Silicon-29 NMR Experimental Datasets used in Statistical Learning of NMR tensors from 2D Isotropic/Anisotropic Correlation Nuclear Magnetic Resonance Spectra

Processed silicon-29 Magic-Angle Flipping and Magic-Angle Turning Nuclear Magnetic Resonance used as input to the smooth-LASSO linear inversion algorithm described in submitted manuscript "Statistical Learning of NMR tensors from 2D Isotropic/Anisotropic Correlation Nuclear Magnetic Resonance Spectra", by Srivastava and Grandinetti.

Details of the csdf dataset format are given in PLOS ONE, 15(1): e0225953 (2020), "Core Scientific Dataset Model: A lightweight and portable model and file format for multi-dimensional scientific data," D. Srivastava, T. Vosegaard, D. Massiot, and P.J. Grandinetti.  The data within csdf files can be accessed with the Python package csdmpy, or other CSDM-compliant software.