Understanding and predicting materials evolution and/or materials chemistry at the
atomic-scale level has become a major challenge towards a more efficient and more
sustainable technology. To address this challenge it is fundamental to be able to explore
the energy landscape and to identify with diffusion/reaction pathways, including the initial,
final, and transition state. One of the most effective techniques for exploring this highdimensional energy surface is the Activation-Relaxation-Technique algorithm [1]
developed many years ago by N. Mousseau. In this presentation, the recent ARTn
refactoring as a plugin will be presented [2], with some typical examples that will include
show cases of its coupling with different Energy/Forces (E/F) Engines (Quantum
ESPRESSO, LAMMPS, and Python).
As development perspective, pARTn will be contextualised in the broader development
perspective of a Kinetic Monte-Carlo of lattice and on-the-fly to address materials
evolution at the long-time-scale. In this respect, other key ingredients, will be described,
in particular, IRA (Iterative Rotations and Translations)[3] our recently developed shape
matching algorithm.
[1]: G.T. Barkema, and N. Mousseau, Event-Based Relaxation of Continuous Disordered
Systems, Phys. Rev. Lett. 77, 21, 4358-4361
[2]: M. Poberznik, et. al., pARTn: A plugin implementation of the Activation Relaxation
Technique nouveau that takes over the FIRE minimisation algorithm, Comput. Phys. Comm.,
295 (2024) 108961
[3]: M. Gunde et. Al., IRA: A Shape Matching Approach for Recognition and Comparisonof
Generic Atomic Patterns, J. Chem. Inf. Model. (2021) 61, 5446−5457
Paolo Umari
