OneScience-Group/NEP

1---2license: gpl-3.03tags:4  - MatPL5  - NEP6  - machine-learning-potential7  - materials-science8  - pwmat9  - pwmlff10  - extxyz11language:12  - en13---14 15<p align="center">16  <strong>17    <span style="font-size: 30px;">NEP</span>18  </strong>19</p>20 21## Dataset Description22 23The NEP dataset provides example data for training materials potentials with `OneScience-Group/NEP`. It includes several materials systems, such as AuAg, Cu, HfO2, and LiSiC, in `pwmat/movement`, `pwmlff/npy`, and `extxyz` formats. The dataset contains atomic coordinates, cell information, energies, and forces for different configurations of these systems. It is intended as a standard benchmark for learning and validating machine-learning interatomic potential methods, including NEP.24 25The current package contains approximately 636 data and metadata files totaling about 38 MB.26 27## Supported Tasks28 29This standardized data repository packages the complete official MatPL examples for four materials systems. It can be used for:30 31- Training and validating machine-learning interatomic potentials32- Fitting potential energy surfaces for materials simulations33- Functional testing and benchmarking of the NEP framework34 35## Dataset Formats and Structure36 37Data files are stored under `data/MatPL/` and grouped by materials system:38 39| Path | Format | Shape/content | Description |40| --- | --- | --- | --- |41| `data/MatPL/AuAg/AuAg-5762.xyz` | extxyz | `[N_frames, N_atoms]` | Configurations for the AuAg system |42| `data/MatPL/Cu/pwdata/0_300_MOVEMENT` | pwmat/movement | `[N_frames, N_atoms]` | Cu training data at 300 K |43| `data/MatPL/Cu/pwdata/1_500_MOVEMENT` | pwmat/movement | `[N_frames, N_atoms]` | Cu training data at 500 K |44| `data/MatPL/Cu/pwdata/valid_movement` | pwmat/movement | `[N_frames, N_atoms]` | Cu validation data |45| `data/MatPL/HfO2/pwdata/init_*/train/atom_type.npy` | npy | `[N_atoms]` | Atomic species for the HfO2 system |46| `data/MatPL/HfO2/pwdata/init_*/train/energies.npy` | npy | `[N_frames]` | Total configuration energies for the HfO2 system |47| `data/MatPL/HfO2/pwdata/init_*/train/forces.npy` | npy | `[N_frames, N_atoms×3]` | Atomic forces for the HfO2 system |48| `data/MatPL/HfO2/pwdata/init_*/train/image_type.npy` | npy | `[N_frames]` | Configuration types for the HfO2 system |49| `data/MatPL/HfO2/pwdata/init_*/train/lattice.npy` | npy | `[N_frames, 9]` | Cell matrices for the HfO2 system |50| `data/MatPL/HfO2/pwdata/init_*/train/position.npy` | npy | `[N_frames, N_atoms×3]` | Atomic coordinates for the HfO2 system |51| `data/MatPL/HfO2/pwdata/init_*/valid/` | npy | Same as above | HfO2 validation-data shards |52| `data/MatPL/LiSiC/pwdata/init_*/train/` | npy | Same as above | LiSiC training-data shards |53| `data/MatPL/LiSiC/pwdata/init_*/valid/` | npy | Same as above | LiSiC validation-data shards |54| `metadata/sha256_manifest.txt` | SHA-256 | Integrity manifest | File-integrity checksums |55 56## Downloading the Dataset57 58```bash59hf download --dataset OneScience-Group/NEP --local-dir ./data60```61 62## Official OneScience Resources63 64| Platform | OneScience Main Repository | Skills Repository |65| --- | --- | --- |66| Gitee | https://gitee.com/onescience-ai/onescience | https://gitee.com/onescience-ai/oneskills |67| GitHub | https://github.com/onescience-ai/OneScience | https://github.com/onescience-ai/oneskills |68 69## Limitations and License70 71This dataset consists of the official MatPL example data. No new samples were generated, and the original data contents were not modified.72 73- **Original source:** Official MatPL repository74- **Model card metadata:** `gpl-3.0`, normalized from the source `GPLv3` declaration75- **Source terms:** Before redistribution or production use, review the licensing and provenance information provided by the original MatPL data sources and the OneScience repository. These source-specific terms remain authoritative for any component with separate licensing.76