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一维欠采样对全二维分离中有效峰容量的影响。

Effect of first-dimension undersampling on effective peak capacity in comprehensive two-dimensional separations.

作者信息

Davis Joe M, Stoll Dwight R, Carr Peter W

机构信息

Department of Chemistry and Biochemistry, Southern Illinois University at Carbondale, Carbondale, Illinois 62901, USA.

出版信息

Anal Chem. 2008 Jan 15;80(2):461-73. doi: 10.1021/ac071504j. Epub 2007 Dec 13.

Abstract

The objective of this work is to establish a means of correcting the theoretical maximum peak capacity of comprehensive two-dimensional (2D) separations to account for the deleterious effect of undersampling first-dimension peaks. Simulations of comprehensive 2D separations of hundreds of randomly distributed sample constituents were carried out, and 2D statistical overlap theory was used to calculate an effective first-dimension peak width based on the number of observed peaks in the simulated separations. The distinguishing feature of this work is the determination of the effective first-dimension peak width using the number of observed peaks in the entire 2D separation as the defining metric of performance. We find that the ratio of the average effective first-dimension peak width after sampling to its width prior to sampling (defined as ) is a simple function of the ratio of the first-dimension sampling time (t(s)) to the first-dimension peak standard deviation prior to sampling (1sigma): = square root1+0.21(t /(s)(1) sigma(2) This is valid for 2D separations of constituents having either randomly distributed or weakly correlated retention times, over the range of 0.2 </= t(s)/1 sigma < or = 16. The dependence of on t(s)/1 sigma from this expression is in qualitative agreement with previous work based on the effect of undersampling on the effective width of a single first-dimension peak, but predicts up to 35% more broadening of first-dimension peaks than is predicted by previous models. This simple expression and accurate estimation of the effect of undersampling first-dimension peaks should be very useful in making realistic corrections to theoretical 2D peak capacities, and in guiding the optimization of 2D separations.

摘要

这项工作的目的是建立一种方法,用于校正全二维(2D)分离的理论最大峰容量,以考虑一维峰欠采样的有害影响。对数百种随机分布的样品成分进行了全二维分离模拟,并使用二维统计重叠理论根据模拟分离中观察到的峰数计算有效一维峰宽。这项工作的显著特点是使用整个二维分离中观察到的峰数作为性能的定义指标来确定有效一维峰宽。我们发现,采样后平均有效一维峰宽与其采样前宽度的比值(定义为β)是一维采样时间(ts)与采样前一维峰标准偏差(σ1)比值的一个简单函数:β = √(1 + 0.21(ts/σ1)²)。这对于保留时间随机分布或弱相关的成分的二维分离是有效的,在0.2 ≤ ts/σ1 ≤ 16的范围内。该表达式中β对ts/σ1的依赖性与先前基于一维峰欠采样对单个一维峰有效宽度影响的工作在定性上一致,但预测的一维峰展宽比先前模型多高达35%。这种简单的表达式以及对一维峰欠采样效应的准确估计,对于对理论二维峰容量进行实际校正以及指导二维分离的优化应该非常有用。

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