A foundation model for atomistic materials chemistry
Bridge University · Federal Institute For Materials Research and Testing · +38 more institutions
Abstract
Atomistic simulations of matter, especially those that leverage first-principles (ab initio) electronic structure theory, provide a microscopic view of the world, underpinning much of our understanding of chemistry and materials science. Over the last decade or so, machine-learned force fields have transformed atomistic modeling by enabling simulations of ab initio quality over unprecedented time and length scales. However, early machine-learning (ML) force fields have largely been limited by (i) the substantial computational and human effort required to develop and validate potentials for each particular system of interest and (ii) a general lack of transferability from one chemical system to the next. Here,…
Citation impact
- FWCI
- 61.15
- Percentile
- 100%
- References
- 285
Authors
88- IBIlyes BatatiaCorresponding
Bridge University
- PBPhilipp Benner
Federal Institute For Materials Research and Testing
- YCYuan Chiang
Lawrence Berkeley National Laboratory, University of California, Berkeley
- AMA. M. Elena
Science and Technology Facilities Council, Science and Engineering Research Council
- DPDávid Péter Kovács
Bridge University
Topics & keywords
- Leverage (statistics)
- Foundation (evidence)
- Ab initio
- Transferability
- Molecular dynamics
- Underpinning
- Force field (fiction)
- Set (abstract data type)
Funding
- NSNational Science FoundationAward: DGE-2146752
- AVAlexander von Humboldt-Stiftung
- URUK Research and InnovationAwards: EP/K01711X/1, EP/T001038/1, EP/S024220/1, EP/T517847/1, EP/L015722/1, EP/S022953/1, EP/X034712/1, EP/W026775/1, EP/K017144/1, EP/V028537/1, EP/L016087/1, EP/X015742/1, EP/V062654/1, EP/V000055/1, EP/N010345/1, EP/X016188/1
- GFGraphene Flagship
- ECEuropean CommissionAward: 951786
- DFDeutsche ForschungsgemeinschaftAwards: 497249646, EXC 2089/1, 390740016
- SNSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungAwards: 182892, 200020_214879
- DGDanmarks Grundforskningsfond
- SDStudienstiftung des Deutschen Volkes
- VVetenskapsrådetAward: 2021-06757
- INIsaac Newton Trust
- SJShanghai Jiao Tong University
- CÀCommissariat à l'Énergie Atomique et aux Énergies Alternatives
- GÉGrand Équipement National De Calcul IntensifAward: A0120913455
- CSCentro Svizzero di Calcolo ScientificoAward: s1209
- GCGauss Centre for Supercomputing
- OOOffice of ScienceAwards: BES-ERCAP0022838, BES-ERCAP0023528, DE-AC02-05-CH11231
- HEHORIZON EUROPE Framework ProgrammeAward: 957189
- NSNatural Sciences and Engineering Research Council of CanadaAward: GR019381
- SAScience and Technology Facilities CouncilAwards: ST/R002452/1, ST/R00689X/1, ST/P002307/1
- CCChurchill College, University of Cambridge
- JFJohn Fell Fund, University of Oxford
- SCStuttgart Center for Simulation Science, Universität Stuttgart
- UNU.S. Naval Research Laboratory
- AFAir Force Research LaboratoryAward: FA8655-21-1-7010
- HEHORIZON EUROPE Marie Sklodowska-Curie ActionsAward: 945357
- HEHORIZON EUROPE European Research CouncilAwards: 101161771, 101001890, 101071937