Optimization of the wetting-drying characteristics of hydrophobic metal organic frameworks via crystallite size: The role of hydrogen bonding between intruded and bulk liquid.
J Colloid Interface Sci
; 645: 775-783, 2023 Sep.
Article
em En
| MEDLINE
| ID: mdl-37172487
ABSTRACT
HYPOTHESIS:
The behavior of Heterogeneous Lyophobic Systems (HLSs) comprised of a lyophobic porous material and a corresponding non-wetting liquid is affected by a variety of different structural parameters of the porous material. Dependence on exogenic properties such as crystallite size is desirable for system tuning as they are much more facilely modified. We explore the dependence of intrusion pressure and intruded volume on crystallite size, testing the hypothesis that the connection between internal cavities and bulk water facilitates intrusion via hydrogen bonding, a phenomenon that is magnified in smaller crystallites with a larger surface/volume ratio. EXPERIMENTS Water intrusion/extrusion pressures and intrusion volume were experimentally measured for ZIF-8 samples of various crystallite sizes and compared to previously reported values. Alongside the practical research, molecular dynamics simulations and stochastic modeling were performed to illustrate the effect of crystallite size on the properties of the HLSs and uncover the important role of hydrogen bonding within this phenomenon.FINDINGS:
A reduction in crystallite size led to a significant decrease of intrusion and extrusion pressures below 100 nm. Simulations indicate that this behavior is due to a greater number of cages being in proximity to bulk water for smaller crystallites, allowing cross-cage hydrogen bonds to stabilize the intruded state and lower the threshold pressure of intrusion and extrusion. This is accompanied by a reduction in the overall intruded volume. Simulations demonstrate that this phenomenon is linked to ZIF-8 surface half-cages exposed to water being occupied by water due to non-trivial termination of the crystallites, even at atmospheric pressure.
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Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article