Dataset for: On the Nature of Hydrophobic Organic Compound Adsorption to Smectite Minerals Using the Example of Hexachlorobenzene-Montmorillonite Interactions

This dataset contains all data obtained from first principle DFT calculations at the PBE-D3 DFT levelby the program VASP  for the paper published in the journal "Minerals". Please cite this article when using the dataset.Title: "On the Nature of Hydrophobic Organic Compound Adsorptionto Smectite Minerals Using the Example of Hexachlorobenzene-Montmorillonite Interactions."

Authors: Peter Grancic, Leonard Böhm, Martin H. Gerzabek, and Daniel Tunega DOI10.3390/min13020280.  

The model systems are Ca-montmorillonite (Ca-Mt) models with varying layer charge from the Mg/Al substitutions.Calculated are interaction energies of hexachlorobenzene (HCB) with Ca-Mt models in various configurations.QE.dat file is file with collected energies of all models, Collect_QE.py is a selfmade python file for the collection of energies.The structure of all directories is as following:HCBCaxxx directories contain optimized  HCB-CaMt complexesHCBCaxxx_Clay directories contain  pure CaMt modelsHCBCaxxx_HOC  directories contain only HOC moleculeEach directory contains:-input geometry data (POSCAR file)-optimized geometries (CONTCAR.norm file)-input parameters for VASP (INCAR file)-k-points (KPOINTS file)-complete output files (OUTCAR.norm and vasprun.xml.norm files)POTCAR file with pseudopotentials are not provided due to copyright rights.Their type can be found in OUTCAR or vasprun.xml files.

Funding: This work has been supported by German Research Foundation (Deutsche Forschungsgemeinschaft, DFG), grant number 443637168, BO5388/1–1 and Austrian Science Fund (Fonds zur Förderung der Wissenschaftlichen Forschung, FWF), grant number I 4876–N in the bilateral project ”Clay minerals as sorbents for hydrophobic organic chemicals – ClayHOC”.  The resultspresented have been achieved using the Vienna Scientific Cluster (VSC), project number 70544.

Terms of use: These data are provided "as is", without any warranty. This dataset is provided under the Creative Commons Attribution 4.0 International license.