Impact of amino and methyl groups on the loading capacity of UiO-66 for 8-hydroxyquinoline: an in-depth experimental and computational analysis

This research systematically investigates a library of UiO-66(Zr) dicarboxylate metal-organic frameworks (MOFs), functionalized with polar and nonpolar substituents (-H, -CH<sub>3</sub>, -NH<sub>2</sub>), to evaluate their potential as carriers for inhibitor encapsulation, using 8-hydroxyquinoline (8-HQ) as a model compound. The encapsulation process was conducted under vacuum, and 8-HQ uptake was quantified using UV-visible absorption spectroscopy, allowing for precise control over host-guest interactions. Quantitative assessment of 8-HQ loading within each functionalized UiO-66 variant revealed significant variations in uptake efficiency, ranging from 14.66% to 19.45% across the modified frameworks. Furthermore, a density functional theory-based quantitative structure-activity relationship (QSAR) approach was employed to identify key chemical and structural attributes of UiO-66 that significantly influence inhibitor uptake. Multivariate analysis identified two critical physicochemical parameters governing encapsulation efficiency: (1) the dipole moment of the functionalized linkers, which dictates framework-polarity-mediated adsorption, and (2) the hydrogen-bond-donating capacity, which modulates specific interactions with 8-HQ's phenolic oxygen. These descriptors exhibited strong linear correlations with experimental loading data, demonstrating that strategic enhancement of linker polarity and H-bonding capability can amplify inhibitor uptake by 10-20% compared to pristine UiO-66. The QSAR model deciphers MOF performance trends and predicts optimal functional groups <i>via</i> descriptor interpolation, streamlining MOF carrier design for corrosion and drug applications through targeted linker engineering.

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Publication Details

Journal
RSC Advances
Published
2025-01-01
DOI
https://doi.org/10.1039/d5ra02802g
Citations
3
Primary Topic
Chemical Synthesis and Reactions
Type
article
Field-Weighted Citation Impact
2.81

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article

Impact of amino and methyl groups on the loading capacity of UiO-66 for 8-hydroxyquinoline: an in-depth experimental and computational analysis

Jinlong Ge, Hao Yan, Bokai Liao, Jake D. Cao
3 citations
RSC Advances
Chemical Synthesis and Reactions
2.81
article

Impact of amino and methyl groups on the loading capacity of UiO-66 for 8-hydroxyquinoline: an in-depth experimental and computational analysis

Jinlong Ge, Hao Yan, Bokai Liao, Jake D. Cao
article en
3 citations

Abstract

This research systematically investigates a library of UiO-66(Zr) dicarboxylate metal-organic frameworks (MOFs), functionalized with polar and nonpolar substituents (-H, -CH<sub>3</sub>, -NH<sub>2</sub>), to evaluate their potential as carriers for inhibitor encapsulation, using 8-hydroxyquinoline (8-HQ) as a model compound. The encapsulation process was conducted under vacuum, and 8-HQ uptake was quantified using UV-visible absorption spectroscopy, allowing for precise control over host-guest interactions. Quantitative assessment of 8-HQ loading within each functionalized UiO-66 variant revealed significant variations in uptake efficiency, ranging from 14.66% to 19.45% across the modified frameworks. Furthermore, a density functional theory-based quantitative structure-activity relationship (QSAR) approach was employed to identify key chemical and structural attributes of UiO-66 that significantly influence inhibitor uptake. Multivariate analysis identified two critical physicochemical parameters governing encapsulation efficiency: (1) the dipole moment of the functionalized linkers, which dictates framework-polarity-mediated adsorption, and (2) the hydrogen-bond-donating capacity, which modulates specific interactions with 8-HQ's phenolic oxygen. These descriptors exhibited strong linear correlations with experimental loading data, demonstrating that strategic enhancement of linker polarity and H-bonding capability can amplify inhibitor uptake by 10-20% compared to pristine UiO-66. The QSAR model deciphers MOF performance trends and predicts optimal functional groups <i>via</i> descriptor interpolation, streamlining MOF carrier design for corrosion and drug applications through targeted linker engineering.

RSC AdvancesVol. 15(26)
Bengbu Medical College (CN), Guangzhou University (CN), Bengbu University
National Natural Science Foundation of China, Bengbu University, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 10%
Chemical Synthesis and Reactions
2.81
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