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license: cc-by-4.0
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---
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license: cc-by-4.0
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tags:
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- chemistry
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- materials
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---
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<h1 align="center" style="font-size: 36px;">Meta Open Materials 2024 (OMat24) Dataset</h1>
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<p align="center">
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<img width="559" height="200" src="https://cdn-uploads.huggingface.co/production/uploads/67004f02d66ad0efb0d494c3/yYySyR4CZjnRr09MB33bS.png"?
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</p>
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## Overview
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Several datasets were utilized in this work. We provide open access to all datasets used to help accelerate research in the community.
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This includes the OMat24 dataset as well as our modified sAlex dataset. Details on the different datasets are provided below.
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## Datasets
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### OMat24 Dataset
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The OMat24 dataset contains a mix of single point calculations of non-equilibrium structures and
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structural relaxations. The dataset contains structures labeled with total energy (eV), forces (eV/A)
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and stress (eV/A^3). The dataset is provided in ASE DB compatible lmdb files.
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The OMat24 train and val splits are fully compatible with the Matbench Discovery benchmark test set.
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1. The splits do not contain any structure that has a protostructure label present in the initial or relaxed
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structures of the WBM dataset.
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2. The splits do not include any structure that was generated starting from an Alexandria relaxed structure with
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protostructure lable in the intitial or relaxed structures of the WBM datset.
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We provide two splits - train and val. Each split is comprised of several subdatasets based on the different input generation strategies, see paper for more details.
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##### Train
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| Sub-dataset | Size | Download |
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| :-----: | :--: | :------: |
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| rattled-1000 | 11,388,510 | [rattled-1000.tar.gz](https://dl.fbaipublicfiles.com/opencatalystproject/data/omat/241018/omat/train/rattled-1000.tar.gz) |
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| rattled-1000-subsampled | 3,879,741 | [rattled-1000-subsampled.tar.gz](https://dl.fbaipublicfiles.com/opencatalystproject/data/omat/241018/omat/train/rattled-1000-subsampled.tar.gz) |
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| rattled-500 | 6,922,197 | [rattled-500.tar.gz](https://dl.fbaipublicfiles.com/opencatalystproject/data/omat/241018/omat/train/rattled-500.tar.gz) |
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| rattled-500-subsampled | 3,975,416 | [rattled-500-subsampled.tar.gz](https://dl.fbaipublicfiles.com/opencatalystproject/data/omat/241018/omat/train/rattled-500-subsampled.tar.gz) |
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| rattled-300 | 6,319,139 | [rattled-300.tar.gz](https://dl.fbaipublicfiles.com/opencatalystproject/data/omat/241018/omat/train/rattled-300.tar.gz) |
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| rattled-300-subsampled | 3,464,007 | [rattled-300-subsampled.tar.gz](https://dl.fbaipublicfiles.com/opencatalystproject/data/omat/241018/omat/train/rattled-300-subsampled.tar.gz) |
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| aimd-from-PBE-1000-npt | 21,269,486 | [aimd-from-PBE-1000-npt.tar.gz](https://dl.fbaipublicfiles.com/opencatalystproject/data/omat/241018/omat/train/aimd-from-PBE-1000-npt.tar.gz) |
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| aimd-from-PBE-1000-nvt | 20,256,650 | [aimd-from-PBE-1000-nvt.tar.gz](https://dl.fbaipublicfiles.com/opencatalystproject/data/omat/241018/omat/train/aimd-from-PBE-1000-nvt.tar.gz) |
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| aimd-from-PBE-3000-npt | 6,076,290 | [aimd-from-PBE-3000-npt.tar.gz](https://dl.fbaipublicfiles.com/opencatalystproject/data/omat/241018/omat/train/aimd-from-PBE-3000-npt.tar.gz) |
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| aimd-from-PBE-3000-nvt | 7,839,846 | [aimd-from-PBE-3000-nvt.tar.gz](https://dl.fbaipublicfiles.com/opencatalystproject/data/omat/241018/omat/train/aimd-from-PBE-3000-nvt.tar.gz) |
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| rattled-relax | 9,433,303 | [rattled-relax.tar.gz](https://dl.fbaipublicfiles.com/opencatalystproject/data/omat/241018/omat/train/rattled-relax.tar.gz) |
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| Total | 100,824,585 | - |
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##### Val
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| Sub-dataset | Size | Download |
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| :-----: | :--: | :------: |
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| rattled-1000 | TODO | TODO |
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| rattled-1000-subsampled | TODO | TODO |
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| rattled-500 | TODO | TODO |
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| rattled-500-subsampled | TODO | TODO |
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| rattled-300 | TODO | TODO |
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| rattled-300-subsampled | TODO | TODO |
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| aimd-from-PBE-1000-npt | TODO | TODO |
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| aimd-from-PBE-1000-nvt | TODO | TODO |
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| aimd-from-PBE-3000-npt | TODO | TODO |
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| aimd-from-PBE-3000-nvt | TODO | TODO |
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| rattled-relax | TODO | TODO |
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| Total | TODO | - |
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### sAlex Dataset
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We also provide the sAlex dataset used for fine-tuning of our OMat models. sAlex is a subsampled, Matbench-Discovery compliant, version of the original [Alexandria](https://alexandria.icams.rub.de/).
