Estimation of second order rate constants using chemometric methods with kinetic constraints.
Estimation of second order rate constants using chemometric methods with kinetic constraints.
复制标题
使用具有动力学约束的化学计量方法估计二阶速率常数。
DOI：
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发表时间：
2002
期刊：
影响因子：
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通讯作者：
R. Brereton
中科院分区：
文献类型：
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作者：
T. J. Thurston;R. Brereton
本文介绍了几种测定U + V -> W型二级反应速率常数的方法，这些方法采用化学计量学和硬模型分析紫外吸收光谱数据，其中所有物质的吸收浓度和吸收率相当。这种类型的反应的一个有趣的特点是，在反应中的步骤的数量小于吸收物种的数量，导致在秩亏响应矩阵。当使用文献中描述的一些方法时，这可能会导致问题。本文中讨论的方法部分取决于系统的可用知识，包括反应物和产物的光谱，初始浓度和确切的动力学。有时，这些信息中的一些可能无法获得或可能难以估计。五组的方法进行了讨论，即使用多元线性回归，以获得浓度曲线和拟合动力学信息，秩增广使用多个批次运行，差异光谱为基础的方法，混合光谱的方法，将反应作为两个独立的假物种，和主成分回归。模拟了两个数据集，一个数据集的光谱截然不同，另一个数据集的反应物和产物的光谱高度重叠。三个来源的误差被认为是，即采样误差，仪器噪声和初始浓度的误差。每种方法的相对优点进行了讨论。
Several methods are described for determining rate constants for second order reactions of the form U + V --> W using chemometrics and hard modelling to analyse UV absorption spectroscopic data, where all species absorb with comparable concentrations and extinctions. An interesting feature of this type of reaction is that the number of steps in the reaction is less than the number of absorbing species, resulting in a rank-deficient response matrix. This can cause problems when using some of the methods described in the literature. The approaches discussed in the paper depend, in part, on what knowledge is available about the system, including the spectra of the reactants and product, the initial concentrations and the exact kinetics. Sometimes some of this information may not be available or may be hard to estimate. Five groups of methods are discussed, namely use of multiple linear regression to obtain concentration profiles and fit kinetics information, rank augmentation using multiple batch runs, difference spectra based approaches, mixed spectral approaches which treat the reaction as two independent pseudospecies, and principal components regression. Two datasets are simulated, one where the spectra are quite different and the other where the spectrum of one reactant and the product share a high degree of overlap. Three sources of error are considered, namely sampling error, instrumental noise and errors in initial concentrations. The relative merits of each method are discussed.