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Materials Learning Algorithms
MALA (Materials Learning Algorithms) is a data-driven framework to accelerate electronic structure calculations based on machine learning. Its purpose is to construct neural-network surrogate models for bypassing computationally expensive steps in state-of-the-art density functional simulations.
- Density functional theory
- electronic structure
- machine-learning
- + 2
- Python
- Fortran
- Shell
- + 1
28
227
JuKKR
The Korringa-Kohn-Rostoker (KKR) Greens function method is a highly accurate all-electron method to perform density functional theory calculations for the prediction of materials properties based on quantum mechanical simulations.
- CPU
- Density functional theory
- High performance computing
- + 5
- Fortran Free Form
- Fortran
- TeX
- + 2
29
0