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The high-entropy alloys break through the traditional alloy structure and present unique and superior mechanical properties. However, the potential deformation mechanism of high-entropy alloy, which is regarded as a new member of alloy families in recent years, needs to be further investigated. In this paper, the mechanical properties of the nano-twin Cr26Mn20Fe20Co20Ni14 high-entropy alloy under tensile loading are studied by molecular dynamics simulation, and the effect of twin boundary on the deformation behavior of nano-twin Cr26Mn20Fe20Co20Ni14 high-entropy alloy is studied on an atomic level. The results show that the yield strength of the nano-twin Cr26Mn20Fe20Co20Ni14 high-entropy alloy increases with twin boundary spacing decreasing, presenting a Hell-Petch relationship. However, there is a critical value of the twin boundary spacing, which makes the sensitivity of the yield strength of the high-entropy alloy to the twin boundary spacing change significantly before and after this value. The results also indicate that the deformation mechanism of nano-twin Cr26Mn20Fe20Co20Ni14 high-entropy alloy changes from dislocation slip to amorphous phase transition with the decrease of twin boundary spacing. The research results of this paper have a certain reference value and guidance significance for designing and preparing high-performance high-entropy alloys.
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图 1 (a) nt-HEA的原子分布图; (b) nt-HEA的模型结构图, 其中绿色区域代表FCC结构, 红色区域代表孪晶界(TB); (c) CrMnFeCoNi HEA与Cr26Mn20Fe20Co20Ni14 HEA的SFE曲线图
Figure 1. (a) Atomic distribution of the nt-HEA; (b) model structure of the nt-HEA, in which the green regions represent the FCC structure and the red regions represent the twin boundary (TB); (c) SFE curves of CrMnFeCoNi HEA and Cr26Mn20Fe20Co20Ni14 HEA.
图 7 孪晶界间距为0.62 nm的nt-HEA的MT相变和DT变形的分析快照图(左侧为CNA分析图, 右侧为DXA分析图), 其中, (a)和(b)的应变为8.6%; (c)和(d)的应变为8.4%; (e)和(f)的应变为12.2%; (g)和(h)的应变为13.5%
Figure 7. Analysis snapshot of MT phase transition and DT deformation of the nt-HEA with the twin boundary spacing of 0.62 nm (CNA analysis diagram on the left and DXA analysis diagram on the right), in which the strains of (a) and (b) are 8.6%; (c) and (d) are 8.4%; (e) and (f) are 12.2%; (g) and (h) are 13.5%.
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[1] Fang Q H, Chen Y, Li J, Jiang C, Liu B, Liu Y, Liaw P K 2019 Int. J. Plast 114 161
Google Scholar
[2] 任县利, 张伟伟, 伍晓勇, 吴璐, 王月霞 2020 69 046102
Google Scholar
Ren X L, Zhang W W, Wu X Y, Wu L, Wang Y X 2020 Acta Phys. Sin 69 046102
Google Scholar
[3] Cantor B, Chang I T H, Knight P, Vincent A J B 2004 Mater. Sci. Eng. A 375 213
Google Scholar
[4] Lu N, Du K, Lu L, Ye H Q 2015 Nat. Commun 6 7648
Google Scholar
[5] Lu K, Lu L, Suresh S 2009 Science 324 349
Google Scholar
[6] 李锐, 刘腾, 陈翔, 陈思聪, 符义红, 刘琳 2018 67 190202
