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Calibration of fiber optic based surface plasmon resonance sensors in aqueous systems [An article from: Analytica Chimica Acta]
Book Details
PublisherElsevier
ISBN / ASINB000RR01O6
ISBN-13978B000RR01O1
AvailabilityAvailable for download now
Sales Rank99,999,999
MarketplaceUnited States 🇺🇸
Description
This digital document is a journal article from Analytica Chimica Acta, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
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 3x10^-^4 RI units (RIU) using an air reference and a RI calibration set of aqueous sucrose samples measured with an Abbe refractometer accurate to 1x10^-^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^oC. MHM was subsequently used to predict the concentration of 0.00-6.99wt.% KCl"("a"q") samples between 6 and 29^oC, a range found in surface ocean waters. Prediction error as small as 0.073wt.% correlates to 2x10^-^4 RIU shows MHM holds over a wide dynamic range.
Description:
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 3x10^-^4 RI units (RIU) using an air reference and a RI calibration set of aqueous sucrose samples measured with an Abbe refractometer accurate to 1x10^-^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^oC. MHM was subsequently used to predict the concentration of 0.00-6.99wt.% KCl"("a"q") samples between 6 and 29^oC, a range found in surface ocean waters. Prediction error as small as 0.073wt.% correlates to 2x10^-^4 RIU shows MHM holds over a wide dynamic range.
