Authors: Guilment, Jean¹; Markel, Sharon²; Windig, Willem²

Source: Applied Spectroscopy, Volume 48, Issue 3, Pages 289-416 (March 1994) , pp. 320-326(7)

Publisher: Society for Applied Spectroscopy

Abstract:

In the analytical environment, spectral data resulting from analysis of samples often represent mixtures of several components. Extraction of information about pure components from that kind of mixture is a major problem, especially when reference spectra are not available. Self-modeling multivariate mixture analysis has been developed for this type of problem. In this paper, two examples will be used to show the potential of the technique for vibrational spectroscopy. Infrared microspectroscopic chemical imaging has been employed to improve spatial resolution for distinguishing differences between adjacent, nonidentical materials. The resolution of a 2- to 3-μm-thick inner layer, from a four-layer polymer laminate, has been achieved. The same approach has been utilized to extract pure component spectra out of a KBr pellet of a mixture of three compounds.

Keywords: SIMPLISMA; Microspectroscopy; FT-IR spectroscopy; Polymer laminate; Chemical imaging; Second-derivative spectra; Mapping experiments; Powder mixture analysis

Document Type: Research article

DOI: http://dx.doi.org/10.1366/0003702944028308

Affiliations: 1: Kodak European Research Laboratories, Z.I.Nord 71102 Chalon/Saône Cedex, France 2: Eastman Kodak Company, Rochester, New York 14652-3712, U.S.A.

Publication date: 1994-03-01

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