Understanding how molecules interact with metal surfaces is fundamental to catalysis and surface chemistry. However, traditional computational methods face a trade-off: achieving high accuracy often ...

Harvard researchers bring the accuracy, sample efficiency, and robustness of deep equivariant neural networks to the simulate 44 million atoms. This is achieved through a combination of innovative ...

A study in Nature Communications by Michele Ceriotti’s group at EPFL has introduced a new dataset and model that greatly improve the efficiency of machine-learning interatomic potentials (MLIPs) and ...

Scientists use quantum many-body data and machine learning to boost density functional theory accuracy for chemistry and materials science. (Nanowerk News) A new trick for modeling molecules with ...

There is more than one way to describe a water molecule, especially when communicating with a machine learning (ML) model, says chemist Robert DiStasio. You can feed the algorithm the molecule's ...

There is more than one way to describe a water molecule, especially when communicating with a machine learning (ML) model, says chemist Robert ...