Media type: E-Article Title: Multivariate spectral analysis of pH SERS probes for improved sensing capabilities Contributor: Williams, Adam; Flynn, Kevin John; Xia, Zhidao; Dunstan, Peter Roger imprint: Wiley, 2016 Published in: Journal of Raman Spectroscopy, 47 (2016) 7, Seite 819-827 Language: English DOI: 10.1002/jrs.4910 ISSN: 1097-4555; 0377-0486 Origination: Footnote: Description: <jats:p>Adsorption of functional groups to the surface of plasmonic nanoparticles provides a platform for localised optical sensing. Over the past decade, nanoscale sensors for intracellular pH measurement based on surface‐enhanced Raman spectroscopy (SERS) have been developed. However, the approaches by which pH‐SERS measurements are made and analysed can greatly impact the precision and accuracy of pH calibration. To improve pH nanosensors, the sources of experimental variation must be determined and the data must be optimally analysed. Here we report the plasmon‐induced decarboxylation of <jats:italic>para</jats:italic>‐mercaptobenzoic acid (pMBA) pH reporters attached to gold nanoparticles and conclude a strong association with laser power. The detrimental decarboxylation of pMBA has profound implications on the sensitivity and reliability of the pH sensor. Decarboxylation spectral signatures map directly onto those that are typically used to record pH changes, and, hence, the greatest implication of decarboxylation of pH sensors is inaccurate or false pH reporting. Here a more robust spectral analysis for pH sensing based upon an optimal spectral region for pH calibration is presented together with a unique application of the multivariate statistical technique, principal component analysis (PCA). PCA interprets complex spectral dynamics, and by direct comparisons with the typically employed ratiometric analysis, a significant improvement in generating accurate pH sensing is demonstrated. An application of these methods in determining the pH of internalised nanosensors in macrophage cells further promotes these step changes in pH measurement methodology via the avoidance of disruptive spectral signatures that arise in real applications. Copyright © 2016 John Wiley & Sons, Ltd.</jats:p>