exa-PD: A scalable high-performance workflow for multi-element phase diagram construction
Abstract
Exa-PD is a highly parallelizable workflow designed for the construction of multi-element phase diagrams (PDs). It uses standard sampling techniques, molecular dynamics (MD) and Monte Carlo (MC) as implemented in the LAMMPS package, to simultaneously sample multiple phases over a fine temperature-composition mesh for free-energy calculations. Parsl serves as the global workflow engine, coordinating large ensembles of MD and MC tasks to achieve massive parallelization with strong scalability. The resulting free energies of liquid and solid phases are then fed to CALPHAD modeling via the PyCalphad package to construct multi-element PDs.
Cite
@article{arxiv.2607.15476,
title = {exa-PD: A scalable high-performance workflow for multi-element phase diagram construction},
author = {Zhuo Ye and Feng Zhang and Maxim Moraru and Weiyi Xia and Ying Wai Li and Yongxin Yao and Cai-Zhuang Wang},
journal= {arXiv preprint arXiv:2607.15476},
year = {2026}
}
Comments
5 pages, 3 figures. The source code associated with this work is available at https://github.com/ML-AMD/exa-pd