelet convolution and average phase difference paves the way for PSi optical biosensors to operate with clinically relevant detection limits for medical diagnostics, environmental monitoring, and food safety.

Hybrid differential interrogation method for sensitive surface plasmon resonance measurement enabled by electro-optically tunable SPR sensors

A novel detection method enabled by electro-optically tunable waveguide-coupled surface plasmon resonance sensors is demonstrated. Both the WCSPR response of sensor and the interrogation light are varied simultaneously in this hybrid scheme. Modulation and demodulation of the sensor's response are achieved by applying a high-frequency AC electrical signal and electrically filtering the detected signal. Scanning the incident angle at a lower speed yields an angular dependent response. Theoretical analyses and experimental results show that the angular-dependent signal is closely related to the derivative of the SPR reflectivity with a sharp, linear jump near the minimum of the SPR peak. Thus, simple linear-fitting and zero-finding algorithms can be used to locate the SPR angle, and sophisticated data processing algorithms and electronic hardware can be avoided.

Surface plasmon spectral fingerprinting of adsorbed magnesium phthalocyanine by angle and wavelength modulation

A novel instrumental method for angle and wavelength modulated surface plasmon resonance (SPR) spectroscopy is applied to the problem of spectral selectivity in SPR experiments. For transparent analytes, SPR reflectivity data are reduced to a two-dimensional (2D) spectrum of resonance wavelength versus incident angle, lambdaSPR(theta). This spectrum encodes the refractive index (RI) dispersion of the analyte and illustrates the increased SPR spectral shift per unit RI change at longer wavelengths (lower angle). For the absorbing analyte magnesium phthalocyanine (MgPc), the 2D data reduction method is complicated by the way the SPR and MgPc-based spectral peaks mix. Fresnel reflectivity models support experimental observations of spectral branching and qualitative fingerprints in the form of branched spectra, and difference reflectivity deltaR(lambda, theta) contour plots are presented.