Developing a machine learning Ni-Co-Al ternary interatomic potential for temperature and strain-rate dependent mechanical behaviors of Ni-based single crystal superalloys

Developing a machine learning Ni-Co-Al ternary interatomic potential for temperature and strain-rate dependent mechanical behaviors of Ni-based single crystal superalloys

Ni-based single crystal (SX) superalloys, with excellent mechanical properties in high temperature, are widely used as the preferred materials in the aerospace field. Atomistic simulations provide an effective means to understand the underlying physics of microstructure-property relationship. Howeve...

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Bibliographic Details
Main Authors: Zhijia Qin, Shirong Liang, Linli Zhu, Penghua Ying, Dongfeng Li, Ligang Sun
Format: Article
Language:English
Published: Elsevier 2025-10-01
Series:Materials & Design
Subjects:
Ni-based single crystal superalloys
Precipitation
Machine learning potential
Mechanical behaviors
Molecular dynamics
Online Access:http://www.sciencedirect.com/science/article/pii/S0264127525009554
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