The atomic cluster expansion is a general polynomial expansion of the atomic energy in
multi-atom basis functions. Here we implement the atomic cluster expansion in the …

The atomic cluster expansion (ACE) provides a general, local, and complete representation
of atomic energies. Here we present an efficient framework for parametrization of ACE …

The atomic cluster expansion (ACE) was proposed recently as a new class of data-driven
interatomic potentials with a formally complete basis set. Since the development of any …

The atomic cluster expansion is developed as a complete descriptor of the local atomic
environment, including multicomponent materials, and its relation to a number of other …

Atomistic simulations such as molecular dynamics and Monte Carlo are widely used for
understanding the material's behavior at a more fundamental level, eg, at the atomic level …

ONETEP is an ab initio electronic structure package for total energy calculations within
density-functional theory. It combines 'linear scaling', in that the total computational effort …

Gaussian Approximation Potentials (GAPs) are a class of Machine Learned Interatomic
Potentials routinely used to model materials and molecular systems on the atomic scale. The …

The central approximation made in classical molecular dynamics simulation of materials is
the interatomic potential used to calculate the forces on the atoms. Great effort and ingenuity …

Machine-learning potentials (MLPs) for atomistic simulations are a promising alternative to
conventional classical potentials. Current approaches rely on descriptors of the local atomic …

We introduce machine-learned potentials for Ag-Pd to describe the energy of alloy
configurations over a wide range of compositions. We compare two different approaches …