Analysis of Multicomponent Ionic Mixtures using Blind Source Separation - a Processing Case Study Dataset
Maggioni, Giovanni Maria
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Management and remediation of complex nuclear waste solutions require identification and quantification of multiple species. Some of the species forming the solution are unknown and they can be different from vessel to vessel, thus limiting the utility of standard calibration approaches. To cope with such limited information, we propose a procedure based on blind source separation (BSS) techniques, in particular independent component analysis and multivariate curve resolution, with a one-point calibration library. Here we show the applicability and reliability of our procedure for on-line measurements of aqueous ionic solutions by proposing an automatic procedure to identify the number of species in the mixture, estimate the spectra of the pure species, and label the spectra with respect to a library of reference components. We test our procedure against simulated and experimental data for mixtures with six species (water plus five sodium salts) for the case of Raman and ATR-FTIR spectroscopy.