Showing physics.comp-phShow all
2 papers · 1 filter
physics.comp-ph2025
Tadah! A Swiss Army Knife for Developing and Deployment of Machine Learning Interatomic Potentials
M. Kirsz, A. Daramola, A. Hermann +2
The Tadah! code provides a versatile platform for developing and optimizing Machine Learning Interatomic Potentials (MLIPs). By integrating composite descriptors, it allows for a n…
physics.comp-ph2024
Understanding solid nitrogen through machine learning simulation
Marcin Kirsz, Ciprian G. Pruteanu, Peter I. C. Cooke +1
We construct a fast, transferable, general purpose, machine-learning interatomic potential suitable for large-scale simulations of . The potential is trained only on high qual…