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Methodologies for the Taylor dispersion analysis for mixtures, aggregates and the mitigation of buffer mismatch effects

机译:混合物,聚集体和缓和缓冲液失配效应的泰勒分散分析方法

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Taylor Dispersion Analysis (TDA) is a fast and simple method for determining hydrodynamic radii. For a mixture of solutes, current TDA methods lead to an average hydrodynamic radius for the different constituents of the mixture. In this paper, we first derive this average for the fitting method. Next, we present a method of deconvoluting a taylorgram from a mixture into its constituent taylorgrams so that the hydrodynamic radii and relative proportions of the individual components can be obtained. Using the differentials and integrals of the taylorgram, near-accurate initial estimates for the parameters of the constituent taylorgrams are obtained. These are used as seed parameters in least-squares fitting algorithms which find the optimum solutions for the constituent taylorgrams. Furthermore, the proximity of the seed parameters to the solutions is a measure of the confidence in the accuracy of the fits. The method is applied to two-, three- and four-component mixtures as well as aggregated samples with good agreement obtained between the results and the expected values. In addition, a fitting method which mitigates the effect of concentration mismatches between the eluent phase and the sample matrix phase is presented.
机译:泰勒色散分析(Taylor Dispersion Analysis,TDA)是一种确定流体动力学半径的快速简便的方法。对于溶质混合物,当前的TDA方法可得出混合物中不同成分的平均流体动力学半径。在本文中,我们首先得出拟合方法的平均值。接下来,我们提出了一种将泰勒图从混合物中解卷积成其组成泰勒图的方法,以便获得各个部件的流体动力学半径和相对比例。使用该泰勒图的微分和积分,可以获得构成泰勒图的参数的近似准确的初始估计。这些在最小二乘拟合算法中用作种子参数,最小二乘拟合算法可找到构成单元图的最佳解决方案。此外,种子参数与解的接近程度是对拟合精度的置信度的度量。该方法适用于二组分,三组分和四组分混合物以及聚集的样品,结果与预期值之间具有良好的一致性。此外,提出了一种拟合方法,该方法可减轻洗脱液相与样品基质相之间浓度失配的影响。

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