Zhang Xiaohua, He Anqi, Guo Ran, Zhao Ying, Yang Limin, Morita Shigeaki, Xu Yizhuang, Noda Isao, Ozaki Yukihiro
Beijing National Laboratory for Molecular Sciences, State Key Laboratory for Rare Earth Materials Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, PR China.
Beijing National Laboratory for Molecular Sciences, State Key Laboratory for Rare Earth Materials Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, PR China; College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen 518060, PR China.
Spectrochim Acta A Mol Biomol Spectrosc. 2022 Jan 15;265:120373. doi: 10.1016/j.saa.2021.120373. Epub 2021 Sep 15.
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 C 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 C 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.
开发了一种从傅里叶变换红外光谱（FTIR）中去除水分干扰的方法。这种干扰来自两个方面：氦氖激光器温度的波动以及FTIR光谱仪光路中水分瞬态浓度的波动。氦氖激光器的温度波动会在单光束样品光谱和背景光谱之间产生系统性的光谱偏移，这常常使光谱减法方法在去除水分干扰时失效。在此，使用碳相似性度量（C值）来反映这种细微的光谱偏移。基于大数据概念和鸽巢理论建立了单光束背景光谱数据库。通过根据C值从数据库中选择合适的单光束背景光谱与给定的单光束样品光谱进行匹配来校正光谱偏移。使用综合二维相关光谱（2D-COS）方法去除水分瞬态浓度波动引起的干扰。我们将该方法应用于两个聚合物样品，以获取无水分干扰的高质量光谱和可靠的二阶导数光谱。目前的工作为在被水分掩盖的光谱区域获得可靠的二阶导数光谱提供了新的机会。
