Visualization and quantification of geometric diversity in metal-organic frameworks

With ever-growing numbers of metal–organic framework (MOF) materials being reported, new computational approaches are required for a quantitative understanding of structure–property correlations in MOFs. Here, we show how structural coarse-graining and embedding (“unsupervised learning”) schemes can...

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Bibliografische gegevens
Hoofdauteurs: Nicholas, TC, Alexandrov, EV, Blatov, VA, Shevchenko, AP, Goodwin, AL, Proserpio, DM, Deringer, VL
Formaat: Journal article
Taal:English
Gepubliceerd in: American Chemical Society 2021