Effects of Molecular Properties on Adsorption of Six-Carbon VOCs by Activated Carbon in a Fixed Adsorber

Gravimetric adsorption equipment with a micro-balance was used to measure the adsorption of volatile organic compounds (VOCs) by activated carbon from 288 to 313 K. VOCs [n-hexane, cyclohexane, 1-hexene, 2-methylpentane, 3-methylpentane, 2,2-dimethylbutane, acetone, butanone, and 2-pentanone (Pentan-2-one)] were used as adsorbates in the adsorption system. Considering the geometric barrier, the critical diameter, and the boiling point, the adsorption capacities for six-carbon (C-6) alkane isomers decrease in the order of n-hexane, 3-methylpentane, and 2-methylpentane. The adsorbates, including nonpolar or weakly polar substances, and substances with smaller geometric obstacles and smaller molecular weights, were more easily adsorbed by the activated carbon. However, the dipole-dipole interactive force at higher pressures resulted in a higher adsorption capacity for 1-hexene than for n-hexane. Both polarity and molecular size should be considered in the analysis of the adsorption of ketones by activated carbon. The adsorption equilibrium constants decreased with increases in temperature because a higher temperature was unfavorable for adsorption. The results for the Toth adsorption isotherm model fitted by the adsorption data showed that the experimental data and the Toth adsorption isotherm model were consistent with each other, as evidenced by the low deviation between the experimental data and those from the fitted model.

Automated summary

Gravimetric adsorption equipment with a micro-balance was used to measure the adsorption of volatile organic compounds (VOCs) by activated carbon in the temperature range of 288 to 313 K. The results showed that nonpolar or weakly polar substances with smaller molecular weights were more easily adsorbed by the activated carbon, and increasing temperature had a negative impact on adsorption equilibrium constants. The Toth adsorption isotherm model fitting results indicated good consistency between experimental data and model predictions.