通过机器学习辅助优化两阶段时效处理提高铜镍硅合金的机械和电气性能

IF 11.2 1区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY Journal of Materials Science & Technology Pub Date : 2024-10-18 DOI:10.1016/j.jmst.2024.09.039
Jinyu Liang, Fan Zhao, Guoliang Xie, Rui Wang, Xiao Liu, Wenli Xue, Xinhua Liu
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引用次数: 0

摘要

最近的研究表明,连续析出物(CPs)和不连续析出物(DPs)的协同析出是同时提高铜镍硅合金强度和导电性的一种可行方法。然而,析出物与两阶段时效过程之间的复杂关系给工艺参数的优化带来了巨大挑战。本研究在正交实验的基础上建立了机器学习模型,以挖掘优先形成 DPs 的 Cu-5.3Ni-1.3Si-0.12Nb 合金的两阶段时效参数与性能之间的关系。然后通过多目标优化结合实验迭代策略,得到了 400 °C/75 min + 400 °C/30 min 的两阶段时效参数,使合金的抗拉强度和电导率分别达到了 875 MPa 和 41.43 %IACS。该合金如此优异的综合性能归功于 DPs 和 CPs 的联合沉淀(总体积分数为 5.4%,CPs 与 DPs 的体积比为 6.7)。这项研究为改善铜-镍-硅合金的综合性能提供了一种新的方法和见解。
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Improving mechanical and electrical properties of Cu-Ni-Si alloy via machine learning assisted optimization of two-stage aging processing
Recent studies have shown that synergistic precipitation of continuous precipitates (CPs) and discontinuous precipitates (DPs) is a promising method to simultaneously improve the strength and electrical conductivity of Cu-Ni-Si alloy. However, the complex relationship between precipitates and two-stage aging process presents a significant challenge for the optimization of process parameters. In this study, machine learning models were established based on orthogonal experiment to mine the relationship between two-stage aging parameters and properties of Cu-5.3Ni-1.3Si-0.12Nb alloy with preferred formation of DPs. Two-stage aging parameters of 400 °C/75 min + 400 °C/30 min were then obtained by multi-objective optimization combined with an experimental iteration strategy, resulting in a tensile strength of 875 MPa and a conductivity of 41.43 %IACS, respectively. Such an excellent comprehensive performance of the alloy is attributed to the combined precipitation of DPs and CPs (with a total volume fraction of 5.4% and a volume ratio of CPs to DPs of 6.7). This study could provide a new approach and insight for improving the comprehensive properties of the Cu-Ni-Si alloys.
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来源期刊
Journal of Materials Science & Technology
Journal of Materials Science & Technology 工程技术-材料科学:综合
CiteScore
20.00
自引率
11.00%
发文量
995
审稿时长
13 days
期刊介绍: Journal of Materials Science & Technology strives to promote global collaboration in the field of materials science and technology. It primarily publishes original research papers, invited review articles, letters, research notes, and summaries of scientific achievements. The journal covers a wide range of materials science and technology topics, including metallic materials, inorganic nonmetallic materials, and composite materials.
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