---
license: cc-by-4.0
pretty_name: CHILI-3K (CHILI nanomaterials, unofficial mirror)
tags:
  - chemistry
  - materials-science
  - nanomaterials
  - graph-machine-learning
size_categories:
  - 1K<n<10K
---

# CHILI-3K — unofficial Hugging Face mirror

Raw archive of **CHILI-3K** from the CHILI dataset, mirrored to HF for convenient
cloud access. This repo contains the original `.h5` files packaged as `CHILI-3K.zip`
(one HDF5 file per crystal-type / composition; each holds all 5 nanoparticle sizes).

## Attribution (please cite the original authors)

> Friis-Jensen, U., Selvan, R., et al. *CHILI: Chemically-Informed Large-scale
> Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning.* KDD '24.

- Paper: https://arxiv.org/abs/2402.13221
- Code:  https://github.com/UlrikFriisJensen/CHILI  (Apache-2.0)
- Data DOI: https://doi.org/10.17894/ucph.e37b6615-8635-49cf-819d-eae60e781a96

## Licensing

- **Data** (the `.h5` archive in this repo): **CC BY 4.0** — the license of the
  original CHILI dataset/paper. You may share and adapt it *with attribution* to
  the authors above. This is the repo's primary `license:` tag.
- **Original CHILI code** (dataset class, generation scripts): **Apache-2.0**,
  see https://github.com/UlrikFriisJensen/CHILI.
- **Any loader/wrapper code added to this mirror**: **MIT** (covers only the
  helper code, not the data).

This mirror is **unofficial**; all credit to the original authors. Attribution is
preserved as required by CC BY 4.0.

## Contents

- `CHILI-3K.zip` — original raw HDF5 archive from the DTU/ERDA repository.

## Graph-level schema (`y` dict, per the paper's Table 2)

Node `x = [atomic_number, atomic_radius, atomic_weight, electron_affinity]`;
`edge_attr = [distance (Å)]`; `pos_abs` / `pos_frac` atomic coordinates.
`y` holds crystal_type, space_group_*, crystal_system(_number), cell_params[6],
the full unit-cell subgraph, and simulated scattering signals
(nd, xrd, nPDF, xPDF, sans, saxs) — usable as targets **or** conditioning inputs.

Load the original way with the authors' `CHILI` PyG dataset class, or unzip and
read the `.h5` files directly with `h5py`.