Data compilation on the effect of grain size, temperature, and texture on the strength of a single-phase FCC MnFeNi medium-entropy alloy
Data compilation on the effect of grain size, temperature, and texture on the strength of a single-phase FCC MnFeNi medium-entropy alloy
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DOI：
10.1016/j.dib.2019.104807
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发表时间：
2020-02-01
期刊：
影响因子：
1.2
通讯作者：
Laplanche, G.
中科院分区：
文献类型：
--
作者：
Schneider, M.;Werner, F.;Laplanche, G.
本文介绍了三元单相FCC MnFeNi中熵合金（MEA）的显微组织和力学数据汇编。对于数据与文献值的分析、解释和比较，读者可以参考原始的相关研究文章《温度和织构对MnFeNi中熵合金晶粒和退火孪晶界强化的影响》，参见Schneider etal . （Metals 9, 2019, 84）。这里报告的显微结构数据包括：(i)使用扫描电子显微镜（SEM）获得的九种不同晶粒尺寸的原始背散射电子（BSE）显微照片（tiff文件），每种晶粒尺寸有四张图像；（ii） pdf报告和表格如下所示，展示了晶粒- （d，仅考虑晶界）和晶体（c，同时考虑晶粒和退火孪晶界）尺寸和退火孪晶厚度(t)的分布。这些数据集可能有助于开发用于自动评估再结晶合金显微组织参数的新算法，即利用这些基准数据，可以训练图像分析算法来评估上述显微组织参数。这将有助于加快微观结构的分析，提高其可靠性。描述再结晶组织和织构的其他表格包括每个晶粒退火孪晶界的平均数目(n)和平均泰勒因子(M)。Raeisinia等（模型）。同时。板牙。Sc. 16, 2008, 025001)最近使用了一个粘塑性模型来表明微观结构参数分布的差异会影响Hall-Petch参数，但由于晶粒尺寸分布很少被报道，迄今为止还没有尝试进行实验研究这种可能性。在这里，我们的基准数据（例如晶粒/晶体尺寸分布，每个晶粒的退火孪晶分布，退火孪晶厚度分布）可以用来解决这些问题。本文所报告的力学性能数据是温度范围为77 K至873 K和不同晶粒尺寸的原始应力-应变曲线的excel表格。给出了所有温度下的屈服应力（sigma(0.2%)）和归一化的Hall-Petch参数(sigma(0)/G和k（y)/Gb(2)）。这里报告了归一化的Hall-Petch参数，因为它们可以更好地比较具有相同晶体结构的不同合金的强度和晶界强化幅度，参见Cordero等人。板牙。Rev. 61, 2016, 495-512)。此外，本文报告的Hall-Petch参数和力学数据可用于数据挖掘和用于合金设计的程序中实现。(C) 2019作者。Elsevier Inc.出版。
This data article presents a compilation of microstructural and mechanical data regarding the ternary single-phase FCC MnFeNi medium-entropy alloy (MEA). For the analysis, interpretation, and comparison of the data to literature values, the reader can refer to the original related research article entitled "Effect of Temperature and Texture on Hall-Petch Strengthening by Grain and Annealing Twin Boundaries in the MnFeNi Medium-Entropy Alloy", see Schneider et al. (Metals 9, 2019, 84). The microstructural data reported here include: (i) raw backscatter electron (BSE) micrographs (tif-files) obtained using a scanning electron microscope (SEM) for nine different grain sizes with four images for each grain size and (ii) pdf reports and tables shown below presenting the distributions of the grain- (d, accounting for grain boundaries only) and crystallite(c, which accounts for both grain and annealing twin boundaries) sizes and of the annealing twin thicknesses (t). These datasets may be useful to develop new algorithms for the automated evaluation of microstructural parameters in recrystallized alloys, i.e. with these benchmark data, an algorithm for image analysis could be trained to assess the above mentioned microstructural parameters. This would help to speed up the analysis of microstructures and improve its reliability. Additional tables describing the recrystallized microstructures and texture include the average number of annealing twin boundaries per grain (n), and the average Taylor factors (M). Raeisinia et al. (Model. Simul. Mater. Sc. 16, 2008, 025001) recently used a viscoplastic model to show that differences in the distribution of microstructural parameters affect the Hall-Petch parameters, but no attempt has been carried out so far to experimentally investigate this possibility since grain size distributions are rarely reported. Here, our benchmark data (e.g. distribution in grain/crystallite sizes, annealing twins per grain, distribution of annealing twin thicknesses) could be used to address these issues.The data describing the mechanical properties reported here are excel-sheets of raw stress-strain curves for temperatures ranging from 77 K to 873 K and different grain sizes. The yield stress (sigma(0.2%)) and the normalized Hall-Petch parameters (sigma(0)/G and k(y)/Gb(2)) are given for all temperatures. The normalized Hall-Petch parameters are reported here since they allow to better compare the strength and the magnitude of grain boundary strengthening of different alloys with the same crystallographic structure, see Cordero et al. (Int. Mater. Rev. 61, 2016, 495-512). Moreover, the Hall-Petch parameters as well as the mechanical data reported here could be used for data mining and implemented in programs used for alloy design. (C) 2019 The Author(s). Published by Elsevier Inc.