Abstract
This manuscript addresses two issues with calibration of surface plasmon resonance sensors which can track refractive index changes to measure correlated bulk properties. First, employing non-air references do not return the traditional parabolic dip in the SPR spectra; instead the returned SPR spectra are more ‘derivative’ in shape. Investigated are five different ways to calibrate SPR spectra when non-air references are employed. The minimum hunt method (MHM) calculates the position of this minimum by fitting a parabola to the curve. MHM is shown to consistently achieve prediction errors of 3×10 −4 RI units (RIU) using an air reference and a RI calibration set of aqueous sucrose samples measured with an Abbé refractometer accurate to 1×10 −4 RIU. Use of principal component regression (PCR) with air or water references generates prediction errors at best the same as MHM but worse as the concentration range of samples increases. Second, a method for calibrating SPR spectra across a wide temperature range is presented. It is shown that this method is capable of successfully mitigating the effect of temperature drifts up to 20 °C. MHM was subsequently used to predict the concentration of 0.00–6.99 wt.% KCl (aq) samples between 6 and 29 °C, a range found in surface ocean waters. Prediction error as small as 0.073 wt.% correlates to 2×10 −4 RIU shows MHM holds over a wide dynamic range.
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