Advances at the Intersection of Density Functional Theory and Artificial Intelligence
This Collection offers an early glimpse into how artificial intelligence and machine learning can further unlock the potential of density functional theory, a highly successful computational method with broad applications.
Guillermo Currás-Lorenzo, Margarida Pereira, Kiyoshi Tamaki, and Marcos Curty
Phys. Rev. Research 8, L032045 (2026)
Jakob Nicolai Bruhnke and Jan Marcus Dahlström
Phys. Rev. Research 8, L032041 (2026)
Hui Liu, Raul Perea-Causin, Zhao Liu, and Emil J. Bergholtz
Phys. Rev. Research 8, L032039 (2026)
Bikram Pain, Sthitadhi Roy, Jens H. Bardarson, and Ivan M. Khaymovich
Phys. Rev. Research 8, L032037 (2026)
Christian Ventura-Meinersen, Edmondo Valvo, Stefano Bosco, and Maximilian Rimbach-Russ
Phys. Rev. Research 8, L032034 (2026)
Pejman Hadi Sichani, Benjamin A. Storer, and Hussein Aluie
Phys. Rev. Research 8, 033239 (2026)



















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