Pure and Binary Adsorption of Methane and Nitrogen on Silicalite

Separation processes comprise a large portion of the activity in the chemical and petrochemical industries. For the chemical, petroleum refining, and materials processing industries as a group, separation processes are considered to be critical. Almost all the applications of chemical industries involves mixtures, so innovation in separation technology not only enhances productivity and global competitiveness of U.S. industries, but is also critical for achieving the industrial energy and waste reduction goals. Traditionally, air separation to produce nitrogen and oxygen and to separate nitrogen from methane was practiced by cryogenic distillation, which involved expensive high pressure units and large requirement of energy. The separation of nitrogen from methane is becoming increasingly important for upgrading LGF (Landfill gas), coal gas, and natural gas. Natural gases contain significant amounts of nitrogen. From the environmental perspective, Methane is the most important non-CO2 greenhouse gas responsible for global warming with more than 10 % of total greenhouse gas emissions. Adsorption separation techniques are used widely among other separation processes as they tend to utilize fewer resources and are highly energy efficient. By considering the advantages of adsorption processes over other separation processes, it is of great interest to characterize the adsorption properties of microporous and nanoporous solid materials for their potential use as an alternative to the conventional catalytic separation process, and storage applications. Despite the advantages of using adsorption for methane upgrading, methane-nitrogen separation has been found particularly difficult because of the lack of satisfactory adsorbent. The equilibrium selectivity favors methane over nitrogen (or high methane/nitrogen selectivity) for all known adsorbents. Therefore, it is one of the objective of this study to check the potential application of silicalite adsorbent in natural gas upgrading. Plenty of data is available in the literature for pure component but not for the binary mixtures as it is very time consuming and involves tedious calculations for quantifying binary adsorption measurement. According to some statistics, there are more models to predict multicomponent adsorption than accurate data to test them. So the effort made here was to complete measurements of the binary adsorption isotherms, compare those with Ideal Adsorbed Solution Theory (IAST) predictions and the experimental data available in the literature. This study reviews one of the most commonly used technique (i.e. volumetric measurement) for pure and binary adsorption isotherm measurement for methane and nitrogen on silicalite adsorbent. This method involves measuring the pressure change in a known volume of gas subjected to adsorption. As the gas is adsorbed and allowed to reach equilibrium, the measured decrease in the system pressure yields the amount of gas adsorbed under the given conditions. Pure adsorption equilibria for the gases listed above was measured at three different temperatures (283.15 K, 308.15 K and 338.15 K). The virial equation of state was used to correlate the experimental data, to calculate the Henry’s law constants and the heats of adsorption at zero loading. Ideal separation factor (selectivity) was obtained from the experimental pure adsorption isotherms by using the virial isotherm model. Binary adsorption behavior for methane and nitrogen mixture, covering the whole concentration range at 308.15 °K and at 504 kPa was determined experimentally. The corresponding x-y diagrams and selectivity were obtained from these data. The experimental results were compared with the results predicted from a mixture adsorption model, IAST. It was found that IAST successfully predicted the total amount adsorbed throughout the concentration range. There is a considerable deviation in selectivity as well as partial amount adsorbed for both the species at higher pressure. The reason is attributable to the fact that selectivity is much more sensitive to uncertainties in the measurement