JOURNAL ARTICLE

Correlated defects in group 4 metal-organic frameworks

Matthew J. CliffeWei WanXiaodong ZouFrançois‐Xavier CoudertAndrew L. Goodwin

Year: 2014 Journal:   Acta Crystallographica Section A Foundations and Advances Vol: 70 (a1)Pages: C1124-C1124

Abstract

The importance of defects for inorganic functional framework materials is well established, being crucial for properties from relaxor ferroelectricity to superconductivity. The corresponding study of defects in metal-organic frameworks (MOFs) is still however in its infancy. Recent studies have established that ligand-absence defects can be controllably introduced into frameworks and that these defects can drastically improve the material properties, but have so far shown no evidence of correlation between defects. Much of this research has focussed on UiO-66, a zirconium dicarboxylate MOF that was amongst the first very stable MOFs to be discovered.[1] As a result of its stability, it and its derivatives have been investigated for a wide range of properties including photo- and Brønsted acid catalysis, sensing and gas sorption properties. The ability to introduce defects has been demonstrated to substantially enhance both the sorption and catalytic properties of UiO-66.[2][3] We have demonstrated, using a combination of powder X-ray diffraction, total scattering and electron diffraction measurements, that UiO-66 can be engineered, under the appropriate synthetic conditions, to accommodate correlated defect nanodomains. These correlations offer exciting opportunities for manipulating the physical properties, including mass transport, chemical activity and mechanical flexibility.

Keywords:
Materials science Metal-organic framework Zirconium Sorption Catalysis Vacancy defect Diffraction Powder diffraction Metal Chemical engineering Nanotechnology Chemical physics Crystallography Physical chemistry Chemistry Organic chemistry Metallurgy

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Topics

Metal-Organic Frameworks: Synthesis and Applications
Physical Sciences →  Chemistry →  Inorganic Chemistry
X-ray Diffraction in Crystallography
Physical Sciences →  Materials Science →  Materials Chemistry
Machine Learning in Materials Science
Physical Sciences →  Materials Science →  Materials Chemistry

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