Prediction of Chromatographic Separation of Eugenol by the Fast Fourier Transform Method
The switching time to change from adsorption to desorption in liquid chromatography, which is the time at which the concentration of the effluent reaches the breakthrough value, is important in the operation, scale-up, and optimisation of chromatographic separation. The switching time can be estima...
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| 主要な著者: | , , , |
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| フォーマット: | 論文 |
| 言語: | English English |
| 出版事項: |
Universiti Putra Malaysia Press
2000
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| オンライン･アクセス: | http://psasir.upm.edu.my/id/eprint/3571/1/Prediction_of_Chromatographic_Separation_of_Eugenol.pdf http://psasir.upm.edu.my/id/eprint/3571/ |
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| 要約: | The switching time to change from adsorption to desorption in liquid chromatography, which is the time at which the concentration of the effluent reaches the breakthrough value, is important in the operation, scale-up, and
optimisation of chromatographic separation. The switching time can be estimated by computer simulation of the chromatographic adsorption column. In this
paper, the theoretical simulation of the chromatographic column of Chen and Hsu (1987) based on the Fast Fourier Transform (FFT) method originally
proposed for chromatographic systems by Hsu using estimated axial diffusivity, film mass transfer coefficient and pore diffusivity obtained from analytical scale
separation, is compared with experimental data of chromatographic separation of eugenol. The use of FIT over more sophisticated techniques such as finite
difference or orthogonal collocation methods was dictated by the simpler computation and the availability of better inverting techniques. The model was
validated by experimental data on chromatographic separation of eugenol on IBondapak CIS analytical column, mobile phase methanol-water (80:20), and
flow rate 0.5 ml/min, at different solution concentration injection at equilibrium
condition. Physical property data required for validation such as equilibrium
adsorption isotherm data was determined experimentally, and mass transfer
data was calculated from normal correlations and from analytical scale separation.
The simulation agreed with experimental data at a Peclet number of 6000, a
bed length parameter of 3.0 and number of samples 90. |
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