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Join online broadcast: Active learning for building your data and machine learning potentials

2024-04-22

In the broadcast, we will demonstrate how MLatom@XACS can be used for accelerating expensive quantum chemical simulations via efficient building of robust machine learning potentials.

JPCL | Tell Machine Learning Potentials What They Are Needed For: Simulation-Oriented Training

2024-04-17

See our paper in JPCL for more details as well as the tutorials on how to use MLatom for such simulations.

April updates: Backup, feedback, surface-hopping dynamics, constrained geometry optimization, and more

2024-04-12

We have made several updates of the XACS platform and software.

Faster & more accurate than DFT: AIQM1 in MLatom@XACS

2024-04-10

AIQM1 (artificial intelligence–quantum mechanical method 1)

Inorg. Chem. : Application of chemical bond analysis in lithium-sulfur batteries design

2024-04-07

New example on the application of XACS showcases the study of Wang Changwei from Shaanxi Normal University and Mo Yirong from the University of North Carolina at Greensboro.

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