Department of Chemistry University of Pittsburgh 219 Parkman Avenue Pittsburgh, Pennsylvania 15260, United States.
Anal Chem. 2016 Dec 6;88(23):11742-11749. doi: 10.1021/acs.analchem.6b03368. Epub 2016 Nov 16.
The general limitations on liquid chromatographic performance in isocratic and gradient elution are now well understood. Many workers have contributed to this understanding and to developing graphical methods, or plots, to illustrate the capabilities of chromatographic systems over a wide range of values of operational parameters. These have been invaluable in getting a picture, in broad strokes, about the value of changing an operational parameter or the value of one separation approach over another. Here we present a plotting approach more appropriate for determining how to use chromatography most efficiently in one's own laboratory. The axes are linear: column length vertical and mobile phase velocity horizontal. In this coordinate system, straight lines with intercept zero correspond to different values of t. Hyperbolas correspond to values of pressure as the product of length and velocity is proportional to pressure. For a given relationship between theoretical plate height and velocity (e.g., van Deemter), the number of theoretical plates as a function of column length and mobile phase velocity is a surface (z direction) to the x and y of velocity and length. By representing the surface as contours, a two-dimensional plot results. Any point along a constant pressure hyperbola represents the best one can do given the particle diameter, solute diffusion coefficient, and temperature. The user can quickly see how to use the pressure for speed or for more theoretical plates. Sets of such plots allow for comparisons among particle diameters or temperatures. Analogous plots of peak capacity for gradient elution are equally revealing. The plots lead instantly to understanding liquid chromatographic optimization at a practical level. They neatly illustrate the value (or not) of changing pump pressure, particle diameter, or temperature for fast or slow separations in either isocratic or gradient elution. They are illustrated with a focus on maximizing plate count with a given analysis time (isocratic), the effect of volume overload (isocratic), and separations of a limited number of peptides with a peak capacity coming from statistical peak overlap theory (gradient).
现在，人们已经很好地理解了在等度和梯度洗脱中液相色谱性能的一般限制。许多工作者为这一理解和开发图形方法做出了贡献，这些图形方法或图，用于说明色谱系统在操作参数的广泛范围内的能力。这些方法在概括地了解改变操作参数或一种分离方法相对于另一种方法的价值方面非常有价值。在这里，我们提出了一种更适合于确定如何在自己的实验室中最有效地使用色谱法的绘图方法。坐标轴是线性的：柱长为垂直轴，流动相速度为水平轴。在这个坐标系中，截距为零的直线对应于不同的 t 值。双曲线对应于压力值，因为长度和速度的乘积与压力成正比。对于理论板高度和速度之间的给定关系（例如，van Deemter），理论板数作为柱长和流动相速度的函数是一个表面（z 方向）到速度和长度的 x 和 y。通过将表面表示为等高线，得到一个二维图。任何沿恒压双曲线的点都代表在给定粒径、溶质扩散系数和温度下可以达到的最佳效果。用户可以快速了解如何利用压力来提高速度或获得更多的理论板数。这样的图组可以用于比较粒径或温度。梯度洗脱的峰容量的类似图同样具有启发性。这些图立即让人们在实际层面上理解液相色谱的优化。它们简洁地说明了在等度或梯度洗脱中，为了快速或缓慢分离，改变泵压、粒径或温度的价值（或无价值）。这些图重点说明了在给定的分析时间内（等度）最大化板数、体积过载的影响（等度）以及通过统计峰重叠理论获得的有限数量肽的分离（梯度）。
