9 citations · 12 across the 6 of their papers we have counts for
6 papers
Perspective: Towards sustainable exploration of chemical spaces with machine learning
Leonardo Medrano Sandonas, David Balcells, Anton Bochkarev +20
Artificial intelligence is transforming molecular and materials science, but its growing computational and data demands raise critical sustainability challenges. In this Perspectiv…
Efficient parameterization of transferable Atomic Cluster Expansion for water
Eslam Ibrahim, Yury Lysogorskiy, Ralf Drautz
We present a highly accurate and transferable parameterization of water using the atomic cluster expansion (ACE). To efficiently sample liquid water, we propose a novel approach th…
From electrons to phase diagrams with classical and machine learning potentials: automated workflows for materials science with pyiron
Sarath Menon, Yury Lysogorskiy, Alexander L. M. Knoll +10
We present a comprehensive and user-friendly framework built upon the pyiron integrated development environment (IDE), enabling researchers to perform the entire Machine Learning P…
Non-collinear Magnetic Atomic Cluster Expansion for Iron
Matteo Rinaldi, Matous Mrovec, Anton Bochkarev +2
The Atomic Cluster Expansion (ACE) provides a formally complete basis for the local atomic environment. ACE is not limited to representing energies as a function of atomic position…
Atomic Cluster Expansion for a General-Purpose Interatomic Potential of Magnesium
Eslam Ibrahim, Yury Lysogorskiy, Matous Mrovec +1
We present a general-purpose parameterization of the atomic cluster expansion (ACE) for magnesium. The ACE shows outstanding transferability over a broad range of atomic environmen…
Origin of the electron disproportionation in the metallic sodium cobaltates
Y. V. Lysogorskiy, S. A. Krivenko, I. R. Mukhamedshin +3
Recently the unusual metallic state with a substantially non-uniform distribution of a charge and mag\-ne\-tic density in CoO planes was found experimentally in the NaCoO$_…