Langmuir, Vol.36, No.29, 8597-8609, 2020
Selective Adsorption of C-6, C-8, and C-10 Linear alpha-Olefins from Binary Liquid-Phase Olefin/Paraffin Mixtures Using Zeolite Adsorbents: Experiment and Simulations
The adsorption separation of gaseous olefin/paraffin using porous materials has been extensively studied from both experimental and molecular simulation perspectives, while the adsorption separation of liquid-phase olefin/paraffin has been much less studied. One of the most important reasons for this is that it is difficult to measure the actual adsorption capacity of liquid-phase adsorption separation directly through experiments, and the simulation results of most studies are compared to gas-phase measurements. In this paper, the selective adsorption of linear alpha-olefins from three binary liquid-phase olefin/paraffin mixtures, 1-hexene/n-hexane (C-6), 1-octene/n-octane (C-8), and 1-decene/n-decane (C-10), by zeolite adsorbents was systematically investigated using batch adsorption experiments and configurational-bias grand canonical Monte Carlo (CB-GCMC) simulations. In the batch experiments, based on the liquid-phase measurement method of the actual adsorption capacity that we developed, a modified commercial SA zeolite with a relatively large pore volume and surface area was used for adsorption. The results showed that the modified SA zeolite had larger actual adsorption capacities for C-6 and C-8 linear alpha-olefins, which increased by 51% and 56%, respectively, than the standard SA zeolite that was used in our previous work. The adsorption isotherms of C-6, C-8, and C-10 in the SA and 13X zeolites were calculated by CB-GCMC simulations. The visualized results of density profiles showed that the olefin molecules were densely distributed at the edge of the zeolite cages and that there were cases where a single molecule was adsorbed over two adjacent cages. The good agreement between the experimental and simulated data proves the completeness of the liquid-phase measurement method that we developed and the reliability of the simulation prediction.