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Journal: Chemical Science
Article Title: Accessible hybrid DFT-quality NMR crystallography via gas-phase machine learning interatomic potentials
doi: 10.1039/d6sc04941a
Figure Lengend Snippet: Workflow used for the analysis of the ML tools discussed in this article. (a) Optimization of the 65 X-ray crystal structures with either DFT or UMA, or no optimization, followed by calculations of magnetic shielding tensors either via RPBE or ShiftML3. (b) For the set of Ramos et al. , optimization of the reported PBE-D3 structures with either UMA (tasks omol or omc) or MACE-Polar-1, followed by calculations of magnetic shieldings with either PBE or ShiftML3.
Article Snippet:
Techniques:
Journal: Chemical Science
Article Title: Accessible hybrid DFT-quality NMR crystallography via gas-phase machine learning interatomic potentials
doi: 10.1039/d6sc04941a
Figure Lengend Snippet: Comparison between the 13 C isotropic magnetic shieldings obtained via (a) X-ray/RPBE vs. RPBE-D2/RPBE, (b) UMA/RPBE vs. RPBE-D2/RPBE, (c) X-ray/ShiftML3 vs. RPBE-D2/RPBE, (d) UMA/ShiftML3 vs. RPBE-D2/RPBE. UMA was used with the task omol and the uma-s-1p1 model.
Article Snippet:
Techniques: Comparison