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使用主成分分析减少pMAIRS光谱的边缘和噪声

Fringe and Noise Reductions of pMAIRS Spectra Using Principal Component Analysis.

作者信息

Shioya Nobutaka, Shimoaka Takafumi, Hasegawa Takeshi

机构信息

Laboratory of Solution and Interface Chemistry, Division of Environmental Chemistry, Institute for Chemical Research, Kyoto University.

出版信息

Anal Sci. 2017;33(1):117-120. doi: 10.2116/analsci.33.117.

Abstract

Infrared p-polarized multiple-angle incidence resolution spectrometry (pMAIRS) is a promising analytical tool for revealing the molecular orientation quantitatively of each chemical group in a thin film even with surface roughness. The spectra are often disturbed by noise and fringe, however, due to the multiple reflections in the substrate and the film, which makes the quantitative analysis very difficult. Therefore, improvement of the signal to noise (SN) ratio of the spectra is expected. Principal component analysis (PCA), in the present study, is first applied to the noise reduction for pMAIRS spectra of a poly(3-hexylthiophene) spin-coated thin film by employing the spin-speed as the experimental parameter. As a result, high quality pMAIRS spectra are readily obtained, with which highly reliable quantitative discussion is made.

摘要

红外p偏振多角度入射分辨光谱法(pMAIRS)是一种很有前景的分析工具,即使薄膜表面存在粗糙度,也能定量揭示薄膜中每个化学基团的分子取向。然而,由于在基底和薄膜中的多次反射,光谱常常受到噪声和条纹的干扰,这使得定量分析非常困难。因此,人们期望提高光谱的信噪比。在本研究中,主成分分析(PCA)首次通过将自旋速度作为实验参数,应用于聚(3-己基噻吩)旋涂薄膜的pMAIRS光谱降噪。结果,很容易获得高质量的pMAIRS光谱,并据此进行了高度可靠的定量讨论。

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