Machine learning-based prediction of FeNi nanoparticle magnetization

Machine learning-based prediction of FeNi nanoparticle magnetization

This work proposes a computationally efficient approach for estimating the magnetization of Fe0.7Ni0.3 body-centered cubic (bcc) nanoparticles (NPs) at room temperature using machine-learning algorithms, in terms of the average magnetic moment per atom, ⟨μ⟩. The magnetization data of isolated NPs we...

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Bibliographic Details
Main Authors: Federico Williamson, Nadhir Naciff, Carlos Catania, Gonzalo dos Santos, Nicolás Amigo, Eduardo M. Bringa
Format: Article
Language:English
Published: Elsevier 2024-11-01
Series:Journal of Materials Research and Technology
Subjects:
Magnetization
Nanoparticle
Machine learning
Atomistic spin dynamics
FeNi
Online Access:http://www.sciencedirect.com/science/article/pii/S2238785424024128
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