Investigating greenhouse gas adsorption in MOFs SIFSIX-2-Cu, SIFSIX-2-Cu-i, and SIFSIX-3-Cu through computational studies

Computational and Machine Learning Methods for CO2 Capture Using Metal-Organic Frameworks

Machine learning (ML) using data sets of atomic and molecular force fields (FFs) has made significant progress and provided benefits in the fields of chemistry and material science. This work examines the interactions between chemistry and materials computational science at the atomic and molecular scales for metal-organic framework (MOF) adsorbent development toward carbon dioxide (CO2) capture. Herein, a connection will be drawn between atomic forces predicted by ML algorithms and the structures of MOFs for CO2 adsorption. Our study also takes into account the successes of atomic computational screening in the field of materials science, especially quantum ML, and its relationship to ML algorithms that clarify advancements in the area of CO2 adsorption by MOFs. Additionally, we reviewed the processes for supplying data to ML algorithms for algorithm training, including text mining from scientific articles, and MOF's formula processing linked to the chemical properties of MOFs. To create ML algorithms for future research, we recommend that the digitization of scientific records can help efficiently synthesize advanced MOFs. Finally, a future vision for developing pioneer MOF synthesis routes for CO2 capture is presented in this review article.

New insight into impact of humidity on direct air capture performance by SIFSIX-3-Cu MOF

Removal of CO2 from air is one of the key human challenges in battling global warming. SIFSIX-3-Cu is a promising metal-organic framework (MOF) suggested for carbon capture even at low CO2 concentrations. However, the impact of humidity on its performance in direct air capture (DAC) is poorly understood. To evaluate the MOF performance for DAC application under humid conditions, we investigate the adsorption of H2O, CO2, and N2 using density functional theory (DFT), grand canonical Monte Carlo (GCMC), and molecular dynamics (MD) simulations. The simulation results show a higher tendency of SIFSIX-3-Cu towards H2O adsorption rather than CO2 (and N2). The results agree with the adsorption isotherms for the pure compounds from the Sips model. The extended Sips model shows 1.34 mmol g-1 CO2 adsorption at the atmospheric pressure and 298 K for the CO2/N2 mixture containing 400 ppm CO2, and low CO2 adsorption (less than 0.75 mmol g-1) at a low relative humidity (RH) of 20%. This finding highlights the efficiency of SIFSIX-3-Cu for DAC in dry air and the negative impact of humidity on the CO2 selective adsorption. Therefore, we suggest to consider the impairing of humidity effects when designing a SIFSIX-3-Cu-based CO2 separation process and removal of any water vapor before introduction of the air to SIFSIX-3-Cu.

Dynamical and electronic properties of anion-pillared metal-organic frameworks for natural gas separation

The increasing demand for natural gas as a clean energy source has emphasized the need for efficient gas separation technologies. Metal-organic frameworks (MOFs) have emerged as a promising class of materials for gas separation, with anion-pillared MOFs (APMOFs) gaining attention for their fine-tuned pore design and shape/size selectivity. In this study, we investigate the dynamical and electronic properties of three APMOFs, SIFSIX-3-Cu, SIFSIX-2-Cu-i, and SIFSIX-2-Cu, for the separation of methane from ethane, ethene, propane, propene, and N using computational simulations. Our simulations employ Grand Canonical Monte Carlo (GCMC) and Molecular Dynamics (MD) techniques combined with Density Functional Theory (DFT) calculations. We find that that all three APMOFs exhibit promising separation capabilities for methane from propane and propene based on both thermodynamics and kinetics parameters. In addition, we use Noncovalent Interaction (NCI) analysis to investigate intermolecular interactions and find that the fluorine atoms in the MOF can polarize gas molecules and establish electrostatic interactions with hydrogen atoms in the molecule. Finally, we show that SIFSIX-2-Cu-i is a potential candidate for separating N2/CH4 due to its interpenetration.

Theoretical Investigations on MIL-100(M) (M=Cr, Sc, Fe) with High Adsorption Selectivity for Nitrogen and Carbon Dioxide over Methane

The removal of impurity gases (N₂ , CO₂ ) in natural gas is critical to the efficient use of natural gas. In this work, the selective adsorption for N₂ and CO₂ over CH₄ on MIL-100 (M) (M=⁴ Cr, ¹⁰ Cr, ⁶ Fe, ¹ In, ¹ Sc, ³ V) is studied by density functional theory (DFT) calculations. The calculated adsorption energy of the large-size cluster model (LC) of MIL-100 (M) shows that the ⁴ MIL-100 (⁴ Cr) is the best at the refinement of natural gas due to the lower adsorption energy of CH₄ (-2.58 kJ/mol) in comparison with that of N₂ (-21.49 kJ/mol) and CO₂ (-23.82 kJ/mol). ¹ MIL-100 (¹ Sc) and ¹ MIL-100 (⁶ Fe) can also achieve selective adsorption and follows the order ⁴ MIL-100 (⁴ Cr)>¹ MIL-100 (¹ Sc)>¹ MIL-100 (⁶ Fe). In the research of the selective adsorption mechanism of MIL-100 (M) (M=⁴ Cr, ¹ Sc, ⁶ Fe), the independent gradient model (IGM) indicates that these outstanding adsorbents interact with CO₂ and N₂ mainly through the electrostatic attractive interaction, while the van der Walls interaction dominates in the interaction with CH_4. The atomic Projected Density of State (PDOS) further confirms that CH₄ contributes least to the intermolecular interaction than that of CO₂ and N₂ . Through the scrutiny of molecular orbitals, it is found that electrons transfer from the gas molecule to the metal site in the adsorption of CO₂ and N₂ . Not only does the type of the metallic orbitals, but also the delocalization of the involved orbitals determines the selective adsorption performance of MIL-100. Both Cr and Sc share their d z 2 ${{d}_{{z}^{2}}}$ orbitals with the gases, making ¹ MIL-100 (¹ Sc) another potential effective separator for CH₄ . Additionally, the comparison of adsorption energy and PDOS shows that the introduction of ligands such as benzene impedes the electron donation from gas molecules (CO₂ , N₂ ) to the metal site, indicating electron-withdrawing ligands will further favor the adsorption.