ASTM E1790-04(2016)e1 pdf free download.Standard Practice for Near Infrared Qualitative Analysis.
ASTM E1790-04(2016)e1 covers the use of near-infrared (NIR) spectroscopy for the qualitative analysis of liquids and solids. The practice is written under the assumption that most NIR qualitative analyses will be performed with instruments designed specifically for this region and equipped with computerized data handling algorithms. In principle, however, the practice also applies to work with liquid samples using instruments designed for operation over the ultraviolet (UV), visible, and mid-infrared (IR) regions if suitable data handling capabilities are available. Many Fourier Transform Infrared (FTIR) (normally considered mid-IR instruments) have NIR capability, or at least extended-range beamsplitters that allow operation to 1.2 μm; this practice also applies to data from these instruments.
NIR qualitative analysis is conducted by comparison of NIR absorption spectra of unknown materials with those of known reference materials. Since the absorption bands of many substances of interest are less distinctive in the NIR than in the mid-IR spectral region, the analytical capability of the technique relies heavily on the accuracy of the absorption measurements and the relationship of the relative absorbances at different wavelengths. Materials to be identified are measured by a NIR spectrometer, and the spectral data thus generated are saved in an auxiliary computer attached to the spectrometer proper. One of the several algorithms described in Section 6 is then applied to the data in order to generate classification criteria, which can then be applied to data from unknown samples in order to classify (or identify) them as being the same as one of the previously seen materials. Good chemical laboratory practice should be followed to help ensure reproducible results for each material. The preparation and presentation of samples to the instrument should be consistent within a library, and unknowns should be treated the same way that the training samples were.
This section describes some of the computerized algorithms that have been found effective for qualitative analysis in the NIR spectral region. This section is mainly for reference. Descriptions of multivariate methods of statistical data analysis tend to be inherently abstract mathematically and resistant to reduction to words. A number of books exist in both the statistical and chemometric literature that describe methods of multivariate analysis at varying levels of mathematical abstraction (see, for example, Refs,a useful starting point but far from exhaustive list); most of the algorithms used for NIR qualitative analysis are relatively straightforward applications of these methods.
7 Keywords
7.1 molecular spectroscopy; near-infrared; qualitative analysis