The Future of Foundation Machine Learning Potentials and DFT in Homogeneous Catalysis: Competition or Synergy?

Ferrer M, Munarriz J, Stuyver T, Laplaza R

DOI: 10.1002/chem.71022
Published: 2026 Jul 2
Container: Chemistry (Weinheim an der Bergstrasse, Germany)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1002/chem.71022,
  title = {The Future of Foundation Machine Learning Potentials and DFT in Homogeneous Catalysis: Competition or Synergy?},
  author = {Ferrer M and Munarriz J and Stuyver T and Laplaza R},
  year = {2026},
  journal = {Chemistry (Weinheim an der Bergstrasse, Germany)},
  doi = {10.1002/chem.71022},
  url = {https://doi.org/10.1002/chem.71022}
}

RIS

TY  - JOUR
TI  - The Future of Foundation Machine Learning Potentials and DFT in Homogeneous Catalysis: Competition or Synergy?
AU  - Ferrer M
AU  - Munarriz J
AU  - Stuyver T
AU  - Laplaza R
PY  - 2026
JO  - Chemistry (Weinheim an der Bergstrasse, Germany)
DO  - 10.1002/chem.71022
UR  - https://doi.org/10.1002/chem.71022
ER  -

APA

M, F., J, M., T, S., & R, L. (2026). The Future of Foundation Machine Learning Potentials and DFT in Homogeneous Catalysis: Competition or Synergy?. Chemistry (Weinheim an der Bergstrasse, Germany). https://doi.org/10.1002/chem.71022

Source records

pubmed · retrieved 2026-09-25T02:31:54.922Z