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sAlex was created by removing structures matched in WBM and only sampling structure along a trajectory with an energy difference greater than 10 meV/atom. For full details,
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please see the manuscript.
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| Dataset | Split | Size | Download |
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| :-----: | :---: | :--: | :------: |
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| sAlex | train | 10,447,765 | [train.tar.gz](dl.fbaipublicfiles.com/opencatalystproject/data/omat/241018/sAlex/train.tar.gz) |
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| sAlex | val | 553,218 | [val.tar.gz](dl.fbaipublicfiles.com/opencatalystproject/data/omat/241018/sAlex/val.tar.gz) |
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## How to read the data
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The OMat24 and sAlex datasets can be accessed with the [fairchem](https://github.com/FAIR-Chem/fairchem) library. This package can be installed with:
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```
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pip install fairchem-core
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```
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Dataset files are written as `AseLMDBDatabase` objects which are an implementation of an [ASE Database](https://wiki.fysik.dtu.dk/ase/ase/db/db.html),
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in LMDB format. A single **.aselmdb* file can be read and queried like any other ASE DB (not recommended as there are many files!).
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You can also read many DB files at once and access atoms objects using the `AseDBDataset` class.
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For example to read the **rattled-relax** subdataset,
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```python
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from fairchem.core.datasets import AseDBDataset
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dataset_path = "/path/to/omat24/train/rattled-relax"
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config_kwargs = {} # see tutorial on additional configuration
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dataset = AseDBDataset(config=dict(src=dataset_path, **config_kwargs))
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# atoms objects can be retrieved by index
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atoms = dataset.get_atoms(0)
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```
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To read more than one subdataset you can simply pass a list of subdataset paths,
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```python
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from fairchem.core.datasets import AseDBDataset
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config_kwargs = {} # see tutorial on additional configuration
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dataset_paths = [
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"/path/to/omat24/train/rattled-relax",
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"/path/to/omat24/train/rattled-1000-subsampled",
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"/path/to/omat24/train/rattled-1000"
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]
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dataset = AseDBDataset(config=dict(src=dataset_paths, **config_kwargs))
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```
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To read all of the OMat24 training or validations splits simply pass the paths to all subdatasets.
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## Citation
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The OMat24 dataset is licensed under a [Creative Commons Attribution 4.0 License](https://creativecommons.org/licenses/by/4.0/legalcode). If you use this work, please cite:
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```
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@misc{barroso_omat24,
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title={Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models},
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author={Luis Barroso-Luque and Muhammed Shuaibi and Xiang Fu and Brandon M. Wood and Misko Dzamba and Meng Gao and Ammar Rizvi and C. Lawrence Zitnick and Zachary W. Ulissi},
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year={2024},
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eprint={2410.12771},
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archivePrefix={arXiv},
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primaryClass={cond-mat.mtrl-sci},
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url={https://arxiv.org/abs/2410.12771},
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}
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```
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