Abstract

Resolution of the reaction steps and the associated component Raman spectra during the formation or desorption of self-assembled monolayers is challenging because intermediate adsorbate populations are present at low concentrations and their spectral bands overlap. By collecting Raman spectra versus applied potential into a two-dimensional data set, one can utilize multivariate statistical techniques to resolve the component concentration profiles along with their corresponding Raman spectra.<i> In situ</i> surface-enhanced Raman spectroscopy (SERS) spectra were collected during the potential-dependent formation and desorption (-1.50 to -0.70V versus Ag/AgCl) of n-hexanethiolate monolayer at a polycrystalline Ag electrode. Resolution of the pure component spectra from these components was accomplished by using self-modeling curve resolution (SMCR), which does not require a physical model. For monolayer adsorption, the potential-dependent Raman spectra could be described by three significant eigenvectors; the eigenvectors could be rotated into a set of pure component spectra and concentration profiles using a linear least-squares step to find a common plane in the space of the eigenvectors representing the linear combination of the real-component responses. The convex hull surrounding the data in the plane and positive amplitude criteria were utilized to identify the coordinates of the pure component responses. The C–S stretching vibrations of the resolved spectra show that the initial adsorbate is a gauche conformer, which allows the hydrocarbon chain to lie on the metal surface; a second phase arises at higher coverage with trans C–S conformation, where the hydrocarbon chains are oriented off the surface plane, and a final complete monolayer is formed with a well-ordered, all-trans C–S configuration. In contrast, desorption studies showed only two surface phases, the initial well-ordered monolayer and the low-density phase dominated by gauche conformations. The results illustrate the utility of self-modeling curve resolution to unravel interfacial reaction mechanisms and intermediate structures from two-dimensional SERS data, without requiring prior knowledge of a physical model for the process.

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