From the 1 of 4 linked papers with an AI index.
4 papers
Machine-Learned NMR Shieldings in Molecular Solids with Built-In Hybrid-Functional Molecular Corrections
Matthias Kellner, Ruben Rodriguez-Madrid, Jacob B. Holmes +4
Fast and accurate chemical shielding estimators are essential for shielding-driven Nuclear Magnetic Resonance (NMR) crystallography. Machine-learning models for shielding predictio…
Robust nuclear hyperpolarization of small molecules through intermolecular transfer of parahydrogen-derived polarization
Bogdan A. Rodin, Anna Parker, Laurynas Dagys +12
The paper presents PHIPNOE, a method that uses parahydrogen‑derived polarization to hyperpolarize a source molecule, which then transfers the enhanced spin polarization to many oth…
Quantum-corrected NMR crystallography at scale
Matthias Kellner, Ruben Rodriguez-Madrid, Jacob B. Holmes +4
Structure determination by chemical-shift-driven NMR crystallography relies on comparing chemical shieldings measured in solid-state NMR experiments with simulations. However, comp…
A deep learning model for chemical shieldings in molecular organic solids including anisotropy
Matthias Kellner, Jacob B. Holmes, Ruben Rodriguez-Madrid +4
Nuclear Magnetic Resonance (NMR) chemical shifts are powerful probes of local atomic and electronic structure that can be used to resolve the structures of powdered or amorphous mo…