GitHub - samarerstm/MoS2_dataset: Dataset for training a Neural Network (NN) potential for MoS2, covering layered and amorphous structures. Includes atomic configurations, energies, and forces from first-principles calculations. Useful for developing ML interatomic potentials for MoS2 across different phases.

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
dE_0.0_0.2		dE_0.0_0.2
dE_0.2_0.3		dE_0.2_0.3
dE_0.3_0.4		dE_0.3_0.4
dE_0.4_0.5		dE_0.4_0.5
dE_0.5_0.6		dE_0.5_0.6
dE_0.6_0.7		dE_0.6_0.7
README		README

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Data Organization

The .yaml files are categorized into different folders based on their energy relative to the convex hull. For example, the folder dE_0.2_0.3 contains structures with energies between 0.2 and 0.3 eV/atom above the global minimum.

Units

All data are provided in atomic units:

Energy: Hartree (Ha)

Length: Bohr

Force: Ha/Bohr

Computational Details

The dataset was generated using the PW91 exchange-correlation functional in combination with Vanderbilt ultra-soft pseudopotentials.

Data Usage

You are not required to use all the available data. Structures with energy differences greater than 0.5 eV/atom above the global minimum can be ignored.

For any further inquiries, please contact the dataset provider.

About

Dataset for training a Neural Network (NN) potential for MoS2, covering layered and amorphous structures. Includes atomic configurations, energies, and forces from first-principles calculations. Useful for developing ML interatomic potentials for MoS2 across different phases.

Readme