Constructing first-principles phase diagrams of amorphous LixSi using machine-learning-assisted sampling with an evolutionary algorithm

10 Feb 2018 Artrith Nongnuch Urban Alexander Ceder Gerbrand

The atomistic modeling of amorphous materials requires structure sizes and sampling statistics that are challenging to achieve with first-principles methods. Here, we propose a methodology to speed up the sampling of amorphous and disordered materials using a combination of a genetic algorithm and a specialized machine-learning potential based on artificial neural networks (ANN)... (read more)

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Categories


  • DISORDERED SYSTEMS AND NEURAL NETWORKS
  • COMPUTATIONAL PHYSICS