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分步退火及初始晶粒对Hastelloy C-276合金晶界特征分布影响

Effects of Two-Step Annealing and Initial Grain Size on the Grain Boundary Character Distributions of Hastelloy C-276
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摘要 不同初始晶粒尺寸的Hastelloy C-276合金经冷轧变形后,分别采用一次退火和二次退火方法进行热处理,其晶界特征分布采用电子背散射衍射技术进行表征.结果表明,初始较大晶粒组织有利于晶界特征分布的优化,特殊晶界比例比小尺寸晶粒组织提高了近10%,达到了78.8%,同时形成了平均尺寸为200μm晶粒团簇组织.在相同晶粒尺寸条件下,采用二次退火工艺可以明显改善合金的晶界特征分布,∑3n晶界比例得到较大幅度的提高,并形成了良好的团簇组织.这是由于较多的非共格∑3晶界,容易产生∑9和∑27晶界,从而形成更多的三叉晶界,阻断了大角度晶界的连通性. Hastelloy C-276 samples with different initial grain sizes were subjected to one-step and two-step annealing heat treatments after cold-rolling process and their grain boundary character distributions( GBCDs) were characterized by electron backscatter diffraction( EBSD) techniques. The results showthat the large-sized initial grains tend to optimize the GBCD. Compared with that in the small-sized grain ones,the fraction of coincident site lattice( CSL) boundary in Hastelloy C-276 samples with large-sized initial grains increases nearly 10%,which is up to 78. 8%. Meanwhile,the clusters with average size of 200 μm are formed. For the samples with same-sized grains,the GBCD can be well improved by the two-step annealing treatment,where the fraction of ∑3 nboundaries can be increased significantly and the better clusters can be formed. The more incoherent ∑3 boundaries,the more ∑9 and ∑27 boundaries can be generated,leading to the more triple junctions. Therefore,the connectivity of the high-angle grain boundary network is disrupted effectively.
作者 张晓宇 赵宪明 李德富 郭胜利 ZHANG Xiao-yu;ZHAO Xian-ming;LI De-fu;GUO Sheng-H(State Key Laboratory of Rolling and Automation,Northeastern University,Shenyang 110819, China;Center for Composites, General Research Institute for Non-ferrous Metals, Beijing 100088, China.)
出处 《东北大学学报(自然科学版)》 EI CAS CSCD 北大核心 2018年第5期630-632,648,共4页 Journal of Northeastern University(Natural Science)
基金 国家自然科学基金资助项目(51205028)
关键词 二次退火热处理 初始晶粒 HASTELLOY C-276合金 特殊晶界 晶界特征分布 two-step annealing heat- treatment initial grain size Hastelloy C-276 alloy special grain boundary grain boundary character distribution(GBCD)
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