Pure Isotropic Proton NMR Spectra in Solids using Deep Learning

Abstract

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 highresolution 1 H solid-state NMR spectra with isotropic linewidths in the 50-400 Hz range.

ARTIST: an automatic residue type assignment program for multidimensional NMR spectra

“…25 Although the designated input format targets carbon detected 3D spectra, it can also be used to assign other spectra with different polarization transfer pathway and detection methods. [26][27][28][29] The program is coded in Python, 30 which allows easy revisions and improvements by other users.…”