Modified Dual-Site Langmuir Adsorption Equilibrium Models from A GCMC Molecular Simulation

In the modern industrial separation process, the pressure swing adsorption technology is widely used to separate and purify gases due to its low energy consumption, low cost, convenience, reliability, and environmental benignity. The basic elements of the design and application of the pressure swing adsorption process are adsorption isotherms at different temperatures for adsorbents. The dual-site Langmuir (DSL) adsorption equilibrium model is the mostly used model; however, this model is based on the assumption that the adsorption energy on the surface of an adsorbent is uniform and remains unchanged. Here, a grand canonical Monte Carlo (GCMC) molecular simulation was used to calculate the CO2 adsorption equilibrium on MIL-101 (Cr) at 298 K. MIL-101 (Cr) was chosen, as it has more a general pore structure with three different pores. The calculation results showed that the adsorption energies with different adsorption pressures fitted a normal distribution and the relationship of the average adsorption energies, E with pressures had a linear form described as: E = aP + c. With this relationship, the parameter b = kexp((E/RT)) in the DSL model was modified to b = kexp(((aP + c)/RT)), and the modified DSL model (M-DSL) was used to correlate the adsorption equilibrium data on CO2-MIL-101 (Cr), C2H4-HHPAC, CH4-BPL, and CO2-H-Mordenite, showing better correlations than those of the DSL model. We also extended the parameter q(m) in the M-DSL model with the equation q(m) = k(1) + k(2)T to adsorption equilibrium data for different temperatures. The obtained model (M-TDSL) was checked with the abovementioned adsorption equilibrium systems. The fitting results also indicated that the M-TDSL model could be used to improve the correlation of adsorption equilibrium data for different temperatures. The linear relationship between the average adsorption energy and adsorption pressure could be further tested in other adsorption equilibrium models to determine its universality.