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Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 57,
  • Issue 2,
  • pp. 176-185
  • (2003)

Accurate Wavelength Measurements of a Putative Standard for Near-Infrared Diffuse Reflection Spectrometry

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Abstract

The diffuse reflection (DR) spectrum of a sample consisting of a mixture of rare earth oxides and talc was measured at 2 cm<sup>-1</sup> resolution, using five different accessories installed on five different Fourier transform near-infrared (FT-NIR) spectrometers from four manufacturers. Peak positions for 37 peaks were determined using two peak-picking algorithms: center-of-mass and polynomial fitting. The wavenumber of the band center reported by either of these techniques was sensitive to the slope of the baseline, and so the baseline of the spectra was corrected using either a polynomial fit or conversion to the second derivative. Significantly different results were obtained with one combination of spectrometer and accessory than the others. Apparently, the beam path through the interferometer and DR accessory was different for this accessory than for any of the other measurements, causing a severe degradation of the resolution. Spectra measured on this instrument were removed as outliers. For measurements made on FT-NIR spectrometers, it is shown that it is important to check the resolution at which the spectrum has been measured using lines in the vibration-rotation spectrum of atmospheric water vapor and to specify the peak-picking and baseline-correction algorithms that are used to process the measured spectra. The variance between the results given by the four different methods of peak-picking and baseline correction was substantially larger than the variance between the remaining five measurements. Certain bands were found to be more suitable than others for use as wavelength standards. A band at 5943.13 cm<sup>-1</sup> (1682.62 nm) was found to be the most stable band between the four methods and the six measurements. A band at 5177.04 cm<sup>-1</sup> (1931.61 nm) has the highest precision between different measurements when polynomial baseline correction and polynomial peak-picking algorithms are used.

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