Pous-Torres S, Baeza-Baeza J J, Torres-Lapasió J R, García-Alvarez-Coque M C
Departament de Química Analítica, Universitat de València, c/Dr. Moliner 50, 46100 Burjassot, Spain.
J Chromatogr A. 2008 Sep 26;1205(1-2):78-89. doi: 10.1016/j.chroma.2008.07.088. Epub 2008 Aug 5.
Peak capacity (i.e. maximal number of resolved peaks that fit in a chromatographic window) is a theoretical concept with growing interest, but based on a situation rarely met in practice. Real chromatograms tend to have uneven distributions, with overlapped peaks and large gaps. The number of resolved compounds should, therefore, be known from estimations. Several equations have been reported for this purpose based on three perspectives, namely, the intuitive approach (peak capacity as the size of the retention time window measured in peak width units), which assumes peaks with the same width, and the outlines of Giddings and Grushka, which consider changes in peak width with retention time. In this work, the peak capacity concept is discussed and three new approaches are derived based on realistic descriptions of peak shape. The first one is based on the Grushka's approach and considers the contributions of column and extra-column peak variances. The second one relies on Giddings' and assumes asymmetrical peaks where left and right peak half-widths depend linearly on retention time. The third equation, based on the intuitive approach, uses a mean peak width obtained by integration, instead of a mean value from several representative peaks. The accuracy of the classical Giddings' approach for ideal peaks, a modification of the Grushka's approach that considers variation of peak width at half-height, and the three new approaches were checked on combined chromatograms built by adding real peaks. The results demonstrate that the change in efficiency (and not in skewness) is the relevant factor, at least in the studied examples. Also, peak width should be measured at low peak height ratios (i.e. 10%) to better account peak deformation.
峰容量(即适合在色谱窗口中分辨的最大峰数)是一个受到越来越多关注的理论概念,但基于实际中很少遇到的情况。实际色谱图往往具有不均匀的分布,存在峰重叠和大的间隙。因此,分辨出的化合物数量应该通过估算得知。基于三个视角已经报道了几个用于此目的的方程,即直观方法(将峰容量视为以峰宽单位测量的保留时间窗口大小),该方法假设峰具有相同宽度,以及吉丁斯(Giddings)和格鲁什卡(Grushka)的轮廓,它们考虑了峰宽随保留时间的变化。在这项工作中,讨论了峰容量概念,并基于峰形的实际描述推导了三种新方法。第一种基于格鲁什卡的方法,考虑了柱内和柱外峰方差的贡献。第二种依赖于吉丁斯的方法,假设峰不对称,其中左右峰半高宽与保留时间呈线性关系。第三个方程基于直观方法,使用通过积分获得的平均峰宽,而不是几个代表性峰的平均值。通过添加真实峰构建的组合色谱图检验了理想峰的经典吉丁斯方法、考虑半高峰宽变化的格鲁什卡方法的修正以及三种新方法的准确性。结果表明,效率的变化(而非偏度的变化)是相关因素,至少在所研究的示例中如此。此外,应在低峰高比(即10%)下测量峰宽,以更好地考虑峰变形。