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Fourier-transform infrared derivative spectroscopy with an improved signal-to-noise ratio
1Department of Electrical Engineering, University of California, Los Angeles, 64-147 Engineering IV Building, Los Angeles, California 90095, USA. fetter@ee.ucla.edu
Abstract:
Infrared derivative spectroscopy is a useful technique for finding peaks hidden in broad spectral features. A data acquisition technique is shown that will improve the signal-to-noise ratio (SNR) of Fourier-transform infrared (FTIR) derivative spectroscopy. Typically, in a FTIR measurement one samples each point for the same time interval. The effect of using a graded time interval is studied. The simulations presented show that the SNR of first-derivative FTIR spectroscopy will improve by 15% and that the SNR of second-derivative FTIR will improve by 34%.
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