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説明:

Ternary MAX phases, characterized by the chemical formula M₂AX, represent a group of layered materials with hexagonal lattices. These MAX phases have been the subject of extensive experimental and theoretical studies. Formation energy and thermodynamic calculations indicate that MAX phases containing late transition metals, such as Rh, Ru, Pt, Pd, Co, and Ni, are unlikely to form. Here, we introduce an alternative family of orthorhombic and monoclinic materials, the LAX phases, which exhibit similarities to MAX phases in terms of their layered structure and A and X elements. However, LAX materials incorporate late transition metals in place of the early transition metals. Advanced techniques for predicting the crystal structure of materials, coupled with data-driven materials research and machine learning algorithms, were employed to investigate the stable structures containing transition metals from the last groups of the d-block elements. The analyses revealed 207 ternary LAX systems that demonstrate robust stability against decomposition, with 100 of these systems showing dynamic stability. An in-depth examination of the top 10 structures revealed five LAX systems that are phase stable and exhibit superior mechanical properties, outperforminMAX phase counterparts in Young's modulus, stiffness, and hardness. These findings indicate that many LAX phase structures are viable candidates for future synthesis, highlighting the potential of heuristic-based structure searches in material discovery.

権利情報:

• Creative Commons BY Attribution 4.0 International
  

キーワード: evolutionary algorithm, LAX phases, machine learning, materials discovery, materials informatics, MAX phases

刊行年月日: 2025-02-17

出版者: Wiley

掲載誌:

• InfoMat (ISSN: 25673165)

研究助成金:

• Iran National Science Foundation 4025794
• Japan Society for the Promotion of Science 24K08211

原稿種別: 出版者版 (Version of record)

MDR DOI:

公開URL: https://doi.org/10.1002/inf2.12664

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更新時刻: 2025-02-23 22:51:28 +0900

MDRでの公開時刻: 2025-02-23 22:51:29 +0900