/Ferrites-Saturation-Magneticzation-Machine-Learning-Model

This project implements an XGBoots machine-learning algorithm to uncover structure composition-saturation magnetization relationship for non-stoichiometric metal substituted ferrites. Essential to learn how to tune compositions of ferrites to achieve desired magnetic properties. Specifically, Mn, Co, Ni, Cu, and Zn inverse spinel structure, for which magnetic moments are computed using DFT calculations.

Primary LanguageJupyter Notebook

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