Modeling and Optimization on the Carbon Dioxide Separation from Natural Gas Using Hydrotalcite-Silica Membrane

Abstract

The process modeling and optimization of carbon dioxide (CO2) separation from carbon dioxide-methane (CH4) binary gas mixture through hydrotalcite (HT)-silica membrane using statistical design of experiments (DoE) is reported in this study. The effect of three important process variables, pressure difference across the membrane (100-500 kPa), temperature (30-190oC) and CO2 feed concentration (10-50%) on the CO2 separation performance of the membrane were investigated. The response surface methodology (RSM) coupled with central composite design (CCD) was used to build up two models to correlate the effect of process conditions to CO2 permeance and CO2/CH4 separation selectivity. The analysis of variance (ANOVA) of the quadratic model at 95% confidence interval confirmed that the model was highly significant. The CO2 feed concentration with 43% showed the best performance with a CO2 permeance of 6.0x10-7 mol.m-2.s-1.Pa-1 and a CO2/CH4 separation selectivity of 109 at 100 kPa pressure difference across the membrane and temperature of 30oC