Microsoft Research· Sebastian Ehlert, Stefano Battaglia, Thijs Vogels, Jan Hermann, Jens Wehner, Giulia Luise, Klaas Giesbertz, Chin-Wei Huang, Aaron Kaplan, Kate Milton, Stephanie Marisa Lanius, Derk Kooi, P. Bernát Szabó, Gregor Simm, Rianne van den Berg, Paola Gori Giorgi·· 2026-08-21
Broadening access to Skala creates a faster path to predictive DFT
Broadening access to Skala creates a faster path to predictive DFT
AI summary
Microsoft Research released deep-learning DFT functional Skala 1.1, trained on 2.5 times more data than the previous public version. It ranks first in 32 of GMTKN55's 55 categories with 2.8 kcal/mol weighted average error. Available in CP2K and being integrated into Psi4, FHI-aims, ORCA and VASP, it is tracked by a new living performance benchmark.
Selection record
Threshold 60Official, first-handFirst 42Second 38
Not admittedSum of both 80 < twice the threshold 120
- Source tier
- Official, first-hand; this tier's threshold is 60
- Pre-filter
- passed：深度学习DFT模型Skala发布，属AI科学应用
A model scores each item twice, independently, against one written standard, out of 100. An item is admitted only when the two scores add up to twice the threshold. The threshold is set per source tier.
Source: Microsoft Research · microsoft.com