journal article·2024-01

Unraveling the origin of local chemical ordering in Fe-based solid-solutions

Keyu Yan, Yichen Xu, Jiejue Niu, Yuye Wu, Yue Li, Baptiste Gault, Shiteng Zhao, Xiaoxiao Wang, Yunquan Li, Jingmin Wang, Konstantin P. Skokov, Oliver Gutfleisch, Haichen Wu, Daqiang Jiang, Yangkun He, Chengbao Jiang

Acta Materialia· Volume 264
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Abstract

Local chemical ordering (LCO) can exert pronounced effects on both structural and functional properties, tailoring LCO domains at (sub-)nanoscale could offer an alternative material-design concept for yet unexplored performance. However, the origin of LCO remains an open question, making accurate manipulation of LCO extremely challenging. Here we selected the Fe-Ga magnetostrictive materials and demonstrated that LCO tetragonal structures play a significant role in optimizing the magnetostrictive properties. The “full-lifecycle”, including formation, evolution and dissolution of LCO, is concretely studied from the atomic-scale up by combined experimental and theoretical studies. The dynamic precipitation and dissolution processes of LCO L6 0 domains during isothermal aging are directly observed based on in-situ high-resolution transmission electron microscopy images, and the corresponding mechanisms are revealed by first-principles calculation. Based on the results, we evidence that LCO domain is a frozen-intermediate-state of a kinetically-slow solid-state phase transformation leading to the formation of the long-range-ordered equilibrium phase with a face-center-cubic structure. We confirm the reversibility of LCO during cycling treatments. Our findings shed light on the origin of LCO in a range of material systems, and we discuss directions for developing materials with superior performance by manipulating LCO domains.
Source: expertdata · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Magnetic Properties and Applications · Magnetic properties of thin films · Microstructure and mechanical properties

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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