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Identifying aspirin polymorphs from combined DFT‐based crystal structure prediction and solid‐state NMR
Author(s) -
Mathew Renny,
Uchman Karolina A.,
Gkoura Lydia,
Pickard Chris J.,
Baias Maria
Publication year - 2020
Publication title -
magnetic resonance in chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.483
H-Index - 72
eISSN - 1097-458X
pISSN - 0749-1581
DOI - 10.1002/mrc.4987
Subject(s) - chemistry , crystal structure prediction , density functional theory , crystal structure , chemical shift , solid state nuclear magnetic resonance , ab initio , crystallography , computational chemistry , two dimensional nuclear magnetic resonance spectroscopy , nuclear magnetic resonance , stereochemistry , organic chemistry , physics
A combined experimental and computational approach was used to distinguish between different polymorphs of the pharmaceutical drug aspirin. This method involves the use of ab initio random structure searching (AIRSS), a density functional theory (DFT)‐based crystal structure prediction method for the high‐accuracy prediction of polymorphic structures, with DFT calculations of nuclear magnetic resonance (NMR) parameters and solid‐state NMR experiments at natural abundance. AIRSS was used to predict the crystal structures of form‐I and form‐II of aspirin. The root‐mean‐square deviation between experimental and calculated 1 H chemical shifts was used to identify form‐I as the polymorph present in the experimental sample, the selection being successful despite the large similarities between the molecular environments in the crystals of the two polymorphs.