Google Scholar
Li R, Liu T, Chen X, Chen S C, Fu Y H, Liu L 2018 Acta Phys. Sin 67 190202
Google Scholar
[7] Li X Y, Wei Y J, Lu L, Lu K, Gao H J 2010 Nature 464 877
Google Scholar
[8] Huang C, Peng X H, Fu T, Chen X, Xiang H G, Li Q B, Hu N 2017 Mater. Sci. Eng. A 700 609
Google Scholar
[9] 邵宇飞, 孟凡顺, 李久会, 赵星 2019 68 216201
Google Scholar
Shao Y F, Meng F S, Li J H, Zhao X 2019 Acta Phys. Sin 68 216201
Google Scholar
[10] Hsieh K T, Lin Y Y, Lu C H, Yang J R, Liaw P K, Kuo C L 2020 Comput. Mater. Sci 184 109864
Google Scholar
[11] Tian Y Y, Fang Q H, Li J 2020 Nanotechnology 31 465701
Google Scholar
[12] Yan S H, Qin Q H, Zhong Z 2020 Nanotechnology 31 385705
Google Scholar
[13] Gludovatz B, Hohenwarter A, Catoor D, Chang E H, George E P, Ritchie R O 2014 Science 345 1153
Google Scholar
[14] Gao X Z, Lu Y P, Liu J Z, Wang J,Wang T M, Zhao Y H 2019 Materialia 8 100485
Google Scholar
[15] Wang Z, Wang C, Zhao Y L, Hsu Y C, Li C L, Kai J J, Liu C T, Hsueh C H 2020 Int. J. Plast 131 102726
Google Scholar
[16] Hirel P 2015 Comput. Phys. Comm 197 212
Google Scholar
[17] Xiao J W, Deng C 2020 Phys. Rev. Materials 4 043602
Google Scholar
[18] Nosé S 1984 J. Chem. Phys. 81 511
Google Scholar
[19] Choi W M, Jo Y H, Sohn S S, Lee S, Lee B J 2018 NPJ Comput. Mater 4 1
Google Scholar
[20] Korchuganov A V 2019 J. Phys. Conf. Ser 1147 012013
Google Scholar
[21] Hou J L, Li Q, Wu C B, Zheng L M 2019 Materials 12 1010
Google Scholar
[22] Plimpton S 1995 J. Comput. Phys. 117 1
Google Scholar
[23] Stukowski A 2010 Model. Simul. Mater. Sci. Eng 18 015012
Google Scholar
[24] Faken D, Jónsson H 1994 Comput. Mater. Sci. 2 279
Google Scholar
[25] Stukowski A, Bulatov V V, Arsenlis A 2012 Model. Simul. Mater. Sci. Eng 20 085007
Google Scholar
[26] Xiao J W, Deng C 2020 Mater. Sci. Eng. A 793 139853
Google Scholar
[27] Zhao S J, Stocks G M, Zhang Y W 2017 Acta. Mater 134 334
Google Scholar
[28] Wu H A 2004 Comput. Mater. Sci 31 287
Google Scholar
[29] Guo X, Xia Y Z 2011 Acta. Mater 59 2350
Google Scholar
[30] 孙倩, 杨熊博, 高亚军, 赵健伟 2014 物理化学学报 30 2015
Google Scholar
Sun Q, Yang X B, Gao Y J, Zhao J W 2014 Acta Phys. Chim. Sin 30 2015
Google Scholar
[31] Zhao S, Hahn E N, Kad B, Remington B A, Wehrenberg C E, Bringa E M, Meyers M A 2016 Acta. Mater 103 519
Google Scholar
[32] Wu W Q, Ni S, Liu Y, Liu B, Song M 2017 Mater. Charact 127 111
Google Scholar
[33] Zhao S T, Li Z Z, Zhu C Y, Yang W, Zhang Z R, Armstrong D E, Grant P S, Ritchie R O, Meyers M A 2021 Sci. Adv 7 3108
Google Scholar
[34] Chen Z, Jin Z, Gao H 2007 Phys. Rev. B 75 212104
Google Scholar
[35] Hao L H, Liu Q, Fang Y Y, Huang M, Li W, Lu Y, Luo J F, Guan P F, Zhang Z, Wang L H, Han X D 2019 Comput. Mater. Sci 169 109087
Google Scholar
[36] Park H S, Gall K, Zimmerman J A 2005 Phys. Rev. Lett 95 255504
Google Scholar
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