Qualitative and quantitative detection of corrosion inhibitors using surface-enhanced Raman scattering coupled with multivariate analysis

In this study, a novel strategy was proposed for the on-site detection and quantitation of corrosion inhibitors by means of surface-enhanced Raman scattering (SERS) detection and partial least squares regression (PLSR) algorithm. Using a SERS tape as the signal amplifier, the Raman signals of 2-mercaptobenzothiazole (MBT) inhibitors adsorbed on aluminium alloy were intensively magnified. The SERS intensities grew monotonously with the increase of inhibitor concentration and immersion time, indicating the continuous accumulation of MBT molecules that facilitated the effective corrosion inhibition performance. Furthermore, PLSR method was adopted to achieve the quantitative analysis of inhibitors on metal surface based on the SERS spectra variations. The regression relationship between the SERS spectra of MBT molecules on the alloy surface and their concentrations showed good predictive ability. Based on the established PLSR model, it has been employed for the quantification of remaining MBT inhibitors during reversible desorption process. SERS analysis combined with PLSR algorithm can be used to sensitively detect, quantify and predict corrosion inhibitors, which is helpful for the in-depth understanding of corrosion inhibition mechanism and will promote the exploitation of new corrosion inhibitors.

Automated summary

This study proposed a novel strategy for on-site detection and quantitation of corrosion inhibitors using SERS detection and PLSR algorithm. SERS intensities were linearly correlated with inhibitor concentrations, showing good predictive ability and quantification performance.