XACS team in collaboration with Mario Barbatti and groups in Warsaw University and Zhejiang lab has recently published a paper in JCTC about the versatile Python implementation of surface-hopping dynamics.

Want to run DFT calculations in an easy way? Search no more!

Transfer learning (TL) is an often-used technique in machine learning that helps you train better AI models.

MLatom supports a wide range of universal machine learning (ML)-based models including ML potentials and hybrid ML-enhanced quantum mechanical (QM) methods.

In this tutorial, we show how to perform such simulations with the newly released MLatom 3.5.0 on an example reproducing the above PNAS paper.