ShiftML | Matthias Kellner

I maintain the ShiftML project. ShiftML is a family of universal chemical shielding predictors for organic solids. Accurate chemical shielding predictions are central to NMR crystallography, a combined computational-experimental structure determination protocol that aims to determine the 3D structure of matter from NMR measurements.

I currently maintain the ShiftML Python package, which makes ShiftML models available to the wider chemistry community. It hosts ShiftML3 (Kellner et al., 2025) and ShiftML4 (Kellner et al., 2026), two chemical shielding models for molecular organic solids. ShiftML4 is also available online at shiftml.org, jointly developed with the LRM laboratory at EPFL.

Building on these models, we have shown how quantum nuclear effects can be included in NMR crystallography at scale (Kellner et al., 2026).

References

2026

arXiv

Machine-Learned NMR Shieldings in Molecular Solids with Built-In Hybrid-Functional Molecular Corrections

Matthias Kellner, Ruben Rodriguez-Madrid, Jacob B Holmes, and 4 more authors

arXiv preprint, 2026

arXiv Bib Code Website

@article{kellner2026machine,
  title = {Machine-Learned NMR Shieldings in Molecular Solids with Built-In Hybrid-Functional Molecular Corrections},
  author = {Kellner, Matthias and Rodriguez-Madrid, Ruben and Holmes, Jacob B and Unzueta, Pablo A and Beran, Gregory JO and Emsley, Lyndon and Ceriotti, Michele},
  journal = {arXiv preprint},
  year = {2026},
}

arXiv

Quantum-corrected NMR crystallography at scale

Matthias Kellner, Ruben Rodriguez-Madrid, Jacob B Holmes, and 3 more authors

arXiv preprint, 2026

arXiv Bib

@article{kellner2026quantum,
  title = {Quantum-corrected NMR crystallography at scale},
  author = {Kellner, Matthias and Rodriguez-Madrid, Ruben and Holmes, Jacob B and Principe, Victor Paul and Emsley, Lyndon and Ceriotti, Michele},
  journal = {arXiv preprint},
  year = {2026},
}

2025

JPCL

A deep learning model for chemical shieldings in molecular organic solids including anisotropy

Matthias Kellner, Jacob B Holmes, Ruben Rodriguez-Madrid, and 4 more authors

The Journal of Physical Chemistry Letters, 2025

DOI Bib Code

@article{kellner2025deep,
  title = {A deep learning model for chemical shieldings in molecular organic solids including anisotropy},
  author = {Kellner, Matthias and Holmes, Jacob B and Rodriguez-Madrid, Ruben and Viscosi, Florian and Zhang, Yuxuan and Emsley, Lyndon and Ceriotti, Michele},
  journal = {The Journal of Physical Chemistry Letters},
  volume = {16},
  number = {34},
  pages = {8714--8722},
  year = {2025},
  publisher = {American Chemical Society},
  doi = {10.1021/acs.jpclett.5c01819},
}