Self-modeling mixture analysis applied to FT-Raman spectral data of hydrogen peroxide activation by nitriles
Self-modeling mixture analysis applied to FT-Raman spectral data of hydrogen peroxide activation by nitriles
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DOI：
10.1366/0003702971940288
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发表时间：
1997-03-01
影响因子：
3.5
通讯作者：
Legrand, P
中科院分区：
文献类型：
--
作者：
Vacque, V;Dupuy, N;Legrand, P
在分析环境中，样品分析产生的光谱数据通常代表几种组分的混合物。这类混合物的纯组分的信息提取是一个主要问题，特别是当参考光谱不可用时或当形成不稳定的中间体时。自建模多元混合物分析已被开发用于这类问题，在本文中，两个例子将被用来显示这种技术的潜力，再加上FT-拉曼光谱，以阐明反应机理，并遵循原位的化学转化的动力学。
In the analytical environment, spectral data resulting from analysis of samples often represent mixtures of several components. Extraction of information about pure components of these kinds of mixtures is a major problem, especially when reference spectra are not available or when unstable intermediates are formed. Self-modeling multivariate mixture analysis has been developed for this type of problem, In this paper two examples will be used to show the potential of this technique coupled with FT-Raman spectroscopy to elucidate reaction mechanisms and to follow in situ the kinetics of chemical transformations.