Spectral data bases, optical

Table 22.2 Optical spectral data bases (according to provider specifications, 01.09.2000).

Considerable interest centres on the Mantle constituting, as it does, more than half of the Earth by volume and by weight. Attention has been focussed on several problems, including the chemical composition, mineralogy, phase transitions and element partitioning in the Mantle, and the geophysical properties of seismicity, heat transfer by radiation, electrical conductivity and magnetism in the Earth. Many of these properties of the Earth s interior are influenced by the electronic structures of transition metal ions in Mantle minerals at elevated temperatures and pressures. Such effects are amenable to interpretation by crystal field theory based on optical spectral data for minerals measured at elevated temperatures and pressures. 

As already mentioned, any multivariate analysis should include some validation, that is, formal testing, to extrapolate the model to new but similar data. This requires two separate steps in the computation of each model component calibration, which consists of finding the new components, and validation, which checks how well the computed components describe the new data. Each of these two steps needs its own set of samples calibration samples or training samples, and validation samples or test samples. Computation of spectroscopic data PCs is based solely on optic data. There is no explicit or formal relationship between PCs and the composition of the samples in the sets from which the spectra were measured. In addition, PCs are considered superior to the original spectral data produced directly by the NIR instrument. Since the first few PCs are stripped of noise, they represent the real variation of the spectra, presumably caused by physical or chemical phenomena. For these reasons PCs are considered as latent variables as opposed to the direct variables actually measured. 

This alkaloid (LXVII) is isomeric with kurchiline and shows close similarity to it in spectral data except for those pertaining to the ketone group. The position of the carbonyl band in the IR-spectrum (1748 cm i) demonstrated the keto group to be a part of a five-membered ring. This fact, in conjunction with strong negative optical rotation shown by the base, led to location of the ketone group in position 16. Both kurchi-... 

Spectroscopic methods can provide fast, non-destructive analytical measurements that can replace conventional analytical methods in many cases. The non-destructive nature of optical measurements makes them very attractive for stability testing. In the future, spectroscopic methods will be increasingly used for pharmaceutical stability analysis. This chapter will focus on quantitative analysis of pharmaceutical products. The second section of the chapter will provide an overview of basic vibrational spectroscopy and modern spectroscopic technology. The third section of this chapter is an introduction to multivariate analysis (MVA) and chemometrics. MVA is essential for the quantitative analysis of NIR and in many cases Raman spectral data. Growth in MVA has been aided by the availability of high quality software and powerful personal computers. Section 11.4 is a review of the qualification of NIR and Raman spectrometers. The criteria for NIR and Raman equipment qualification are described in USP chapters <1119> and < 1120>. The relevant highlights of the new USP chapter on analytical instrument qualification <1058> are also covered. Section 11.5 is a discussion of method validation for quantitative analytical methods based on multivariate statistics. Based on the USP chapter for NIR <1119>, the discussion of method validation for chemometric-based methods is also appropriate for Raman spectroscopy. The criteria for these MVA-based methods are the same as traditional analytical methods accuracy, precision, linearity, specificity, and robustness however, the ways they are described and evaluated can be different. 

A Variable Angle Spectroscopic EUipsometer of the type M200-F (J.A. Woollam Co. Inc., Lincoln, USA) with a spectral range from 245 to 995 nm was used to determine the thickness of the adsorbed polymer layers. Measurements were performed in ambient at three different angles (65, 70, and 75° with respect to the surface normal). For each polymer adlayer, i.e. Sil-PEG (from toluene), Sil-PEG (from acidic aqueous solution), and PLL-g-PEG (from aqueous HEPES buffer), five samples were prepared to obtain statistical data. The measurements were fitted with multilayer models using WVASE32 analysis software. The analysis of optical constants was based on a bulk silicon/ SiOj, layer, fitted in accordance with the Jellison model. After adsorption of the molecules, the adlayer thickness was determined using a Cauchy model A = 1.45, B = 0.01, C = 0). 

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