Mo-Si Alloys Studied by Atomistic Computer Simulations Using a Novel Machine-Learning Interatomic Potential: Thermodynamics and Interface Phenomena

被引：0

作者：

Lenchuk, Olena ^{[1
]}

Rohrer, Jochen ^{[1
]}

Albe, Karsten ^{[1
]}

机构：

[1] Tech Univ Darmstadt, Inst Mat Sci, Otto Berndt Str 3, D-64287 Darmstadt, Germany

来源：

ADVANCED ENGINEERING MATERIALS | 2024年 / 26卷 / 17期

关键词：

machine-learning interatomic potentials; molecular dynamics; Mo-Si alloys; refractory alloys; STANDARD MOLAR ENTHALPY; COMBUSTION CALORIMETRIC DETERMINATION; MOLYBDENUM DISILICIDE; MECHANICAL-PROPERTIES; ELASTIC-CONSTANTS; THERMAL-EXPANSION; TEMPERATURE; SILICIDES; MO3SI; FLUORINE;

D O I：

10.1002/adem.202302043

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

A machine-learning interatomic potential for Mo-Si alloys based on the atomic cluster expansion formalism is presented, its performance is validated, and it is applied for studying interface phenomena. Structural parameters, elastic constants, and melting temperatures of the crystalline body-centered cubic Mo, diamond Si, and stable Mo-Si alloys (Mo3Si, Mo5Si3, and MoSi2) are calculated and compared to experimental values. Using the trained potential defect, formation energies are calculated and the thermodynamic stability of various MoxSiy alloys is discussed with focus on Mo3Si. Finally, the intermixing between Mo and Si phases is studied by performing interface simulations of Mo|Si. The crystallization behavior of the Mo3Si phase provides additional evidence for the off-stoichiometric composition of this intermetallic phase. A novel machine-learning interatomic potential for Mo-Si alloys is used to investigate the crystallization behavior of the Mo3Si phase and provides evidence for the off-stoichiometric composition of this intermetallic phase.image (c) 2024 WILEY-VCH GmbH

引用

页数：12

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