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

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The uploaded data contains (i) "01_Data" optimized molecular structure in XYZ format and the primary attributes and SMILES, (ii) "02_Datasets" datasets used in the publication, and (iv) "03_pynb_script" a Jupyter-Notebook. The 01_Data 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: (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. (2) "freeEnergy.dat" contains the free energy of different states. (3) "schemesquare.dat" has the parameters of the electrochemical scheme of square representation. The new version (v1.1) contains some updates around: (i) The DFT calculations workflow in a folder called "04_workflow_of_DFT" The Gaussian input files have been explained in the "README" file. (ii) The Python scripts for data extraction have been added and can be found in "05_how_to_extracted_data" (iii) We explained how to compute the Purbaix diagram in great detail "06_how_to_compute_Pourbaix_diagram/" All these changes/improvements were applied/made following the Referee of Digital Discovery Journal. Here, we would like to thank him/her.
Näytä enemmän

Julkaisuvuosi

2023

Aineiston tyyppi

Tekijät

Department of Applied Physics

Amir Mahdian - Tekijä

Arsalan Hashemi Petrudi Orcid -palvelun logo - Tekijä

Kari Laasonen Orcid -palvelun logo - Tekijä

Michael Busch - Tekijä

Pekka Peljo Orcid -palvelun logo - Tekijä

Reza Khakpour Orcid -palvelun logo - Tekijä

Ulm University - Muu tekijä

University of Turku - Muu tekijä

Zenodo - Julkaisija

Projekti

Muut tiedot

Tieteenalat

Kemia

Kieli

Saatavuus

Avoin

Lisenssi

Creative Commons Nimeä 4.0 Kansainvälinen (CC BY 4.0)

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Asiasanat

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