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Flexible metal-organic frameworks (MOF) can show exceptional selectivity and capacity for adsorption of CO2. The incorporation of CO2 into flexible MOFs that have Cu2+ coordination centers and organic pillar ligands is accompanied by a distortion of the framework lattice arising from chemical interactions between these components and CO2 molecules. CO2 adsorption yields a reproducible lattice expansion that is enabled by the rotation of the pillar ligands. The structures of Cu2(pzdc)2(bpy) and Cu2(pzdc)2(bpe), CPL-2 and CPL-5, were evaluated using in situ synchrotron x-ray powder diffraction at room temperature at CO2 gas pressures up to 50 atm. The structural parameters exhibit hysteresis between pressurization and depressurization. The pore volume within CPL-2 and CPL-5 increases at elevated CO2 pressure due to a combination of the pillar ligand rotation and the overall expansion of the lattice. Volumetric CO2 adsorption measurements up to 50 atm reveal adsorption behavior consistent with the structural results, including a rapid uptake of CO2 at low pressure, saturation above 20 atm, and hysteresis evident as a retention of CO2 during depressurization. A significantly greater CO2 uptake is observed in CPL-5 in comparison with predictions based on CO2 pressure-induced expansion of the pore volume available for adsorption, indicating that the flexibility of the CPL structures is a key factor in enhancing adsorption capacity.
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Simulating CO2 diffusivity in rigid and flexible Mg-MOF-74 with machine-learning force fields
The flexibility of metal–organic frameworks (MOFs) affects their gas adsorption and diffusion properties. However, reliable force fields for simulating flexible MOFs are lacking. As a result, most atomistic simulations so far have been carried out assuming rigid MOFs, which inevitably overestimates the gas adsorption energy. Here, we show that this issue can be addressed by applying a machine-learning potential, trained on quantum chemistry data, to atomistic simulations. We find that inclusion of flexibility is particularly important for simulating CO2 chemisorption in MOFs with coordinatively unsaturated metal sites. Specifically, we demonstrate that the diffusion of CO2 in a flexible Mg-MOF-74 structure is about one order of magnitude faster than in a rigid one, challenging the rigid-MOF assumption in previous simulations.
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- Award ID(s):
- 2119276
- PAR ID:
- 10588142
- Publisher / Repository:
- American Institute of Physics
- Date Published:
- Journal Name:
- APL Machine Learning
- Volume:
- 2
- Issue:
- 2
- ISSN:
- 2770-9019
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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