Combination of ab initio descriptors and machine learning approach for the prediction of the plasticity mechanisms in β-metastable Ti alloys

Combination of ab initio descriptors and machine learning approach for the prediction of the plasticity mechanisms in β-metastable Ti alloys

This study proposes a machine-learning (ML) model combining ab initio calculations and an experimental dataset of 201 alloys (in addition to pure Ti) to predict the activated plasticity mechanisms in β-Ti alloys. This methodology is shown to be more efficient than the so-called Bo¯-Md¯ approach, ach...

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Bibliographic Details
Main Authors: M. Coffigniez, P.-P. De Breuck, L. Choisez, M. Marteleur, M.J. van Setten, G. Petretto, G.-M. Rignanese, P.J. Jacques
Format: Article
Language:English
Published: Elsevier 2024-03-01
Series:Materials & Design
Subjects:
β-metastable titanium alloys
Plasticity mechanisms
Machine learning
Ab initio
TRIP
Twip
Online Access:http://www.sciencedirect.com/science/article/pii/S0264127524001734

Internet

http://www.sciencedirect.com/science/article/pii/S0264127524001734

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