A new approach to removing interference of moisture from FTIR spectrum

An approach is developed to remove the interference of moisture from FTIR spectra. The interference arises from two aspects: the fluctuation on the temperature of the HeNe laser and the fluctuation on the transient concentration of moisture in the light - path of an FTIR spectrometer. The temperature fluctuation on the HeNe laser produces a systematic spectral shift between single-beam sample and background spectra, which often makes spectral subtraction method invalid in removing the interference of moisture. Herein, the Carbo similarity metric (the CAB value) is used to reflect the subtle spectral shift. A database of single-beam background spectra is established based on the concept of big-data and the pigeon-hole theory. The spectral shift is corrected by selecting suitable single-beam background spectra from the database to match with the given single-beam sample spectrum according to the CAB value. The interference caused by the fluctuation of the transient concentration of moisture is removed using a comprehensive 2D-COS method. We apply the approach on two polymeric samples to retrieve high-quality spectra and reliable second derivative spectra without the interference of moisture. The present work provides a new opportunity of obtaining the reliable second derivative spectra in the spectral region masked by moisture. (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

An approach has been developed to eliminate moisture interference in FTIR spectra, utilizing the Carbo similarity metric to reflect subtle spectral shifts and establishing a single-beam background spectrum database based on big data and pigeon-hole theory. The interference caused by moisture fluctuation is removed using a comprehensive 2D-COS method, providing a new opportunity for obtaining reliable second derivative spectra in the spectral region masked by moisture.