Building machine learning force fields for nanoclusters
Claudio Zeni,
Kevin Rossi,
Aldo Glielmo
et al.
Abstract:We assess Gaussian process (GP) regression as a technique to model interatomic forces in metal nanoclusters by analysing the performance of 2-body, 3-body and many-body kernel functions on a set of 19-atom Ni cluster structures. We find that 2-body GP kernels fail to provide faithful force estimates, despite succeeding in bulk Ni systems. However, both 3-and many-body kernels predict forces within a ∼0.1 eV/ Å average error even for small training datasets, and achieve high accuracy even on out-ofsample, high … Show more
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