通过掺杂微量硼减少退火孪晶边界,改善铁锰硅基合金的形状记忆效应

IF 4.3 2区 材料科学 Q2 CHEMISTRY, PHYSICAL Intermetallics Pub Date : 2024-11-15 DOI:10.1016/j.intermet.2024.108552
Guoqing Cao , Yanni Luo , Yu Fu, Qilin Wang, Huabei Peng, Yuhua Wen
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引用次数: 0

摘要

以往的研究表明,形状记忆效应(SME)与铁锰硅基合金中退火孪晶边界(ATB)的密度呈强烈的负相关。因此,降低 ATB 的密度是改善铁锰硅基合金 SME 的有效方法。本研究调查了溶液处理铁锰硅基合金中掺杂痕量硼对 ATB 密度和由此产生的 SME 的影响。结果表明,掺杂 89 ppm B 有效降低了溶液处理铁锰硅基合金中的 ATB 密度。因此,其 SME 显著提高。掺入硼的合金的最大形状恢复应变达到 2.7%,比未掺入硼的合金高出 1.3%。这项研究为通过掺杂痕量硼来改善 SME 提供了一条新途径,这对于以更具成本效益的方式制造铁锰硅形状记忆合金具有重要意义。
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Improving shape memory effect in Fe-Mn-Si-based alloys by reducing annealing twin boundaries through trace boron doping
Previous work has shown that the shape memory effect (SME) exhibited a strong negative dependence on the density of annealing twin boundaries (ATBs) in Fe-Mn-Si-based alloys. Reducing the density of ATBs has thus been an effective way to improve the SME of Fe-Mn-Si-based alloys. This study investigated the effects of trace B doping on the density of ATBs and the resultant SME in solution-treated Fe-Mn-Si-based alloys. Results indicated that doping 89 ppm B effectively reduced the density of ATBs in the solution-treated Fe-Mn-Si-based alloy. Consequently, its SME was remarkably improved. The maximum shape recovery strain reached 2.7 % in the B-doped alloy, 1.3 % higher than in the alloy without B doping. This work demonstrates a new avenue to improve the SME by doping trace B, which is of significance for the fabrication of Fe-Mn-Si-based shape memory alloys in a more cost-effective manner.
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来源期刊
Intermetallics
Intermetallics 工程技术-材料科学:综合
CiteScore
7.80
自引率
9.10%
发文量
291
审稿时长
37 days
期刊介绍: This journal is a platform for publishing innovative research and overviews for advancing our understanding of the structure, property, and functionality of complex metallic alloys, including intermetallics, metallic glasses, and high entropy alloys. The journal reports the science and engineering of metallic materials in the following aspects: Theories and experiments which address the relationship between property and structure in all length scales. Physical modeling and numerical simulations which provide a comprehensive understanding of experimental observations. Stimulated methodologies to characterize the structure and chemistry of materials that correlate the properties. Technological applications resulting from the understanding of property-structure relationship in materials. Novel and cutting-edge results warranting rapid communication. The journal also publishes special issues on selected topics and overviews by invitation only.
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