Статья

Maximizing the mechanical performance of Ti3AlC2-based MAX phases with aid of machine learning

Xingjun DuanBeijing Advanced Innovation Center for Materials Genome Engineering, Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing, 100083, ChinaZhi FangBeijing Advanced Innovation Center for Materials Genome Engineering, Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing, 100083, ChinaTao YangBeijing Advanced Innovation Center for Materials Genome Engineering, Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing, 100083, ChinaChunyu GuoBeijing Advanced Innovation Center for Materials Genome Engineering, Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing, 100083, ChinaZhongkang HanFritz-Haber-Institut der Max-Planck-Gesellschaft, Faradayweg 4-6, Berlin, 14195, GermanyDebalaya SarkerUGC-DAE Consortium for Scientific Research, University Campus, Khandwa Road, Indore, 452001, IndiaXinmei HouBeijing Advanced Innovation Center for Materials Genome Engineering, Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing, 100083, ChinaEnhui WangBeijing Advanced Innovation Center for Materials Genome Engineering, Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing, 100083, China

2022en

ABI

Аннотация

Abstract 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 Ti 3 AlC 2 -based MAX phases via the A-site substitution (Ti 3 (Al 1− x A x )C 2 ). The structure—property correlation between the A-site substitution and mechanical properties of Ti 3 (Al 1− x A x )C 2 is established. The results show that the thermodynamic stability of Ti 3 (Al 1− x A x )C 2 is enhanced with substitutions A = Ga, Si, Sn, Ge, Te, As, or Sb. The stiffness of Ti 3 AlC 2 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 Ti 3 AlC 2 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.

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Идентификаторы

DOI: 10.1007/s40145-022-0612-4

Цитирования и источники

Цитирований: 2Использованных источников: 0

Показатели — AkademScholar