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·· 2026-08-21AI score50
Broadening access to Skala creates a faster path to predictive DFT
Broadening access to Skala creates a faster path to predictive DFT
AI introduction
Microsoft Research released Skala 1.1, trained on 2.5 times the data of the previous version, ranking first in 32 of the 55 categories of the GMTKN55 benchmark with a weighted average error of 2.8 kcal/mol at compute cost comparable to a meta-GGA functional. Skala is now available in CP2K and being integrated into Psi4, FHI-aims, ORCA, and VASP, alongside a dynamic benchmark tracking each version's computational performance.
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Source: Microsoft Research · microsoft.com