High-throughput screening of pairwise alloying interaction in bcc-Fe: A DFT and machine learning study

Published: 26 November 2025| Version 2 | DOI: 10.17632/zbm4wjmvny.2
Contributor:
Andrey Kartamyshev

Description

The supplementary materials to the article "A.I. Kartamyshev, D.A. Aksyonov, S.V. Levchenko, A.O. Boev. High-throughput screening of pairwise alloying interaction in bcc-Fe: A DFT and machine learning study". 1. File supplementary materials contains figures and tables additional to the main text of the article. 2. Folder 'sol, vac' contains databases for containing only one solute atom in substitutional, octahedral and tetrahedral positions as well as one substitutional solute atom with vacany on first to third coordination sphere in bcc lattice of iron. 3. Folder sub-sub contains databases for substitutional-substitutional solute pairs on first coordination sphere used to train different machine learning models. 4. Folder oct-sub contains databases for octahedral-substitutional solute pairs on first and second coordination spheres. 5. Folder tet-sub contains databases for tetrahedral-substitutional solute pairs on first and second coordination spheres.

Files

Steps to reproduce

Database files in folders are ready to be used to train the machine learning models.

Categories

Machine Learning, Crystal, Alloy Steel, Point Defect, Database

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