Tunable stacking fault energies by tailoring local chemical order in CrCoNi medium-entropy alloys
Tunable stacking fault energies by tailoring local chemical order in CrCoNi medium-entropy alloys
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DOI：
10.1073/pnas.1808660115
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发表时间：
2018-09-04
影响因子：
11.1
通讯作者：
Ritchie, Robert O.
中科院分区：
文献类型：
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作者：
Ding, Jun;Yu, Qin;Ritchie, Robert O.
高熵合金（HEAs）由于其独特的力学行为而成为一类有趣的新型金属材料。实现在这些材料的结构-性能关系的详细理解已受到挑战的组成混乱，其独特的机械行为的基础。因此，在这项工作中，我们采用第一性原理计算，调查当地的化学秩序的性质，并建立其内在和外在的堆垛层错能（SFE）在CrCoNi中熵固溶体合金，其强度，延展性和韧性的组合属性接近最好的记录。我们发现，随着局域化学有序度的增加，平均本征和非本征SFE都是高度可调的，其值分别为-43到30 mJ·m（-2）和-28到66 mJ·m（-2）。局部有序状态也与面心立方（fcc）和六方密堆积（hcp）相之间的能量差密切相关，这影响相变诱导塑性的发生。这一理论研究表明，化学短程有序在HEAs中是有利的，并且可以调节以影响这些合金的机械行为。因此，它解决了迫切需要建立强大的工艺-结构-性能关系，以指导具有目标机械行为的新HEAs的科学设计。
High-entropy alloys (HEAs) are an intriguing new class of metallic materials due to their unique mechanical behavior. Achieving a detailed understanding of structure-property relationships in these materials has been challenged by the compositional disorder that underlies their unique mechanical behavior. Accordingly, in this work, we employ first-principles calculations to investigate the nature of local chemical order and establish its relationship to the intrinsic and extrinsic stacking fault energy (SFE) in CrCoNi medium-entropy solid-solution alloys, whose combination of strength, ductility, and toughness properties approaches the best on record. We find that the average intrinsic and extrinsic SFE are both highly tunable, with values ranging from -43 to 30 mJ.m(-2) and from -28 to 66 mJ.m(-2), respectively, as the degree of local chemical order increases. The state of local ordering also strongly correlates with the energy difference between the face-centered cubic (fcc) and hexagonal close-packed (hcp) phases, which affects the occurrence of transformation-induced plasticity. This theoretical study demonstrates that chemical short-range order is thermodynamically favored in HEAs and can be tuned to affect the mechanical behavior of these alloys. It thus addresses the pressing need to establish robust processing-structure-property relationships to guide the science-based design of new HEAs with targeted mechanical behavior.