colabfit/Open_Direct_Air_Capture_ODAC2025_Train_Full

这是ODAC25的完整（未过滤）训练分割。ODAC25是一个大规模DFT数据集，旨在推进用于从潮湿空气中直接捕获大气CO2的金属有机骨架（MOF）吸附剂的计算机筛选。该数据集涵盖约15,000个MOF，包括实验性、有缺陷、合成和胺功能化的骨架，包含近6000万个单点计算，覆盖四种吸附物：CO2、H2O、N2和O2。所有计算均使用VASP 6.3进行，采用PBE泛函并增强D3色散校正（Becke-Johnson阻尼）。全程使用自旋极化计算（ISPIN=2）。相对于ODAC23，ODAC25增加了两种新吸附物（N2和O2）、功能化MOF变体、改进的k点收敛以及裸MOF单元的重新弛豫。提供了三种配置集：mof_plus_adsorbate（吸附物负载MOF的完整DFT弛豫）、mof（空框架的重新弛豫）和gcmc（从巨正则蒙特卡洛模拟导出的DFT单点）。This is the full (unfiltered) training split of ODAC25. ODAC25 is a large-scale DFT dataset intended to advance the computational screening of Metal-Organic Framework (MOF) sorbents for direct air capture (DAC) of atmospheric CO2 from humid air. Spanning ~15,000 MOFs, including experimental, defective, synthetic, and amine-functionalized frameworks, the dataset comprises nearly 60 million single-point calculations covering four adsorbates: CO2, H2O, N2, and O2. All calculations were performed with VASP 6.3 using the PBE functional augmented with D3 dispersion corrections (Becke-Johnson damping). Spin-polarized calculations (ISPIN=2) were used throughout. Relative to ODAC23, ODAC25 adds two new adsorbates (N2 and O2), functionalized MOF variants, improved k-point convergence, and re-relaxations of bare MOF cells. Three configuration sets are provided: mof_plus_adsorbate (full DFT relaxations of adsorbate-loaded MOFs), mof (re-relaxations of empty frameworks), and gcmc (DFT single points derived from Grand Canonical Monte Carlo simulations).