Computational Screening of Functionalized UiO-66 Materials for Selective Contaminant Removal from Air

Abstract

Metal−organic frameworks (MOFs) have potential applications for efficient filtration of toxic gases from ambient air. We have used computational methods to examine the efficacy of functionalized UiO-66 with a wide range of functional groups to identify materials suitable for selective adsorption of NH 3 , H 2 S, or CO 2 under humid conditions. To this end, adsorption energies at various favorable positions in the structures are obtained from both clusterbased and periodic models. Our cluster calculations show that DFT calculations using the PBE-D2 functional can reliably predict the ranking of materials obtained at the MP2 level. Performing PBE-D2 calculations using periodic models gives rankings of materials that are significantly different from those of cluster calculations, showing that confinement effects are important in these materials. On the basis of these calculations, recommendations for high performing materials are made using PBE-D2 calculations from periodic models that use the full structure of each MOF.

Integrated Portable Shrimp-Freshness Prediction Platform Based on Ice-Templated Metal–Organic Framework Colorimetric Combinatorics and Deep Convolutional Neural Networks

“…Figure a compares the binding energy for four amine gases in functionalized UiO-66 materials. The PBE-D2 calculation is a useful quantification to consider situations with a low bulk phase concentration of adsorbing species . Since our calculations have focused on individual binding sites for adsorbed molecules and the concentration of absorbed molecules was low in the food package, PBE-D2 was selected.…”

“…We adopted metal–organic frameworks (MOFs) to enhance sensitivity; due to the high-porosity structure with extremely high surface to bulk ratio, they have been widely applied in gas separation and storage, catalysis, biomolecule encapsulation, and battery. , Among different MOFs, we chose UiO-66 (named from the University of Oslo) for its high thermal, water, chemical, and mechanical stability, all of which arise from the high coordination number, strong bonds between inorganic blocks and the linker, and strong Zr–O bonds . Furthermore, functional groups (such as −NO 2 , −NH 2 , −OH, (COOH) 2 , −(CH 3 ) 2 , and −Br) can be introduced into UiO-66 to increase the gas detection sensitivity and selectivity . To address the long-standing challenge in accurate image recognition, we exploited the latest advances in AI and deep learning .…”

The Effects of Functional Groups and Missing Linkers on the Adsorption Capacity of Aromatic Hydrocarbons in UiO-66 Thin Films

“…The role of the functional group is much more difficult to assess experimentally because it is nearly impossible to synthesize ideal materials. Several studies have reported higher adsorption capacity in UiO-66-NH 2 and UiO-66-NO 2 than UiO-66-H [39][40][41][42][43][44][45]. In most cases, the smaller pore size of UiO-66-NO 2 and/or UiO-66-NH 2 compared to UiO-66-H is thought to contribute to stronger guest-host interactions.…”

Influence of Ligand Functionalization of UiO-66-Based Metal-Organic Frameworks When Used as Sorbents in Dispersive Solid-Phase Analytical Microextraction for Different Aqueous Organic Pollutants

“…This result shows that the reduction in effective pore size by functional groups is not critical in the analytical procedure, since the electronic properties of these groups favor the analyte-MOF interaction. The UiO-66 has a moderate pore window size of around 7 Å in diameter and moderate pore size diameter of 11 Å, whereas the UiO-66-X variants reduce the window opening and pore sizes [ 30 ]. This implies that the pore window size is large enough for small molecules, but the bulkier ones may have hindering problems and they most likely interact with the MOF surface.…”