Binding of carbon dioxide and acetylene to free carboxylic acid sites in a metal–organic framework

Marsh, Christopher; Han, Xue; Lu, Zhenzhong; da Silva, Ivan; Cheng, Yongqiang; Daemen, Luke L.; Day, Sarah J.; Thompson, Stephen P.; Ramirez-Cuesta, Anibal J.; Yang, Sihai; Schröder, Martin

doi:10.1039/d4sc00101j

Chem. Sci.

2024

DOI: 10.1039/d4sc00101j

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Binding of carbon dioxide and acetylene to free carboxylic acid sites in a metal–organic framework

Christopher Marsh,

Xue Han,

Zhenzhong Lu

et al.

Abstract: The functionalisation of organic linkers in metal-organic frameworks (MOFs) to improve gas uptake is well-documented. Although the positive role of free carboxylic acid sites in MOFs for binding gas molecules...

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Cited by 2 publications

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Trace benzene capture by decoration of structural defects in metal–organic framework materials

Han,

Huang,

et al. 2024

Nat. Mater.

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Capture of trace benzene is an important and challenging task. Metal–organic framework materials are promising sorbents for a variety of gases, but their limited capacity towards benzene at low concentration remains unresolved. Here we report the adsorption of trace benzene by decorating a structural defect in MIL-125-defect with single-atom metal centres to afford MIL-125-X (X = Mn, Fe, Co, Ni, Cu, Zn; MIL-125, Ti8O8(OH)4(BDC)6 where H2BDC is 1,4-benzenedicarboxylic acid). At 298 K, MIL-125-Zn exhibits a benzene uptake of 7.63 mmol g−1 at 1.2 mbar and 5.33 mmol g−1 at 0.12 mbar, and breakthrough experiments confirm the removal of trace benzene (from 5 to <0.5 ppm) from air (up to 111,000 min g−1 of metal–organic framework), even after exposure to moisture. The binding of benzene to the defect and open Zn(II) sites at low pressure has been visualized by diffraction, scattering and spectroscopy. This work highlights the importance of fine-tuning pore chemistry for designing adsorbents for the removal of air pollutants.

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Trace benzene capture by decoration of structural defects in metal–organic framework materials

Han,

Huang,

et al. 2024

Nat. Mater.

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Understanding CO adsorption in MOFs combining atomic simulations and machine learning

Ercakir,

Aksu,

Keskin

2024

Sci Rep

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This study introduces a computational method integrating molecular simulations and machine learning (ML) to assess the CO adsorption capacities of synthesized and hypothetical metal–organic frameworks (MOFs) at various pressures. After extracting structural, chemical, and energy-based features of the synthesized and hypothetical MOFs (hMOFs), we conducted molecular simulations to compute CO adsorption in synthesized MOFs and used these simulation results to train ML models for predicting CO adsorption in hMOFs. Results showed that CO uptakes of synthesized MOFs and hMOFs are between 0.02–2.28 mol/kg and 0.45–3.06 mol/kg, respectively, at 1 bar, 298 K. At low pressures (0.1 and 1 bar), Henry’s constant of CO is the most dominant feature, whereas structural properties such as surface area and porosity are more influential for determining the CO uptakes of MOFs at high pressure (10 bar). Structural and chemical analyses revealed that MOFs with narrow pores (4.4–7.3 Å), aromatic ring-containing linkers and carboxylic acid groups, along with metal nodes such as Co, Zn, Ni achieve high CO uptakes at 1 bar. Our approach evaluated the CO uptakes of ~ 100,000 MOFs, the most extensive and diverse set studied for CO capture thus far, as a robust alternative to computationally demanding molecular simulations and iterative experiments.

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Binding of carbon dioxide and acetylene to free carboxylic acid sites in a metal–organic framework

Abstract: The functionalisation of organic linkers in metal-organic frameworks (MOFs) to improve gas uptake is well-documented. Although the positive role of free carboxylic acid sites in MOFs for binding gas molecules...

Cited by 2 publications

References 38 publications

Trace benzene capture by decoration of structural defects in metal–organic framework materials

Trace benzene capture by decoration of structural defects in metal–organic framework materials

Understanding CO adsorption in MOFs combining atomic simulations and machine learning

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