Multi-response optimization of MIL-101 synthesis for selectively adsorbing N-compounds from fuels
Abstract In this work, MIL-101, a metal organic framework, has been synthesized and examined in the adsorptive denitrogenation process. Due to the importance of adsorption capacity and selectivity, the effects of synthesis parameters including metal type, reagent ratio, time and temperature on the M...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
SpringerOpen
2019-07-01
|
Series: | Petroleum Science |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1007/s12182-019-0351-5 |
Summary: | Abstract In this work, MIL-101, a metal organic framework, has been synthesized and examined in the adsorptive denitrogenation process. Due to the importance of adsorption capacity and selectivity, the effects of synthesis parameters including metal type, reagent ratio, time and temperature on the MIL-101 performance were investigated by measuring quinoline (QUI) separation from iso-octane. The optimum conditions were determined using a Taguchi experimental design and the multi-response optimization (multivariate statistical) method. Based on the arithmetic mean of normalized QUI adsorption capacity and QUI/dibenzothiophene (DBT) selectivity, as the objective function, the optimum value of synthesis parameters were found to be manganese as metal type in the structure, 180 °C for synthesis temperature, 15 h for synthesis time and 1.00 for reagent molar ratio. Under these conditions, QUI adsorption capacity and QUI/DBT selectivity were 19.3 mg-N/g-Ads. and 24.6, respectively. Accordingly, the arithmetic mean between normalized values of these measured parameters was equal to 1.10, which is in good agreement with the predicted value. The MIL-101 produced under optimum conditions was characterized by determining its specific surface area, X-ray powder diffraction patterns and Fourier transform infrared spectroscopy. Finally, isotherm and kinetic studies indicate that the Langmuir isotherm and pseudo-first-order model can successfully describe the experimental data. |
---|---|
ISSN: | 1672-5107 1995-8226 |