Spectral manipulation techniques, Fourier

Spectral Manipulation Techniques. Many sophisticated software packages are now available for the manipulation of digitized spectra with both dedicated spectrometer minicomputers, as well as larger main - frame machines. Application of various mathematical techniques to FT-IR spectra is usually driven by the large widths of many bands of interest. Fourier self - deconvolution of bands, sometimes referred to as "resolution enhancement", has been found to be a valuable aid in the determination of peak location, at the expense of exact peak shape, in FT-IR spectra. This technique involves the application of a suitable apodization weighting function to the cosine Fourier transform of an absorption spectrum, and then recomputing the "deconvolved" spectrum, in which the widths of the individual bands are now narrowed to an extent which depends on the nature of the apodization function applied. Such manipulation does not truly change the "resolution" of the spectrum, which is a consequence of instrumental parameters, but can provide improved visual presentations of the spectra for study. 

Equation 9 represents the IR spectmm (intensity versus wavenumber), which can be derived from expression (8) using a mathematical technique known as Fourier transformation. Needless to say, this requires spectrometer-interfaced computing power, which additionally provides the capacity for spectral manipulation such as deconvolution, smoothing, and subtraction. 

Many sophisticated data manipulation techniques used in NMR spectroscopy were ushered in together with Fourier transform NMR. Specifically, FT introduced spectroscopists to the power of dealing with information in both the time and frequency domains. These data manipulation techniques are also available for use on cw spectra, which can be Fourier transformed into the time domain to carry out such operations, if necessary, and then transformed back to the spectral representation. Having the opportunity to manipulate the data both in the time and the frequency domain adds greatly to the ability to refine the data. 

No discussion has been devoted to the recent use of Fourier transform spectrometers rather than dispersion instruments. The ease with which the spectral data can be manipulated and background subtracted make the FT methods particularly useful for studies of surface species, particularly during catalytic reaction. Recently there has been a surge of interest in the coupling of computer subtraction techniques to conventional grating instruments. For many IR surface studies, where only limited frequency range is required, this... 

Enhancement of the accuracy of quantitative infrared determinations by use of mathematical manipulation of the spectral data as performed by Fourier Transform (FTIR) and Coiqruterlzed Dispersive (GDIS) Infrared Spectroscopy has been compared. Cotton-polyester blends and cotton treated with THPOH-NHo and with dimethyloldihydroxy-ethylene urea (DMDHEU) were analyzed by FTIR and GDIS. The mathematical techniques used Included direct spectral subtraction attd spectral subtraction combined with analysis of peak areas. 

Similar spectral techniques as discussed for macroscopic tumour imaging can be employed for fluorescence microscopy. Confocal and two-photon-induced fluorescence microscopy [10.210], and imaging Fourier transform spectroscopy [10.211] are all valuable techniques for studies at the cellular level. Related to this field is the optical trapping of ceils with focused laser beams optical tweezers), which relies on gradient forces of the same kind as discussed in Sect. 9.8.5. Trapped cells and polymer strings can be manipulated in many ways to enable fundamental studies to be conducted [10.212]. 

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