University of Bonn, Institute of Nutritional and Food Sciences, Chair of Food Chemistry - Department Fast GC, Endenicher Allee 11 - 13, 53115 Bonn, Germany.
University of Bonn, Institute of Nutritional and Food Sciences, Chair of Food Chemistry - Department Fast GC, Endenicher Allee 11 - 13, 53115 Bonn, Germany; Hyperchrom GmbH Germany, Endenicher Allee 11 -13, 53115, Bonn, Germany.
J Chromatogr A. 2023 Sep 27;1707:464301. doi: 10.1016/j.chroma.2023.464301. Epub 2023 Aug 14.
The development of new analytical methods can save resources, time and costs if there are prediction tools like computer simulation which support the optimization process. In GC the distribution-centric 3-parameter model (K-centric model) is well established for prediction of retention factors k and retention times but laborious isothermal measurements for determination of the characteristic parameters are needed. For the most important parameter, the characteristic temperature T, the search for simpler determination methods or even estimates is an interesting research topic. In this work the elution temperatures for 37 fatty acid methyl esters, 6 BTEXs and 40 other volatile substances are determined by measurements under variable heating rates, initial temperatures, constant pressure mode and constant flow mode. The relationship between the measured elution temperature and the characteristic temperature was investigated. The novel multivariate curve fit model presented in this study describes accurately the relation between the characteristic temperature T and elution temperatures T under variable heating rates R, respectively, and initial temperature T conditions. The novel model shows good accordance to earlier estimation models and expands the prediction range, especially for high volatile compounds. The model is suitable for determination of T by estimated T and vice versa. Predictions of retention times of simple temperature programs were also possible by using the model with relative deviations < 5% compared to measurements.
如果有预测工具(如计算机模拟)支持优化过程,新的分析方法的发展可以节省资源、时间和成本。在 GC 中,基于分布中心的三参数模型(K-中心模型)已被广泛用于预测保留因子 k 和保留时间,但需要进行繁琐的等温测量来确定特征参数。对于最重要的参数——特征温度 T,寻找更简单的确定方法甚至是估计方法是一个有趣的研究课题。在这项工作中,通过在不同升温速率、初始温度、恒压模式和恒流模式下进行测量,确定了 37 种脂肪酸甲酯、6 种 BTEX 和 40 种其他挥发性物质的洗脱温度。研究了测量的洗脱温度与特征温度之间的关系。本研究提出的新型多元曲线拟合模型准确地描述了特征温度 T 与不同升温速率 R 下的洗脱温度 T 之间的关系,以及初始温度 T 条件下的关系。新型模型与早期的估计模型吻合较好,并扩展了预测范围,特别是对于高挥发性化合物。该模型适用于通过估计的 T 来确定 T,反之亦然。通过使用该模型,还可以对简单温度程序的保留时间进行预测,与测量值相比,相对偏差 <5%。