Microsoft Research blog
Broadening access to Skala creates a faster path to predictive DFT
| 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, and Paola Gori Giorgi
Skala 1.1, the updated deep-learning exchange-correlation functional from Microsoft Research, provides greater accuracy, expanded accessibility across the computational chemistry ecosystem, and a living benchmark to track computational performance.
Breaking bonds, breaking ground: Advancing the accuracy of computational chemistry with deep learning
| Rianne van den Berg, Jan Hermann, Christopher Bishop, and Paola Gori Giorgi
Microsoft researchers achieved a breakthrough in the accuracy of DFT, a method for predicting the properties of molecules and materials, by using deep learning. This work can lead to better batteries, green fertilizers, precision drug discovery, and more.
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