2 papers
cond-mat.mtrl-sci2025
Benchmarking Universal Interatomic Potentials on Zeolite Structures
Shusuke Ito, Koki Muraoka, Akira Nakayama
Interatomic potentials (IPs) with wide elemental coverage and high accuracy are powerful tools for high-throughput materials discovery. While the past few years witnessed the devel…
physics.chem-ph2025
DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning Potentials
Jinzhe Zeng, Duo Zhang, Anyang Peng +44
In recent years, machine learning potentials (MLPs) have become indispensable tools in physics, chemistry, and materials science, driving the development of software packages for m…