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.
No Explore or Discover sections associated with this archive record.
|40.4 MiB||Python code used to train and use the model and pre-trained model|
|13.0 MiB||Datasets of variable-rate MAS 1H NMR experiments on which the model is applied|
|263.8 MiB||NMR experiments used to determine the assignment of the proton spectra|
|182.2 KiB||Assignment probabilities of the carbon chemical shifts of molnupiravir|
|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|