Abstract
The selective adsorption of porous aromatic frameworks (PAFs) with two different functional groups per aromatic ring from three types of acid gas/N2 binary mixtures was investigated and compared with the comparable performance of PAFs with two of the same functional groups, using Grand Canonical Monte Carlo (GCMC) simulations. The functional groups selected include three electron-donating groups (EDGs: –OH, –NH2, and –CH3) and three electron-withdrawing groups (EWGs: –COOH, –CN, and –NO2). The binary gas mixtures considered for selective capture simulations included CO2/N2 (0.15:0.85), SO2/N2 (0.05:0.95), and H2S/N2 (0.15:0.85). The adsorption isotherms were constructed based on GCMC gas loading, the selectivity was calculated from the adsorption isotherm, and the isosteric enthalpy of adsorption (Qst) of the acid gases was calculated by the fluctuation formula. The results indicate that in general PAFs with two mixed EWGs (mix-EWGs-PAF) have better acid gas capture and selectivity than PAFs with two mixed EDGs (mix-EDGs-PAF). However, the best mix-EDGs-PAF (PAF-3-OH-5-NH2) has as good acid gas loading and selectivity as mix-EWGs-PAF, with the advantage of much higher maximum adsorption limit. In addition, PAF-3-OH-5-NH2 has significantly higher adsorption and selectivity than any other PAFs functionalized with two of the same EDGs, indicating the great potential of mixing two different functional groups on PAF aromatic rings. The results indicate that by mixing two different functional groups, the acid gas loading may follow one of two predicted scenarios: 1. PAF-R-R’ has higher acid gas loading at low pressures with little to no impact on high-pressure adsorption, which is the most desired outcome for the selective adsorption with PAFs; 2. PAF-R-R’ has intermediate acid gas loading compared with PAF-R2 and PAF-R’2, showing no benefit to mixing the two functional groups. Calculations carried out using isosteric enthalpy of adsorption strongly support the predictions of the GCMC adsorption isotherms.
Original language | English (US) |
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Article number | 113672 |
Journal | Computational Materials Science |
Volume | 250 |
DOIs | |
State | Published - Feb 20 2025 |
All Science Journal Classification (ASJC) codes
- General Computer Science
- General Chemistry
- General Materials Science
- Mechanics of Materials
- General Physics and Astronomy
- Computational Mathematics