Abstract

Two-dimensional (2D) correlation spectroscopy has been extensively applied to analyze various vibrational spectroscopic data, especially infrared and Raman. However, when it is applied to real-world experimental data, which often contains various imperfections (such as noise interference, baseline fluctuations, and band-shifting) and highly overlapping bands, many artifacts and misleading features in synchronous and asynchronous maps will emerge, and this will lead to difficulties with interpretation. Therefore, an approach that counters many artifacts and therefore leads to simplified interpretation of 2D correlation analysis is certainly useful. In the present contribution, band-target entropy minimization (BTEM) is employed as a spectral pretreatment to handle many of the artifact problems before the application of 2D correlation analysis. BTEM is employed to elucidate the pure component spectra of mixtures and their corresponding concentration profiles. Two alternate forms of analysis result. In the first, the normally <i>v</i> × <i>v</i> problem is converted to an equivalent <i>n</i><i>v</i> × <i>n</i><i>v</i> problem, where <i>n</i> represents the number of species present. In the second, the pure component spectra are transformed into simple distributions, and an equivalent and less computationally intensive <i>n</i><i>v</i>′ × <i>n</i><i>v</i>′ problem results (<i>v</i>′ < <i>v</i>). In both cases, the separation of spectral contributions greatly simplifies interpretation of the 2D plots. This new approach is successfully applied to a solvent evaporation study where <i>in situ</i> Fourier transform infrared (FT-IR) spectroscopy is used as the analytical tool.

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