DAC-SIM

Associated dataset and files for the paper entitled"<b>Accelerating CO2 Direct Air Capture Screening for Metal-Organic Frameworks with a Transferable Machine Learning Force Field</b>"<br><br><b>GoldDAC.zip</b><br>- The dataset used to train and evaluate the developed MLFF (MACE-DAC).<br>- General descriptions were provided in Readme.md file in the .zip file.<br><br><b>DACSIM_optimized_coremof_2019_asr.zip</b><br>- <i>7,906 frameworks</i> undergone geometry optimization using MLFF (MACE-DAC-1) were provided as .cif file.<br>- Excluding frameworks with more than 250 atoms, 8,131 frameworks from CoRE MOF 2019 ASR database were initially considered.<br>- A few frameworks (~2.8 %) were failed during geometry optimization stage.<br><br><b>chemically_correct_promising_mofs.zip</b><br>- <i>119 chemically correct frameworks</i> suitable for DAC application were provided as .cif file.<br>- A total of 161 frameworks were originally regarded as promising during screening stage; however, 42 of them contain chemically impractical moieties (e.g. missing hydrogen atom or overlapping of atoms due to symmetry issues).<br><br><b>DACSIM_screening_coremof_2019_asr.csv</b><br>- Screening results for 7,906 geometry optimized frameworks.<br>- Adsorption properties (e.g. averaged interaction energy, Henry's law coefficient, and heat of adsorption) calculated from the Widom insertion Monte Carlo (MC) simulation were collected.<br>- Two independent calculations were conducted and the mean value of those two calculations were set as the final value.<br><br><b>DACSIM-Qst_vs_ODAC23-Eint</b><br>- Minimum interaction energy (referred to adsorption energy in the orginal paper) obtained from ODAC 2023 database were provided with heat of adsorption (Qst) values calculated in this work.<br>- A total of <i>2,794 frameworks</i> existed across both dataset.<br><br><b>DACSIM_FF_screening.csv</b><br>- Qst calculated using a classical force field (a combination of universal force field and DDEC charges) were provided with Qst values calculated in this work.<br>- A total of <i>2,654 frameworks</i> existed across both dataset.<br><br><b>Feature_analysis.csv</b><br>- A file that describes what chemical features the 119 chemcially correct promising MOFs contain.<br>- If the framework contain certain feature, it designate as 1; otherwise, it designate as 0.<br>