Mechanical properties consisting of the bulk modulus, shear modulus, Young’s modulus, Poisson’s ratio, etc., are key factors in determining the practical applications of MAX phases. These mechanical properties are mainly dependent on the strength of M-X and M-A bonds. In this study, a novel strategy based on the crystal graph convolution neural network (CGCNN) model has been successfully employed to tune these mechanical properties of Ti₃AlC₂-based MAX phases via the A-site substitution (Ti₃(Al_1−xA_x)C₂). The structure—property correlation between the A-site substitution and mechanical properties of Ti₃(Al_1−xA_x)C₂ is established. The results show that the thermodynamic stability of Ti₃(Al_1−xA_x)C₂ is enhanced with substitutions A = Ga, Si, Sn, Ge, Te, As, or Sb. The stiffness of Ti₃AlC₂ increases with the substitution concentration of Si or As increasing, and the higher thermal shock resistance is closely associated with the substitution of Sn or Te. In addition, the plasticity of Ti₃AlC₂ can be greatly improved when As, Sn, or Ge is used as a substitution. The findings and understandings demonstrated herein can provide universal guidance for the individual synthesis of high-performance MAX phases for various applications.

由体积模量、剪切模量、杨氏模量、泊松比等组成的力学性能是决定 MAX 相实际应用的关键因素。这些机械性能主要取决于 MX 和 MA 键的强度。在这项研究中，一种基于晶体图卷积神经网络 (CGCNN) 模型的新策略已成功用于_通过A 位取代 ( Ti _{3 (} Al _{1− x} A _x )C ₂ )。Ti ₃ (Al _{1− x}A _x )C ₂成立。结果表明，Ti ₃ (Al _{1- x} A _x )C ₂的热力学稳定性通过取代 A = Ga、Si、Sn、Ge、Te、As 或 Sb 得到增强。_{Ti 3} AlC ₂的刚度随着Si或As取代浓度的增加而增加，较高的抗热震性与Sn或Te的取代密切相关。此外，Ti ₃ AlC _2的塑性当使用 As、Sn 或 Ge 作为替代品时，可以大大改善。本文展示的发现和理解可以为各种应用的高性能 MAX 相的单独合成提供通用指导。