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Lei C, Erlebach A, Brivio F, Grajciar L, Tošner Z, Heard CJ, Nachtigall P. The need for operando modelling of 27Al NMR in zeolites: the effect of temperature, topology and water. Chem Sci 2023; 14:9101-9113. [PMID: 37655014 PMCID: PMC10466278 DOI: 10.1039/d3sc02492j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 08/02/2023] [Indexed: 09/02/2023] Open
Abstract
Solid state (ss-) 27Al NMR is one of the most valuable tools for the experimental characterization of zeolites, owing to its high sensitivity and the detailed structural information which can be extracted from the spectra. Unfortunately, the interpretation of ss-NMR is complex and the determination of aluminum distributions remains generally unfeasible. As a result, computational modelling of 27Al ss-NMR spectra has grown increasingly popular as a means to support experimental characterization. However, a number of simplifying assumptions are commonly made in NMR modelling, several of which are not fully justified. In this work, we systematically evaluate the effects of various common models on the prediction of 27Al NMR chemical shifts in zeolites CHA and MOR. We demonstrate the necessity of operando modelling; in particular, taking into account the effects of water loading, temperature and the character of the charge-compensating cation. We observe that conclusions drawn from simple, high symmetry model systems such as CHA do not transfer well to more complex zeolites and can lead to qualitatively wrong interpretations of peak positions, Al assignment and even the number of signals. We use machine learning regression to develop a simple yet robust relationship between chemical shift and local structural parameters in Al-zeolites. This work highlights the need for sophisticated models and high-quality sampling in the field of NMR modelling and provides correlations which allow for the accurate prediction of chemical shifts from dynamical simulations.
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Affiliation(s)
- Chen Lei
- Department of Physical and Macromolecular Chemistry, Faculty of Science, Charles University in Prague 128 43 Prague 2 Czech Republic
| | - Andreas Erlebach
- Department of Physical and Macromolecular Chemistry, Faculty of Science, Charles University in Prague 128 43 Prague 2 Czech Republic
| | - Federico Brivio
- Department of Physical and Macromolecular Chemistry, Faculty of Science, Charles University in Prague 128 43 Prague 2 Czech Republic
| | - Lukáš Grajciar
- Department of Physical and Macromolecular Chemistry, Faculty of Science, Charles University in Prague 128 43 Prague 2 Czech Republic
| | - Zdeněk Tošner
- Department of Physical and Macromolecular Chemistry, Faculty of Science, Charles University in Prague 128 43 Prague 2 Czech Republic
| | - Christopher J Heard
- Department of Physical and Macromolecular Chemistry, Faculty of Science, Charles University in Prague 128 43 Prague 2 Czech Republic
| | - Petr Nachtigall
- Department of Physical and Macromolecular Chemistry, Faculty of Science, Charles University in Prague 128 43 Prague 2 Czech Republic
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Cordova M, Moutzouri P, Nilsson Lill SO, Cousen A, Kearns M, Norberg ST, Svensk Ankarberg A, McCabe J, Pinon AC, Schantz S, Emsley L. Atomic-level structure determination of amorphous molecular solids by NMR. Nat Commun 2023; 14:5138. [PMID: 37612269 PMCID: PMC10447443 DOI: 10.1038/s41467-023-40853-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 08/10/2023] [Indexed: 08/25/2023] Open
Abstract
Structure determination of amorphous materials remains challenging, owing to the disorder inherent to these materials. Nuclear magnetic resonance (NMR) powder crystallography is a powerful method to determine the structure of molecular solids, but disorder leads to a high degree of overlap between measured signals, and prevents the unambiguous identification of a single modeled periodic structure as representative of the whole material. Here, we determine the atomic-level ensemble structure of the amorphous form of the drug AZD4625 by combining solid-state NMR experiments with molecular dynamics (MD) simulations and machine-learned chemical shifts. By considering the combined shifts of all 1H and 13C atomic sites in the molecule, we determine the structure of the amorphous form by identifying an ensemble of local molecular environments that are in agreement with experiment. We then extract and analyze preferred conformations and intermolecular interactions in the amorphous sample in terms of the stabilization of the amorphous form of the drug.
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Affiliation(s)
- Manuel Cordova
- Institut des Sciences et Ingénierie Chimiques, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015, Lausanne, Switzerland
- National Centre for Computational Design and Discovery of Novel Materials MARVEL, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Pinelopi Moutzouri
- Institut des Sciences et Ingénierie Chimiques, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015, Lausanne, Switzerland
| | - Sten O Nilsson Lill
- Data Science & Modelling, Pharmaceutical Sciences, R&D, AstraZeneca, Gothenburg, Sweden
| | - Alexander Cousen
- Early Chemical Development, Pharmaceutical Sciences, R&D, AstraZeneca, Macclesfield, UK
| | - Martin Kearns
- Early Product Development and Manufacturing, Pharmaceutical Sciences, R&D, AstraZeneca, Macclesfield, UK
| | - Stefan T Norberg
- Oral Product Development, Pharmaceutical Technology & Development, Operations, AstraZeneca, Gothenburg, Sweden
| | - Anna Svensk Ankarberg
- Oral Product Development, Pharmaceutical Technology & Development, Operations, AstraZeneca, Gothenburg, Sweden
| | - James McCabe
- Early Product Development and Manufacturing, Pharmaceutical Sciences, R&D, AstraZeneca, Macclesfield, UK
| | - Arthur C Pinon
- Swedish NMR Center, Department of Chemistry and Molecular Biology, University of Gothenburg, 41390, Gothenburg, Sweden
| | - Staffan Schantz
- Oral Product Development, Pharmaceutical Technology & Development, Operations, AstraZeneca, Gothenburg, Sweden.
| | - Lyndon Emsley
- Institut des Sciences et Ingénierie Chimiques, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015, Lausanne, Switzerland.
- National Centre for Computational Design and Discovery of Novel Materials MARVEL, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
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Dedication: Commemorative Issue in Honor of Professor Karlheinz Schwarz on the Occasion of His 80th Birthday. COMPUTATION 2022. [DOI: 10.3390/computation10050078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Karlheinz Schwarz was born in January 1941 in Vienna (Austria), and he married Christine Schwarz in 1969 [...]
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