Workshop “Machine Learning Interatomic Potentials and Accessible Databases”

9-11 September 2024

Published on

9 – 11 September 2024


Registration deadline: 14 August 2024

Machine Learning Interatomic Potentials (MLIPs) have positioned themselves as a key tool for atomistic modeling in materials science. MLIPs cover an expansive range of systems, taking advantage of the highly accurate electronic structure calculations based on quantum mechanics, but at a significantly lower computational cost. They allow to scale up atomistic simulations to larger systems, longer timescales, and more complex phenomena; they therefore significantly contribute to the acceleration of the discovery of novel structural and functional materials, and in the advancements in our understanding of matter. Ground-breaking bodies of work have been published since the seminal work of Behler and Parrinello in 2007 [1], transforming the field into a rapidly evolving research discipline [2-16]. However, alongside these advancements, a crucial challenge emerges: the need for standardized protocols for MLIP generation and storage, as well as comprehensive, accessible databases for ab initio datasets.

This workshop is organized as part of targeted project DIAMOND.


  • Magali Benoit (CEMES, CNRS, Toulouse)
  • Arthur France-Lanord (CNRS)
  • Noel Jakse (Université Grenoble Alpes)
  • Antonino Marco Saitta (IMPMC – Université Pierre et Marie Curie (UPMC) – Paris)