Density Functional Theory and Machine Learning for Electrochemical Square-Scheme Prediction: An Application to Quinone-type Molecules Relevant to Redox Flow Batteries

<p>The uploaded data contains (i) &quot;<strong>01_Data</strong>&quot;&nbsp;optimized molecular structure in XYZ format and the&nbsp;primary attributes and SMILES, (ii)&nbsp;&quot;<strong>02_Datasets</strong>&quot; datasets used in the publication, and (iv) &quot;<strong>03_pynb_script</strong>&quot; a Jupyter-Notebook. The&nbsp;<strong>01_Data </strong>directory contains more than 8000 subdirectories. Each is for a molecule that undergoes a two-proton two-electron transfer reaction. In each subdirectory, one finds the following files:</p> <p>(1) directories named corresponding to the ones in Figure 1 of the paper. Inside each, there are geometries and properties in XYZ and CSV format, respectively.</p> <p>(2)<strong> &quot;freeEnergy.dat&quot;&nbsp;</strong>contains the free energy of different states.</p> <p>(3) <strong>&quot;schemesquare.dat&quot; </strong>has&nbsp;the parameters of the electrochemical scheme of square representation.</p> <p>├── A<br> │&nbsp;&nbsp;&nbsp;├── info.csv<br> │&nbsp;&nbsp;&nbsp;└── pos.xyz<br> ├── A1-<br> │&nbsp;&nbsp;&nbsp;├── info.csv<br> │&nbsp;&nbsp;&nbsp;└── pos.xyz<br> ├── A2-<br> │&nbsp;&nbsp;&nbsp;├── info.csv<br> │&nbsp;&nbsp;&nbsp;└── pos.xyz<br> ├── AH<br> │&nbsp;&nbsp;&nbsp;├── info.csv<br> │&nbsp;&nbsp;&nbsp;└── pos.xyz<br> ├── AH1+<br> │&nbsp;&nbsp;&nbsp;├── info.csv<br> │&nbsp;&nbsp;&nbsp;└── pos.xyz<br> ├── AH1-<br> │&nbsp;&nbsp;&nbsp;├── info.csv<br> │&nbsp;&nbsp;&nbsp;└── pos.xyz<br> ├── AH2<br> │&nbsp;&nbsp;&nbsp;├── info.csv<br> │&nbsp;&nbsp;&nbsp;└── pos.xyz<br> ├── AH21+<br> │&nbsp;&nbsp;&nbsp;├── info.csv<br> │&nbsp;&nbsp;&nbsp;└── pos.xyz<br> ├── AH22+<br> │&nbsp;&nbsp;&nbsp;├── info.csv<br> │&nbsp;&nbsp;&nbsp;└── pos.xyz<br> ├── <strong>freeEnergy.dat</strong><br> └── <strong>schemesquare.dat</strong><br> ******************************************************<br> The new version (v1.1) contains some updates around:<br> (i) The DFT calculations workflow in a folder called &quot;<strong>04_workflow_of_DFT</strong>&quot;</p> <p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; The Gaussian input files have been explained in the &quot;README&quot; file.</p> <p>(ii) The Python scripts for data extraction have been added and can be found in &quot;<strong>05_how_to_extracted_data</strong>&quot;</p> <p>(iii) We explained how to compute the Purbaix diagram in great&nbsp;detail&nbsp;&quot;<strong>06_how_to_compute_Pourbaix_diagram</strong>/&quot;</p> <p>All these changes/improvements were applied/made following the Referee of Digital Discovery Journal. Here, we would like to thank him/her.</p>