Equivariant graph neural networks accurately predict full magnetic shielding and electric field gradient tensors for SiO2 structures, enabling fast simulation of static solid-state NMR spectra.
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Graph-neural-network predictions of solid-state NMR parameters from spherical tensor decomposition
Equivariant graph neural networks accurately predict full magnetic shielding and electric field gradient tensors for SiO2 structures, enabling fast simulation of static solid-state NMR spectra.