| --- |
| license: mit |
| tags: |
| - physics |
| - Wannier functions |
| --- |
| |
| # WannierDatasets |
|
|
| Datasets of input files for Wannier functions. |
|
|
| ## List of datasets |
|
|
| - `Si2_valence`: Silicon valence band only |
| - `Si2`: Silicon valence and conduction bands |
| - `Si2_3d`: Silicon with 3d orbitals included in the projection |
| - `Cu`: copper, metal |
| - `graphene`: graphene, 2D material |
| - `graphene_soc`: graphene, 2D material, with spin orbit coupling (SOC) |
| - `MoS2`: molybdenum disulfide, 2D material |
| - `Fe_collinear`: iron, collinear magnetic calculation |
| - `Fe_soc`: iron, spin-orbit coupling (SOC) calculation |
| - `CrI3`: chromium triiodide, magnetic calculation |
| - `BN`: 3D boron nitride, insulator |
| - `SnSe2`: tin diselenide, 3D material |
| - `CuBr2`: copper bromide, 3D material |
| - `GaAs`: gallium arsenide |
| - `TiO2`: titanium dioxide, for MRWF with cubic-6-neighbors `nnkp` file |
|
|
| The following datasets are coarse-grained calculations, with fewer k-points |
| and/or fewer bands, for `Wannier.jl` testing purposes: |
| - `Si2_coarse`: silicon valence+conduction bands |
| - `Si2_valence_coarse`: silicon valence band only |
| - `GaAs_coarse`: gallium arsenide |
| - `graphene_coarse`: graphene, 2D material, real-space MLWFs in XSF format |
| - `Fe_collinear_coarse`: iron, collinear magnetic calculation |
|
|
| ## Why this repo? |
|
|
| Specifically, this repo |
|
|
| - provides input data files for running the examples inside |
| [`Wannier.jl`](https://github.com/qiaojunfeng/Wannier.jl) documentation |
| - provides a set of cheap and small datasets for testing |
| [`Wannier.jl`](https://github.com/qiaojunfeng/Wannier.jl) |
| and [`WannierIO.jl`](https://github.com/qiaojunfeng/WannierIO.jl) |
| - allow users to quickly load typical systems when developing algorithms for |
| Wannier functions. Fully focus on Wannier algorithms, without the need of |
| running density functional theory (DFT) calculations |
|
|
| On technical side, we use [Julia Artifacts](https://pkgdocs.julialang.org/v1/artifacts/) |
| to manage the datasets. This allows us to |
|
|
| - keep the `Wannier.jl` and `WannierIO.jl` repositories small and clean |
| - safely rewrite the datasets without the risk of rebasing the history of |
| `Wannier.jl` and `WannierIO.jl` repositories |
| - still providing a convenient way to load the datasets in Julia scripts/REPL. |
|
|
| ## Structure of the repo |
|
|
| The tarballs are stored in the [`artifacts` branch](https://huggingface.co/datasets/atomology/WannierDatasets/tree/artifacts). |
|
|
| While in the [`main` branch](https://huggingface.co/datasets/atomology/WannierDatasets/tree/main), the structure of the repo is as follows: |
| - [`datasets/`](./datasets/) each subfolder contains a dataset as well as input/output files for one material |
| - [`pseudo/`](./pseudo/) pseudopotentials used when generating the datasets |
| - [`src/`](./src/) a fake folder just to make `Project.toml` happy |
|
|
| ## Contributing |
|
|
| If you feel your dataset is useful for the community, please feel free to contribute. |
| Please have a look at the [contributing guidelines](./docs/CONTRIBUTING.md). |
|
|
