Augmenting Molecular Graphs with Geometries via Machine Learning Interatomic Potentials

arXiv:2507.00407v2 Announce Type: replace-cross Abstract: Accurate molecular property predictions require 3D geometries, which are typically obtained using expensive methods such as density functional theory (DFT). Here, we attempt to obtain molecular geometries by relying sol...

🔗 Read more: https://arxiv.org/abs/2507.00407

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