Résumé
Hybrid workflow merging force fields and machine-learned potentials enables scalable, near-quantum accuracy for MOF screening. Ethylene capture for food packaging, as a test case, shows framework flexibility is critical for reliable rankings.
- Titre
- Towards accurate and scalable high-throughput MOF adsorption screening: merging classical force fields and universal machine learned interatomic potentials
- Créateurs - sans rôle
- Satyanarayana Bonakala - Université de Montpellier, ICGM - Institut Charles Gerhardt MontpellierMohammad Wahiduzzaman - Université de Montpellier, ICGM - Institut Charles Gerhardt MontpellierTaku Watanabe - Development Bank of JapanKarim Hamzaoui - Development Bank of JapanGuillaume Maurin - Université de Montpellier, ICGM - Institut Charles Gerhardt Montpellier
- Détails de publication
- Chemical Science, Vol.17(24), p.12084-12093
- Identifiants
- 99256614409311
- Unité académique
- ICGM - Institut Charles Gerhardt Montpellier
- Langue
- Anglais
- Type de ressource
- Article de revue scientifique
- Champs locaux
- hal-05672998