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Cover image for Materials Learning Algorithms

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.

  • DFT
  • machine-learning
  • Python
  • Fortran
  • Shell
  • + 1
11
84
Cover image for FLEUR

FLEUR

FLEUR is a feature-full, freely available FLAPW (full-potential linearized augmented-plane-wave) code, based on density-functional theory. This highly precise all-electron approach is universally applicable to all atoms of the periodic table and to systems with compact as well as open structures.

  • DFT
  • High performance computing
  • hpc
  • + 3
  • Fortran Free Form
  • C
  • Motorola 68K Assembly
  • + 2
32
0