MACE with Genetic Algorithm for Point Defects Distribution in Crystal Structure

How to Use MACE with Genetic Algorithm to Find Low Energy Point Defect Configurations in Crystal Structure

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

Use MACE machine learning interatomic potential with genetic algorithm to find the possible lowest energy states of point defects distribution (substitutions, vacancies) in a crystal structure.