標題: 逆向流層析與水相基質萃取關聯性之研究
Correlation of Countercurrent Chromatography and Extraction in Aqueous Matrixes
作者: 梁嘉杉
Liang, Chia-Shang
余艇
Yu, Tiing
應用化學系碩博士班
關鍵字: 逆向流層析;水相基質
公開日期: 1997
摘要: 本實驗室先前以逆向流屋析儀進行超臨界流體萃取與層析的實驗,並建立萃取與層析間的數學相關式,由層析的數據要預測萃取的結果。萃取回收率的計算分兩階段來進行,首先將萃取槽等分成有限層,以逆向流分佈(Counter-current distribution, CCD)的模式計算動相穿越靜相時,分析物在管內的濃度分佈;然後每一層分析物同時進行層析,而由實際的層析數據可計算得每個假想層析峰的分佈函數,再將所有的層析峰累加起來即可得模擬萃取回收率圖。 本研究的萃取與層析是在液相╱液相系統中進行,並用層析(Chromatography,CH)的模式修正管內濃度分佈,其萃取回收率的預測結果比CCD模式更接近於實驗值,不論對超臨界流體萃取或液相╱液相萃取的模擬都有明顯的改善,而對於capacity factor (k')較小的樣品會有較大的改善。理論與實驗之間偏差的主要原因,來自分析物在管柱內由濃度梯度所造成的擴散行為,這也使得每一個假想層析峰不會呈理想的高斯分佈。
A mathematical model was employed to simulate supercritical fluid extraction (SFE) efficency with supercritical fluid chromatography (SFC) data in a previous study. The SFE extraction vessel, i.e., the column for SFC, was mathematically divided into limited layers. Two steps achieved the calculation of extraction efficiency. The analyte mass was uniformly distributed in the vessel before extraction. However,it changed when the fluid flowed through the aqueous sample and reached the column outlet. The mass distribution was computed using a countercurrent distribution (CCD) approach. Afterwards, each layer was considered to undergo a chromatographic process. Each layer's chromatographic calpacity factor and peak width were caculated using true SFC experimental data and the sum of all these peak distributions as a function of time gave the extraction efficiency. In this work, the mass redistrbution was calculated through a chromatographic approach, which predicted the extration recovery better than the previous model. Both the previous SFE and newly acquired liquid/liquid extrction data using countercurrent chromatographic apparatus were examined to demonstrate the upgrading of the model using this new chromatographic approach. Significant improvements were observed, especially for the analytes with smaller capacity factors. The simulation deviations came mainly from the fact that analyte molecules in the individual layers would shift away from Gaussian shapes which was assumed in the model.
URI: http://140.113.39.130/cdrfb3/record/nctu/#NT863500026
http://hdl.handle.net/11536/63565
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