Chemical Shifts in Molecular Solids by Machine Learning

Understand

The calculation of chemical shifts in solids has enabled methods to determine crystal structures in powders.

• The dependence of chemical shifts on local atomic environments sets them among the most powerful tools for structure elucidation of powdered solids or amorphous materials.
• Unfortunately, this dependency comes with the cost of high accuracy first-principle calculations to qualitatively predict chemical shifts in solids.
• Machine learning methods have recently emerged as a way to overcome the need for explicit high accuracy first-principle calculations.