Defects and Disorder in MOFs

Halbherr, Olesia; Fischer, Roland A.

doi:10.1002/9783527693078.ch26

Cited by 4 publications

(4 citation statements)

References 92 publications

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“…However, in the present work, we observed that the ICT process when NR is adsorbed on the MOF surface is slightly faster than when it is encapsulated within its structure (∼1 ps, Figure S18). The possible presence of defects, typically present on the surface of solid structures, 40 can provide specific interactions that condition the dye photodynamics and facilitate the ICT and ET processes. This reflects different interactions of this molecular probe with the Al−ITQ-HB surface and suggests possible different outcome of the catalytic reactions using this MOF when the reactants are within or on the external surface.…”

Section: Picosecondmentioning

confidence: 99%

How Does the Surface of Al–ITQ-HB 2D-MOF Condition the Intermolecular Interactions of an Adsorbed Organic Molecule?

Caballero-Mancebo

Moreno

Corma

et al. 2018

ACS Appl. Mater. Interfaces

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In this work, we unravel how the two-dimensional Al-ITQ-4-heptylbenzoic acid (HB) metal-organic framework (MOF) changes the interactions of Nile red (NR) adsorbed on its surface. Time-resolved emission experiments indicate the occurrence of energy transfer between adsorbed NR molecules, in abnormally long time constant of 2-2.5 ns, which gets shorter (∼0.25 ns) when the concentration of the surface-adsorbed NR increases. We identify the emission from local excited state of aggregates and charge transfer and energy transfer between adsorbed molecules. Femtosecond emission studies reveal an ultrafast process (∼425 fs) in the NR@Al-ITQ-HB composites, assigned to an intramolecular charge transfer in NR molecules. A comparison of the observed photobehavior with that of NR/SiO and NR/AlO composites suggests that the occurrence of energy transfer in the NR@MOF complexes is a result of specific and nonspecific interactions, reflecting the different surface properties of Al-ITQ-HB that are of relevance to the reported high catalytic activity. Our results provide new knowledge for further researches on other composites with the aim to improve understanding of photocatalytic and photonic processes within MOFs.

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Section: Picosecondmentioning

confidence: 99%

How Does the Surface of Al–ITQ-HB 2D-MOF Condition the Intermolecular Interactions of an Adsorbed Organic Molecule?

Caballero-Mancebo

Moreno

Corma

et al. 2018

ACS Appl. Mater. Interfaces

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“…As displayed in Figure a, methane uptake calculated from the GCMC simulation have large discordances with the reported experimental methane uptakes for the case of UiO-66. This is because UiO-66 usually has diverse defects when it is synthesized, and determining the exact microscopic structure in the sample is almost impossible. , Owing to these reasons, the experimentally measured SA and V p values deviate from those predicted from the perfect crystal structure (Table S4). Similarly, the GCMC simulation failed to predict the experimental methane uptakes because it performs calculations based on perfect crystal structures.…”

Section: Results and Discussionmentioning

confidence: 99%

Machine-Learning-Based Prediction of Methane Adsorption Isotherms at Varied Temperatures for Experimental Adsorbents

Kim

Bae

2020

J. Phys. Chem. C

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Metal–organic frameworks (MOFs) are crystalline materials and one of the optimal materials for large-scale grand canonical Monte Carlo (GCMC) simulations. Recently, there have been trials for applying machine learning (ML) to the results of large-scale GCMC simulations to predict gas adsorption on MOFs. However, the functions of the developed algorithms are not different from those of GCMC simulations, in that they provide a prediction of adsorption properties based on the coordination structures. In this study, we propose a novel Monte Carlo-Machine Learning (MC-ML) strategy, which combines ML with GCMC to provide the function that is distinct from that of GCMC. To verify the concept of the strategy, we designed an algorithm to predict methane isotherms at a range of temperatures from a methane isotherm at a temperature of 298 K. GCMC simulations functioned as a data-producing tool for ML, which yielded adsorption properties of 4951 structures in the CoRE-MOF database. The ML was applied to the GCMC results using experimentally measurable properties as features. Finally, the algorithm developed from ML was evaluated using experimental methane adsorption data for defective MOFs, MOFs with open metal sites, and non-MOF materials, which revealed the merits of the MC-ML strategy in comparison with typical GCMC.

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“…This speeding up of the ICT, along with the occurrence of ET in the NR@Al-ITQ-HB composites suggests the presence of defects, typically found on the surface of solid structures, that can provide specific interactions that condition the dye photodynamics and facilitate both processes. 124 This in turn reflects how the singular local environment created due to the different probe locations when interacting with Al-ITQ-HB (either adsorbed on its surface or entrapped within the interior) might provide different outcomes for the catalytic reactions using this MOF.…”

Section: Nr Adsorbed On Al-itq-hb 2d-mofmentioning

confidence: 99%

Synthesis, characterization & catalysis of ITQ 2D metal–organic frameworks and spectroscopic & photodynamic properties of their composites with organic dyes

Gutiérrez,

Díaz,

Cohen

et al. 2023

J. Mater. Chem. C

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Defects and Disorder in MOFs

Cited by 4 publications

References 92 publications

How Does the Surface of Al–ITQ-HB 2D-MOF Condition the Intermolecular Interactions of an Adsorbed Organic Molecule?

How Does the Surface of Al–ITQ-HB 2D-MOF Condition the Intermolecular Interactions of an Adsorbed Organic Molecule?

Machine-Learning-Based Prediction of Methane Adsorption Isotherms at Varied Temperatures for Experimental Adsorbents

Synthesis, characterization & catalysis of ITQ 2D metal–organic frameworks and spectroscopic & photodynamic properties of their composites with organic dyes

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