colabfit/OMat24_train_aimd_from_PBE_3000_nvt
收藏Hugging Face2025-10-20 更新2025-10-18 收录
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https://hf-mirror.com/datasets/colabfit/OMat24_train_aimd_from_PBE_3000_nvt
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资源简介：
OMat24是一个基于PBE 3000 nvt的aimd训练分割的大规模开放密度泛函理论(DFT)计算数据集。该数据集根据结构生成策略分为子数据集和子采样数据集，主要分为训练集和验证集。数据集包含了7839846种独特的分子配置和530963613个原子，涵盖了多种元素。数据集中的属性包括能量、原子力和Cauchy应力。
The aimd-from-PBE-3000-nvt training split of OMat24 (Open Materials 2024). OMat24 is a large-scale open dataset of density functional theory (DFT) calculations. The dataset is available in sub-datasets and subsampled sub-datasets based on the structure generation strategy used. There are two main splits in OMat24: train and validation, each divided into the aforementioned subsampling and sub-datasets. The dataset contains 7839846 unique molecular configurations and 530963613 atoms, covering a variety of elements. Properties included in the dataset are energy, atomic forces, and Cauchy stress.
提供机构：
colabfit
