Multivariate analysis of disorder in metal–organic frameworks

Journal article

The rational design of disordered frameworks is an appealing route to target functional materials. However, intentional realisation of such materials relies on our ability to readily characterise and quantify structural disorder. Here, we use multivariate analysis of pair distribution functions to fingerprint and quantify the disorder within a series of compositionally identical metal–organic frameworks, possessing different crystalline, disordered, and amorphous structures. We find this approach can provide powerful insight into the kinetics and mechanism of structural collapse that links these materials. Our methodology is also extended to a very different system, namely the melting of a zeolitic imidazolate framework, to demonstrate the potential generality of this approach across many areas of disordered structural chemistry.JM11106 EPSRC iCASE Fundin

Authors: Sapnik, AF; Bechis, I; Bumstead, AM; Johnson, T; Chater, PA

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Nature Research
• Journal: Nature Communications
• Volume: 13
• Issue: 1
• Pages: 2173-2173
• Article number: 2173
• Publication date: 2022-04-21
• DOI: 10.1038/s41467-022-29849-6
• EISSN: 2041-1723
• ISSN: 2041-1723
• Language: English
• Keywords: Imidazolate; Amorphous solid; Chemistry; Generality; Computer science; Materials science; Metal-organic framework; Nanotechnology; Biology; Physical chemistry; Machine learning; Zeolitic imidazolate framework; Biological system; Multivariate statistics; Crystallography