FTIR spectrometers generate a beam of finite area and convergence. Appropriately located variable apertures can be used to control both the area and the convergence of the beam. We have used a spectrometer fitted with such apertures to investigate their effect on transmission and reflection spectra. Perhaps the most significant finding is that the relative intensities of bands in an ATR spectrum can be altered by more than 10% simply by varying the beam convergence.
KEYWORDS: Tablets, Signal to noise ratio, Solids, Near infrared, Raman spectroscopy, Principal component analysis, Spectroscopy, Near infrared spectroscopy, Liquids, Smoothing
NIR FT-Raman spectroscopy offers rapid measurements with very convenient sampling, especially for solids. However, for quality control applications an even more important consideration is the repeatability of the measurements. In this paper we examine how varying the measurement conditions can affect repeatability. Problems arise because the Raman spectrum is usually obtained from a fairly small volume of material. For solids such as pharmaceutical tablets both the homogeneity of the sample and its positioning in the instrument may affect the appearance of the spectrum. The spectrum is usually recorded from a small volume in order to maximize the collection angle and hence the signal-to-noise ratio in the spectra. Our results show that inhomogeneity can be the largest source of variation in the spectra of tablets. In this situation it is better to measure a larger volume, the increase in noise being offset by the more representative sampling.
The introduction of multivariate methods such as PCR and PLS has considerably extended the scope of quantitative FT-IR analysis. However method development is now an area for specialists who can interpret the wealth of diagnostic information generated by current chemometric software packages. Inexperienced users are faced with so much information that they simply do not know where to start. We have developed a rule-based system that uses this information in an iterative procedure to develop calibrations automatically. The main task is to identify and eliminate outliers of various types, namely spectra, variables and property values. The system is capable of generating robust calibrations from data sets containing multiple errors, using either PCR or PLS.
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