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Originally, JR spectra of polymers were measured using a dispersive instrument
equipped with an optical element of prisms or gratings to geometrically disperse
the infrared radiation'. Using a scanning mechanism, the dispersed
radiation is passed over a slit system which isolates the frequency range
falling on the detector. In this manner, the spectrum, that is, the energy
transmitted through a sample as a function of frequency is obtained. This
dispersive JR method is highly limited in sensitivity because most of the
available energy is being thrown away , i. e• , it does not fall on the open
slits and hence does not reach the detector. To improve the sensitivity of
JR, a multiplex optical device was sought which allows the continuous detection
of all of the transmitted energy simultaneously. The Michelson interferometer
is such an optical device and the JR instrumentation which resulted
is termed an Fourier Transform infrared (FT-JR) spectrometer2 The Fourier
transform process was well known to Michelson and his peers, but the computational
difficulty of making the transformation prevented the application of
this powerful technique to spectroscopy. An important advance was made with
the discovery of the fast Fourier transform (FFT) algorithm by Cooley and
Tukey3 which breathed new life into the field of spectroscopy using interferometers
by allowing the calculation of the Fourier transform to be
carried out rapidly. As computers have improved, the time required for a
Fourier transform has been reduced to such an extent that the spectra can be
calculated during the time needed for the moving mirror to return to its
starting position.
When we acquired our first FT-JR instrument, we were impressed with the
performance and depressed by the lack of software to manipulate the spectra.
Since the infrared spectral data from FT-JR are recorded in digital form, a
variety of digital data processing techniques are available to eliminate
spectral distortions. These distortions can arise from such things as sample
scattering and reflection or from sampling devices such as ATR, photoacoustic,
and diffuse reflection. The digital data processing techniques are also used
to isolate spectral features for study and quantification.
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