Title :

Collinear-spin machine learned interatomic potential for Fe7Cr2Ni alloy

Author(s) :

Shenoy, Lakshmi [Auteur]
University of Warwick [Coventry]
Woodgate, Christopher D. [Auteur]
University of Warwick [Coventry]
Staunton, Julie B. [Auteur]
University of Warwick [Coventry]
Bartók, Albert P. [Auteur]
University of Warwick [Coventry]
Becquart, Charlotte [Auteur]
Unité Matériaux et Transformations (UMET) - UMR 8207
Etude et Modélisation des Mécanismes de Vieillissement des Matériaux [EM2VM]
Domain, Christophe [Auteur]
Matériaux et Mécanique des Composants [EDF R&D MMC]
Etude et Modélisation des Mécanismes de Vieillissement des Matériaux [EM2VM]
Kermode, James R. [Auteur]
University of Warwick [Coventry]

Journal title :

Physical Review Materials

Abbreviated title :

Phys. Rev. Materials

Volume number :

8

Publisher :

American Physical Society (APS)

Publication date :

2024-03-22

ISSN :

2475-9953

HAL domain(s) :

Chimie/Matériaux
Physique [physics]/Matière Condensée [cond-mat]/Science des matériaux [cond-mat.mtrl-sci]

English abstract : [en]

We have developed a machine learned interatomic potential for the prototypical austenitic steel Fe7Cr2Ni, using the Gaussian approximation potential (GAP) framework. This GAP can model the alloy's properties with close to ...
Show more >We have developed a machine learned interatomic potential for the prototypical austenitic steel Fe7Cr2Ni, using the Gaussian approximation potential (GAP) framework. This GAP can model the alloy's properties with close to density functional theory (DFT) accuracy, while at the same time allowing us to access larger length and time scales than expensive first-principles methods. We also extended the GAP input descriptors to approximate the effects of collinear spins (spin GAP), and demonstrate how this extended model successfully predicts structural distortions due to antiferromagnetic and paramagnetic spin states. We demonstrate the application of the spin GAP model for bulk properties and vacancies and validate against DFT. These results are a step towards modeling the atomistic origins of ageing in austenitic steels with higher accuracy.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

European Project :

European Database for Multiscale Modelling of Radiation Damage

Administrative institution(s) :

Université de Lille
CNRS
INRAE
ENSCL

Collections :

• Unité Matériaux et Transformations (UMET) - UMR 8207

Research team(s) :

Métallurgie Physique et Génie des Matériaux

Submission date :

2024-03-25T07:07:33Z
2024-03-27T08:50:16Z