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Site-dependent mechanical properties of 3d transition metal-doped MnV intrinsic ductile intermetallic: First-principles and data mining study.

Authors :
Benaissa, Mohammed
Khebichat, Ghada
Sekkal, Abdessamad
Source :
Computational Materials Science. Dec2022, Vol. 215, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

[Display omitted] • The first-principles modelling based on the density functional theory was used to study the site dependent mechanical properties, such as elastic constants and related modulus for 3d transition metal doped MnV intermetallic. • The calculated properties show a dopant-site dependency. • Ni, Cu and Zn doping into MnV is a promising way to further improve ductility while maintaining appreciable hardness. • Data mining revealed that ductile materials show higher formation energies, suggesting that these systems are less stable. In this paper, the first-principles modeling based on the density functional theory (DFT) was used to explore the structural, mechanical, and thermodynamical properties of 3d transition metal-doped MnV intermetallic. The site-dependent mechanical properties such as elastic constants C ij , bulk modulus B , shear modulus G , Young's modulus E , Vickers hardness H V , Poisson's ratio ν , Cauchy pressure C 12 - C 44 , Pugh ratio B / G , and Debye temperature Θ D were systematically presented. Our study suggests that doping 3d metal elements into MnV is a promising way to tune the mechanical properties of the MnV intermetallic and further improve its intrinsic ductility while maintaining appreciable hardness. Data mining is also employed alongside DFT calculations to classify the hard/ductile systems and to study the interrelationships among the systems studied here and their physical properties in order to generate unexpected knowledge. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09270256
Volume :
215
Database :
Academic Search Index
Journal :
Computational Materials Science
Publication Type :
Academic Journal
Accession number :
159626635
Full Text :
https://doi.org/10.1016/j.commatsci.2022.111801