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

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

Description

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.
Show more

Year of publication

2023

Authors

Department of Applied Physics

Amir Mahdian - Creator

Arsalan Hashemi Petrudi Orcid -palvelun logo - Creator

Kari Laasonen Orcid -palvelun logo - Creator

Michael Busch - Creator

Pekka Peljo Orcid -palvelun logo - Creator

Reza Khakpour Orcid -palvelun logo - Creator

Ulm University - Contributor

University of Turku - Contributor

Zenodo - Publisher

Other information

Fields of science

Chemical sciences

Open access

Open

License

Creative Commons Attribution 4.0 International (CC BY 4.0)

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