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 spectra used as input to the smooth-LASSO linear inversion algorithm along with their corresponding NMR tensor parameter distributions as described in the paper "Statistical Learning of NMR tensors from 2D Isotropic/Anisotropic Correlation Nuclear Magnetic Resonance Spectra", by Srivastava and Grandinetti.  

Files with names containing "MAF" or "MAT" are the corresponding experimental Si-29 NMR MAF or MAT dataset on the composition given in the filename.  Files with names containing "inverse" are the corresponding NMR tensor parameter distributions obtained from the inversion of the corresponding experimental MAF and MAT dataset with the composition given in the filename.  

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.