Update README.md

README.md

@@ -59,7 +59,7 @@ dataset_info:
     dtype: float64
   - name: e_electronic
     dtype: float64
-  - name: n
+  - name: 'n'
     dtype: float64
   - name: universal_anisotropy
     dtype: float64
@@ -88,4 +88,159 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc-by-4.0
+pretty_name: Materials Project
+size_categories:
+- 100K<n<1M
+tags:
+- materials-science
+- crystal-structures
+- pymatgen
 ---
+
+
+# Dataset Card for xpanceo-team/materials-project
+
+## Dataset Summary
+
+This dataset is a snapshot of the **Materials Project (MP)** materials database, exported from the MP **Summary** endpoint using `mp-api`.
+
+Snapshot date: **2026-01-18**.
+
+The `structure` column stores **pymatgen `Structure` JSON** serialized as a string. 
+
+Important: For several rich/large MP sub-documents (e.g. XAS, DOS, band structure), this dataset stores only *availability flags* (`*_is_available`) rather than the full objects.
+
+## Source
+
+Upstream data source: the Materials Project database and API documentation.
+
+Materials Project is an open resource for computed materials properties and structures, built using high-throughput DFT workflows and a curated data model.
+
+## Preprocessing
+
+Structures and properties were downloaded using `mp-api` (version `0.45.15`) with `MPRester.materials.summary.search()`.
+
+The export used a fixed field list:
+- “regular” scalar fields (energetics, electronic structure, magnetism, elasticity-related, dielectric-related),
+- `material_id`, `structure`, and symmetry (used to derive `space_group_number` and `crystal_system`),
+- availability checks for selected Emmet (internal document model) sub-documents: `xas`, `bandstructure`, `dos`, `decomposes_to`, `types_of_magnetic_species`.
+
+## Dataset Structure
+
+### Data Instances
+
+Each row corresponds to one Materials Project entry identified by `material_id` (e.g., `mp-149`), with an associated crystal structure and computed properties.
+
+### Data Fields
+
+- `material_id` (string): Materials Project material identifier (e.g., `mp-149`).
+- `structure` (string): **pymatgen `Structure` JSON** (serialized) for the entry’s structure.
+- `deprecated` (bool): Whether the entry is marked deprecated upstream.
+- `space_group_number` (int): International space group number from `mp_doc.symmetry.number`.
+- `crystal_system` (string): Crystal system label from `mp_doc.symmetry.crystal_system`.
+
+Energetics / thermodynamics:
+- `uncorrected_energy_per_atom` (float)
+- `energy_per_atom` (float)
+- `formation_energy_per_atom` (float)
+- `energy_above_hull` (float)
+- `is_stable` (bool)
+- `equilibrium_reaction_energy_per_atom` (float)
+
+Electronic structure:
+- `band_gap` (float)
+- `cbm` (float)
+- `vbm` (float)
+- `efermi` (float)
+- `is_gap_direct` (bool)
+- `is_metal` (bool)
+
+Magnetism (when available):
+- `is_magnetic` (bool)
+- `ordering` (string)
+- `total_magnetization` (float)
+- `total_magnetization_normalized_vol` (float)
+- `total_magnetization_normalized_formula_units` (float)
+- `num_magnetic_sites` (int)
+- `num_unique_magnetic_sites` (int)
+
+Additional properties (when available):
+- `universal_anisotropy` (float)
+- `homogeneous_poisson` (float)
+- `e_total` (float)
+- `e_ionic` (float)
+- `e_electronic` (float)
+- `n` (float)
+- `e_ij_max` (float)
+
+Composition helpers:
+- `possible_species` (list[string])
+- `theoretical` (bool)
+
+Availability flags (full objects are not included in this dataset):
+- `xas_is_available` (bool)
+- `bandstructure_is_available` (bool)
+- `dos_is_available` (bool)
+- `decomposes_to_is_available` (bool)
+- `types_of_magnetic_species_is_available` (bool)
+
+Note: Numeric fields are preserved as-is from the MP Summary documents. Refer to official Materials Project documentation for definitions and conventions.
+
+### Data Splits
+
+Single split:
+- `train`: 210,579 examples
+
+## Usage
+
+Load the dataset:
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("xpanceo-team/materials-project", split="train")
+print(ds)
+print(ds.column_names)
+```
+
+Convert to pandas (may be heavy depending on memory):
+
+```python
+df = ds.to_pandas()
+```
+
+Parse `structure` with pymatgen:
+
+```python
+from pymatgen.core import Structure
+
+row = ds[0]
+structure = Structure.from_str(row["structure"], fmt="json")
+
+print(structure.composition, len(structure))
+```
+
+## Citation
+
+If you use this dataset, please cite the upstream Materials Project publication and acknowledge this Hugging Face repackaging.
+
+```bibtex
+@article{Jain2013MaterialsProject,
+  title   = {Commentary: The Materials Project: A materials genome approach to accelerating materials innovation},
+  author  = {Jain, Anubhav and Ong, Shyue Ping and Hautier, Geoffroy and Chen, Wei and Richards, William Davidson and Dacek, Stephen and Cholia, Shreyas and Gunter, Dan and Skinner, David and Ceder, Gerbrand and Persson, Kristin A.},
+  journal = {APL Materials},
+  year    = {2013},
+  volume  = {1},
+  number  = {1},
+  pages   = {011002},
+  doi     = {10.1063/1.4812323}
+}
+```
+
+## License
+
+
+This dataset is distributed under **Creative Commons Attribution 4.0 (CC BY 4.0)**, consistent with Materials Project’s CC BY 4.0 terms..
+
+If you use or redistribute this dataset (including derivatives), please **cite Materials Project** (see **Citation**) and **indicate if you made changes**, as required by CC BY 4.0.