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Explore trend between Bader charges and oxidation states for binaries with AFLOW database and Python

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BADERvsOS

Explore trend between Bader charges and oxidation states for binaries with AFLOW database and Python.

File 'Full_for_SV_and_MV.csv' includes final data set used in the article Posysaev, S., Miroshnichenko, O., Alatalo, M., Le, D. & Rahman, T. S. Oxidation states of binary oxides from data analytics of the electronic structure. Comput. Mater. Sci. 161, 403–414 (2019) https://doi.org/10.1016/j.commatsci.2019.01.046. You are welcome to read or download the article by April 23 2019 free of charge here https://authors.elsevier.com/c/1Yf~k3In-ul718.

quick_results.py can be used to analyze trends between OS and Bader charges.

aflowlib.py contains all needed functions, make sure it imported properly.

Needed libraries: pandas, requests, re, matplotlib, mendeleev, asyncio, nest_asyncio Note: asyncio library has been added. Asynchronous programming allows making multiple requests to AFLOWLIB server which allows receiving needed data much faster.

How to: In quick_results.py specify

  1. path to save data
  2. desired anion and cation. In the end, the graph will appear.

TODO:

  1. Analysis of mixed valence compounds
  2. And analysis of structures by calculating coordination numbers, cure from duplicates, make sure that each atom has anion-cation bond
  3. Calculation of oxidation states in mixed-valence compounds. mv_mn_new

If you have any questions, please write to posysaev.sergey@gmail.com

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Explore trend between Bader charges and oxidation states for binaries with AFLOW database and Python

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