Oxides

Dataset Description

Oxides is derived from the oxide polymorph study published by Mehta, Salvador, and Kitchin in 2015. FAIR Chemistry provides the JSON data from the paper's supporting information with its fine-tuning tutorial. This repository extracts PBE/EOS/calculations from that data and standardizes it as ASE SQLite databases.

The dataset covers five oxides—IrO2, RuO2, SnO2, TiO2, and VO2—across 30 oxide/polymorph groups. Each record contains a periodic structure, DFT total energy, atomic forces, and stress. The splits contain 238 training structures, 28 validation structures, and 29 test structures, for a total of 295 equation-of-state (EOS) crystal structures.

Source paper: P. Mehta, P. A. Salvador, and J. R. Kitchin, Identifying Potential BO2 Oxide Polymorphs for Epitaxial Growth Candidates, ACS Applied Materials & Interfaces 6(5), 3630–3639 (2015).

Paper: https://pubs.acs.org/doi/10.1021/am4059149
DOI: https://doi.org/10.1021/am4059149

Data sources:

• FAIR Chemistry fine-tuning tutorial: https://github.com/FAIR-Chem/fairchem/blob/main/docs/core/common_tasks/fine-tuning/fine-tuning.md
• Supporting information distributed by FairChem with the tutorial: https://github.com/FAIR-Chem/fairchem/blob/main/docs/core/common_tasks/fine-tuning/supporting-information.json

This repository provides the preprocessed data in ASE DB format. data/OXIDES/ contains four data files totaling approximately 605 KiB.

Supported Tasks

This standardized dataset contains oxide PBE EOS training, validation, and test data suitable for:

• Analyzing relationships among oxide EOS structures, energies, and volumes
• Training, fine-tuning, and evaluating interatomic potentials on energies and atomic forces
• Independent validation and generalization analysis of oxide polymorphs
• Validating data loading and processing pipelines for energy, force, and stress labels
• The OneScience eSEN oxide PBE fine-tuning example

Dataset Format and Structure

The data files are located under data/OXIDES/:

data/OXIDES/
├── manifest.json
└── prepared/
    ├── train.db
    ├── val.db
    └── test.db

File	Format	Shape / contents	Description
data/OXIDES/prepared/train.db	ASE SQLite	238 structures	Training split
data/OXIDES/prepared/val.db	ASE SQLite	28 structures	Validation split
data/OXIDES/prepared/test.db	ASE SQLite	29 structures	Test split
data/OXIDES/manifest.json	JSON	Split and source metadata	Data source, random seed, split strategy, and sample counts
metadata/schema.yaml	YAML	Data schema	ASE DB fields, units, and split definitions
metadata/sha256_manifest.txt	SHA256	Four entries	Data-file integrity manifest

The split is grouped by oxide/polymorph with a random seed of 42. The EOS trajectory for a given polymorph never crosses the training, validation, and test splits, preventing trajectory-level data leakage.

ASE DB Format

Each row in an ASE SQLite database represents one periodic crystal structure:

Field	Type	Description
numbers	int array	Atomic numbers
positions	float array	Cartesian coordinates in Å
cell	float array	Unit-cell matrix in Å
pbc	bool array	Periodic boundary conditions
energy	float	DFT total energy in eV
forces	float array	Atomic forces with shape [N, 3] in eV/Å
stress	float array	Six-component Voigt stress in eV/ų
oxide	str	Oxide chemical formula
polymorph	str	Polymorph group name
xc	str	Exchange-correlation functional, fixed to PBE

Stress values in the source supporting information are given in GPa and were converted to the ASE unit of eV/ų before publication. This repository does not redistribute the original JSON file.

Usage

Download the dataset:

hf download OneScience-Group/oxides --repo-type dataset --local-dir ./oxides
cd oxides

Validate the dataset directory, sample counts, ASE fields, and SHA256 checksums:

python scripts/validate_oxides.py \
  --dataset-root data/OXIDES \
  --checksum-manifest metadata/sha256_manifest.txt

To skip SHA256 verification and check only the data structure:

python scripts/validate_oxides.py \
  --dataset-root data/OXIDES \
  --skip-checksum

The dataset can be used directly with interatomic-potential training, fine-tuning, and independent evaluation workflows that support ASE DB files. The OneScience eSEN oxide PBE example uses the three databases under data/OXIDES/prepared/.

Official OneScience Resources

Platform	OneScience main repository	Skills repository
Gitee	https://gitee.com/onescience-ai/onescience	https://gitee.com/onescience-ai/oneskills
GitHub	https://github.com/onescience-ai/OneScience	https://github.com/onescience-ai/oneskills

Limitations and License

This repository covers only five oxides and a specific collection of PBE EOS trajectories. Its small scale does not represent the general distribution of inorganic materials. It is suitable for tutorials, fine-tuning pipeline checks, and method reproduction, but should not be used directly as a general-purpose interatomic-potential training set.

This release is distributed under the Apache License 2.0, which applies to the curation, conversion, metadata, validation scripts, and documentation in this repository. The original PBE EOS data comes from the paper's supporting information distributed with the FairChem tutorial. The Apache License 2.0 does not replace the provenance, attribution, or any other applicable requirements of that upstream data. When using or redistributing the dataset, retain the appropriate citations to FairChem, the supporting information, and the paper by Mehta et al.