Publication date: Dec 22, 2022
The resolution of proton solid-state NMR spectra is usually limited by broadening arising from dipolar interactions between spins. Magic-angle spinning alleviates this broadening by inducing coherent averaging. However, even the highest spinning rates experimentally accessible today are not able to completely remove dipolar interactions. Here, we introduce a deep learning approach to determine pure isotropic proton spectra from a two-dimensional set of magic-angle spinning spectra acquired at different spinning rates. Applying the model to 8 organic solids yields high-resolution 1H solid-state NMR spectra with isotropic linewidths in the 50-400 Hz range.
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File name | Size | Description |
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code.zip
MD5md5:1063ccb35b855825414891e088d2527c
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40.4 MiB | Python code used to train and use the model and pre-trained model |
MAS_datasets.zip
MD5md5:1cf1c48691243aa4f1570313a26b8fab
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13.0 MiB | Datasets of variable-rate MAS 1H NMR experiments on which the model is applied |
assignment_experiments.zip
MD5md5:ec2e06aef2effca4210ca36cab4c4889
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263.8 MiB | NMR experiments used to determine the assignment of the proton spectra |
probabilistic_assignment.zip
MD5md5:c6813b6bd845a76bd956f15b6555a12a
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182.2 KiB | Assignment probabilities of the carbon chemical shifts of molnupiravir |
Quantum_espresso.zip
MD5md5:c69af26fad5f5f72293b68479583d471
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47.7 KiB | Quantum ESPRESSO DFT chemical shift computations to assign chemical shifts of MDMA hydrochloride |
2022.180 (version v1) [This version] | Dec 22, 2022 | DOI10.24435/materialscloud:a7-59 |