000170932 001__ 170932
000170932 005__ 20260430151735.0
000170932 0247_ $$2doi$$a10.1002/chem.71022
000170932 0248_ $$2sideral$$a149030
000170932 037__ $$aART-2026-149030
000170932 041__ $$aeng
000170932 100__ $$aFerrer, Maxime
000170932 245__ $$aThe Future of Foundation Machine Learning Potentials and DFT in Homogeneous Catalysis: Competition or Synergy?
000170932 260__ $$c2026
000170932 5060_ $$aAccess copy available to the general public$$fUnrestricted
000170932 5203_ $$aWhile DFT is the computational method of choice for mechanistic insight in homogeneous catalysis, the recent rise of foundation‐level machine learning interatomic potentials (MLIPs) invites reconsideration: are we approaching competition, or a deeper synergy? These pretrained, fast surrogates are able to map reaction space, sample conformers, and flag likely transition states, potentially displacing routine low‐level DFT. Yet their reliability hinges on calibrated uncertainty, transferability across ligand and oxidation‐state manifolds, and faithful treatment of long‐range polarization, solvation, and open‐shell or multireference character. We argue that the near future will likely be contested: MLIPs will handle everyday exploratory tasks, while DFT and higher‐level methods will anchor electronic effects, validate high‐stakes predictions, and resolve edge cases. If supported by FAIR catalysis datasets, standardized workflows, and robust error quantification, the two approaches will coevolve, enabling scalable, predictive discovery without sacrificing rigor or interpretability.
000170932 536__ $$9info:eu-repo/grantAgreement/ES/MCIU/PID2024-159030NA-I00$$9info:eu-repo/grantAgreement/ES/MICIU/AEI/10.13039/501100011033
000170932 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000170932 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000170932 700__ $$0(orcid)0000-0001-6089-6126$$aMunarriz, Julen$$uUniversidad de Zaragoza
000170932 700__ $$aStuyver, Thijs
000170932 700__ $$aLaplaza, Ruben
000170932 7102_ $$12012$$2755$$aUniversidad de Zaragoza$$bDpto. Química Física$$cÁrea Química Física
000170932 773__ $$pChemistry (Weinh.)$$tChemistry (Weinheim)$$x0947-6539
000170932 8564_ $$s2791191$$uhttps://zaguan.unizar.es/record/170932/files/texto_completo.pdf$$yVersión publicada
000170932 8564_ $$s2407909$$uhttps://zaguan.unizar.es/record/170932/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000170932 909CO $$ooai:zaguan.unizar.es:170932$$particulos$$pdriver
000170932 951__ $$a2026-04-30-13:57:21
000170932 980__ $$aARTICLE