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A fast composition-stability machine learning model for screening MAX phases and guiding discovery of Ti2SnN

Zhiyao Lu Yuelei Bai Yun Fan Zhaoxu Sun Xiaodong He Chuchu Yang Hang Yin Jinze Zhang Guangping Song Yongting Zheng

先进陶瓷（英文版）2025，Vol.14Issue(4)：1-15,15.

先进陶瓷（英文版）2025，Vol.14Issue(4)：1-15,15.DOI:10.26599/JAC.2025.9221050

A fast composition-stability machine learning model for screening MAX phases and guiding discovery of Ti2SnN

Zhiyao Lu ¹Yuelei Bai ¹Yun Fan ¹Zhaoxu Sun ¹Xiaodong He ¹Chuchu Yang ¹Hang Yin ¹Jinze Zhang ¹Guangping Song ¹Yongting Zheng¹

作者信息

1. National Key Laboratory of Science and Technology on Advanced Composites in Special Environments and Center for Composite Materials and Structures,Harbin Institute of Technology,Harbin 150080,China
折叠

摘要

关键词

MAX phases/machine learning(ML)/Ti2SnN/first principles/self-extrusion

Key words

MAX phases/machine learning(ML)/Ti2SnN/first principles/self-extrusion

引用本文复制引用

Zhiyao Lu,Yuelei Bai,Yun Fan,Zhaoxu Sun,Xiaodong He,Chuchu Yang,Hang Yin,Jinze Zhang,Guangping Song,Yongting Zheng..A fast composition-stability machine learning model for screening MAX phases and guiding discovery of Ti2SnN[J].先进陶瓷（英文版）,2025,14(4):1-15,15.

基金项目

This work was supported by the National Natural Science Foundation of China(No.51972080). （No.51972080）

先进陶瓷（英文版）

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