Computer applications, FTIR

Figure 4 FTIR microscopy of polyethylene cable insulation. (A) Water-tree, (B) undamaged area, and (C) the difference spectrum (A) (B). (Parker SF (1995) Industrial applications of vibrational spectroscopy and the role of the computer. In George WO and Steele D (eds.) Computing Applications in Molecular Spectroscopy, pp. 181-199. Cambridge The Royal Society of Chemistry reproduced by permission of The Royal Society of Chemistry.)...

Brooks A.L., Afanasyeva N.I., Makhine V., Bruch R.F., McGregor B., FEW-FTIR Spectroscopy Applications and Computer Data Processing for Noninvasive Skin Tissue Diagnostics In Vivo, SPIE, 1999 3596 140-151. 

The advent of computers and Fourier transform completely revolutionized the detection and identification of organic compounds. Modern automated instruments allow very small samples in the nanogram (10 g) range to be characterized in a very short time. The application of Fourier transform nuclear magnetic resonance (FTNMR) and Fourier transform infrared (FTIR) allows recovery of the sample in contrast to mass spec-trometric (MS) determination which is a destructive but quite often a necessary technique. 

The application of FTIR in chemistry, its unique features, and the relevant instrumentation are well documented [34,35], In brief, an FUR spectrometer is based on a Michelson interferometer that provides a spectrum in the time domain which is Fourier-transformed by a computer to a spectrum in the frequency domain. The sample can be scanned repeatedly, and the accumulated spectra can be averaged, thus producing a representative IR spectrum of a very high signal to noise ratio. This enables the measurement of samples containing a very low concentra-... 

In this review we will attempt to critically assess the application of FTIR procedures to the characterization of the structure of coal. To an extent much of what we have to say is not original. Difficulties, such as those mentioned above for curve resolving, were encountered and addressed a number of years ago. However, with the advent of any new instrumentation there is a tendency to ignore segments of previous work that were obtained on inferior machines and in effect spend a considerable amount of time and effort reinventing the wheel. Accordingly, we will not simply review the results of the FTIR studies of coal published to date, but first consider the use of certain computer routines. 

FTIR takes a completely different approach. The spectral data are acquired as an Interferogram (Figure 1) which must be transformed Into a plot of Intensity versus wavenumber or wavelength through the application of Fourier transform equations. Thus, the computer Is an Integral part of the system without which little useful Information could be obtained. FTIR has the following advantages over computerized dispersive Infrared spectroscopy ... 

The improvement in computer technology associated with spectroscopy has led to the expansion of quantitative infrared spectroscopy. The application of statistical methods to the analysis of experimental data is known as chemometrics [5-9]. A detailed description of this subject is beyond the scope of this present text, although several multivariate data analytical methods which are used for the analysis of FTIR spectroscopic data will be outlined here, without detailing the mathematics associated with these methods. The most conunonly used analytical methods in infrared spectroscopy are classical least-squares (CLS), inverse least-squares (ILS), partial least-squares (PLS), and principal component regression (PCR). CLS (also known as K-matrix methods) and PLS (also known as P-matrix methods) are least-squares methods involving matrix operations. These methods can be limited when very complex mixtures are investigated and factor analysis methods, such as PLS and PCR, can be more useful. The factor analysis methods use functions to model the variance in a data set. 

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