Generate Python code for simulations with machine learning interatomic potentials

Generate standalone Python code for simulations with universal machine learning interatomic potential

📚 If you like the app, please cite: Lebeda, M., Drahokoupil, J., Mazáčová, V., & Vlčák, P. (2026). Revealing interstitial energetics in Ti-23Nb-0.7Ta-2Zr gum metal base alloy via universal machine learning interatomic potentials. Journal of Materials Research and Technology, 41, 6766–6774.

Compile the application from GitHub: https://github.com/bracerino/mace-md-gui

Generate Python code for performing calculations of single-point energies, geometry optimization, phonons, or elastic properties using MACE machine learning interatomic potential in interactive interface. 

Multiple structures can be uploaded at once and the calculations run in batch mode.