Exploration of Solid Solutions and the Strengthening of Aluminum Substrates by Alloying Atoms: Machine Learning Accelerated Density Functional Theory Calculations

Exploration of Solid Solutions and the Strengthening of Aluminum Substrates by Alloying Atoms: Machine Learning Accelerated Density Functional Theory Calculations

In this paper, we studied the effects of a series of alloying atoms on the stability and micromechanical properties of aluminum alloy using a machine learning accelerated first-principles approach. In our preliminary work, high-throughput first-principles calculations were explored and the solution...

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Bibliographic Details
Main Authors: Jingtao Huang, Jingteng Xue, Mingwei Li, Yuan Cheng, Zhonghong Lai, Jin Hu, Fei Zhou, Nan Qu, Yong Liu, Jingchuan Zhu
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Materials
Subjects:
aluminum substrate
single atoms
mechanical properties
explainable machine learning
density function theory
Online Access:https://www.mdpi.com/1996-1944/16/20/6757

Internet

https://www.mdpi.com/1996-1944/16/20/6757

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