超臨界流體水相基質萃取與層析關聯性之研究

Abstract

本研究的目的在於建立超臨界流體萃取與層析間的數學相關式，期望以層析的方法來 預測分析物的萃取結果，並利用之做為萃取條件最佳化的方法。這個想法來自於層析 與萃取的相似性；因為在相同的實驗條件下，包括溫度、壓力、基質、流速等等，若 將萃取槽等分割成許多分層，並將各分層視為各自獨立的個體，那麼整個萃取的過程 似乎就可以以層析的觀點來看待之。如此，那麼影響萃取的複雜因素就可以用簡單的 層析參數k(（capacity factor）將之簡化不少。 到目前為止的結果顯示，我們的數學模式對k(值較大的分析物（k(在0.901以上）有較 佳的預測結果；對於k(值較小的分析物，萃取預測結果和實驗值有較大的差異， 但我們已能從提出的模式中判斷其偏差的趨勢。 提出的模式中判斷其偏差的趨勢。

A mathematical modeling is established in this study to correlate supercritical fluid chromatography (SFC) in aqueous stationary phase with supercritical fluid extraction (SFE) in aqueous matrices. A solar coaxial countercurrent chromatography was applied for both SFC and SFE experiments. The extraction vessel, i.e. the column for SFC, was mathematically divided into limited layers. During the extraction, each layer was considered undergoing a chromatographic process. The plate heights of all the layers was assumed equal throughout the column. The capacity factor and peak broadening for each "imaginary" chromatographic peak were calculated by the true SFC experimental data. Accordingly, the analyte recovery curve of SFE can be simulated with SFC data using this model. Since operations of SFC are more straightforward than those of SFE, optimization of SFE may be more easily achieved with this mathematical correlation. The simulated data of analytes with capacity factor greater than 0.9 mathch the experimental results very well. Deviations become gradually greater while capacity factors of analytes decrease. A rationale was proposed to successfully interpret this deviation trend.