Update README.md

README.md

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----
-license: cc0-1.0
----
+
+---
+license: cc0-1.0
+task_categories:
+  - other
+tags:
+  - chemistry
+  - crystallography
+  - xrd
+  - materials-science
+pretty_name: COD XRD Patterns
+size_categories:
+  - 100K<n<1M
+---
+
+# Crystallography Open Database — Synthetic XRD Patterns
+
+436,196 synthetic powder X-ray diffraction (XRD) patterns generated from every CIF file in the [Crystallography Open Database](https://www.crystallography.net/cod/) (COD).
+
+## What's in the dataset
+
+Each pattern is a simulated powder diffractogram computed from a published crystal structure. The dataset covers the full chemical and structural diversity of COD: metals, minerals, organics, MOFs, and everything in between. No measured (experimental) patterns are included — these are purely computational.
+
+## Files and subsets
+
+| File | Patterns | Purpose |
+|---|---|---|
+| `COD_xrd_patterns_1000.pt` | 1,000 | Quick prototyping |
+| `COD_xrd_patterns_10000.pt` | 10,000 | Development / hyperparameter tuning |
+| `COD_xrd_patterns_50000.pt` | 50,000 | Development / hyperparameter tuning |
+| `COD_xrd_patterns_100000.pt` | 100,000 | Development / hyperparameter tuning |
+| `COD_xrd_patterns.pt` | 436,196 | Full dataset |
+
+The smaller subsets are random samples drawn from the full set.
+
+## Data format
+
+Each `.pt` file is a Python dictionary saved with `torch.save()`. Load it with:
+
+```python
+import torch
+
+data = torch.load("COD_xrd_patterns.pt")
+
+patterns = data["patterns"]    # torch.Tensor, shape (N, 4500)
+filenames = data["filenames"]  # list[str], length N
+```
+
+- **`patterns`**: A float tensor where each row is a 4,500-point XRD intensity vector.
+- **`filenames`**: The corresponding COD CIF filenames (e.g. `"4326570.cif"`).
+
+## Generation parameters
+
+| Parameter | Value |
+|---|---|
+| Software | pymatgen `XRDCalculator` |
+| Radiation | Cu K-alpha (lambda = 1.54184 angstrom) |
+| 2-theta range | 0 to 90 degrees |
+| Step size | 0.02 degrees |
+| Points per pattern | 4,500 |
+| Normalisation | Min-max scaled to [0, 1] |
+
+Patterns were generated by reading each CIF file, computing the theoretical diffraction peak positions and intensities, and interpolating onto the uniform 2-theta grid. Regions with no diffraction peaks are zero-padded.
+
+## Finding the original CIF files
+
+Every filename maps directly to a COD entry. Strip the `.cif` extension to get the COD ID, then download the structure file:
+
+```
+Filename:  4326570.cif
+COD ID:    4326570
+URL:       https://www.crystallography.net/cod/4326570.cif
+```
+
+## License
+
+CC0 1.0 Universal — same as the Crystallography Open Database itself.
+
+## Citation
+
+If you use this dataset, please cite:
+
+**COD:**
+Grazulis, S. et al. "Crystallography Open Database — an open-access collection of crystal structures." *Journal of Applied Crystallography*, 42(4), 726–729, 2009.
+
+**pymatgen:**
+Ong, S. P. et al. "Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis." *Computational Materials Science*, 68, 314–319, 2013.