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Quantification of grain boundary connectivity for predicting intergranular corrosion resistance in BFe10-1-1 copper–nickel alloy

  • Yinghui Zhang (a1), Xingyu Feng (a1), Chunmei Song (a1), Hang Wang (a2), Bin Yang (a2) and Zhigang Wang (a1)...


We investigated the connectivity of high-energy random grain boundaries through fractal analyses of specimens with different grain boundary (GB) microstructures in BFe10-1-1 copper–nickel alloy. It was found that the profile of maximum random boundary network possesses a fractal nature and more than one fractal dimension can exist. The fraction of special boundaries and grain size homogeneity can play an important role on GB character distribution. Here, GB microstructures are combined with quantitative materials structure–property relationship models to predict intergranular corrosion properties. The experimental results are accurately consistent with the theoretical predictions.


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Address all correspondence to Xingyu Feng at and Zhigang Wang at


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1.Bechtle, S., Kumar, M., Somerday, B.P., Launey, M.E., and Ritchie, R.O.: Grain-boundary engineering markedly reduces susceptibility to intergranular hydrogen embrittlement in metallic materials. Acta Mater. 57, 4148 (2009).
2.Tokita, S., Kokawa, H., Sato, Y.S., and Fujii, H.T.: In situ EBSD observation of grain boundary character distribution evolution during thermomechanical process used for grain boundary engineering of 304 austenitic stainless steel. Mater. Charact. 100, 365 (2017).
3.Kumar, B. S., Prasad, B.S., Kain, V., and Reddy, J.: Methods for making alloy 600resistant to sensitization and intergranular corrosion. Corros. Sci. 70, 55 (2013).
4.Burleigh, T.D. and Waldeck, D.H.: Effect of alloying on the resistance of Cu-10% Ni alloys to seawater impingement. Corrosion 55, 800 (1999).
5.Hu, C., Xia, S., Li, H., Liu, T., Zhou, B., Chen, W., and Wang, N.: Improving the intergranular corrosion resistance of 304 stainless steel by grain boundary network control. Corros. Sci. 53, 1880 (2011).
6.Watanabe, T.: An approach to grain boundary design for strong and ductile polycrystals. Res. Mech. 11, 47 (1984).
7.Chen, A.Y., Hu, W.F., Wang, D., Zhu, Y.K., Wang, P., Yang, J.H., Wang, X.Y., Gu, J.F., and Lu, J.: Improving the intergranular corrosion resistance of austenitic stainless steel by high density twinned structure. Scr. Mater. 130, 264 (2017).
8.Deepak, K., Mandal, S., Athreya, C.N., Kim, D-IK, de Boer, B., and Subramanya Sarma, V.: Implication of grain boundary engineering on high temperature hot corrosion of alloy 617. Corros. Sci. 106, 293 (2016).
9.Michiuchi, M., Kokawa, H., Wang, Z.J., Sato, Y.S., and Sakai, K.: Twin-induced grainboundary engineering for 316 austenitic stainless steel. Acta Mater. 54, 5179 (2006).
10.Drach, A., Tsukrov, I., DeCew, J., Aufrecht, J., Grohbauer, A., and Hofmann, U.: Field studies of corrosion behaviour of copper alloys in natural seawater. Corros. Sci. 76, 453 (2013).
11.Ma, A.L., Jiang, S.L., Zheng, Y.G., and Ke, W.: Corrosion product film formed on the 90/10 copper-nickel tube in natural seawater: composition/structure and formation mechanism. Corros. Sci. 91, 245 (2015).
12.Ekerenam, O.O., Ma, A., Zheng, Y., and Emori, W.: Electrochemical behavior of three 90Cu-10Ni tubes from different manufacturers after immersion in 3.5% NaCl solution. J. Mater. Eng. Perform. 26, 1701 (2017).
13.Randle, V.: “Special” boundaries and grain boundary plane engineering. Scr. Mater. 54, 1011 (2006).
14.Gottstein, G. and Shvindlerman, L.S.: Grain boundary junction engineering. Scr. Mater. 54, 1065 (2006).
15.Kobayashi, S., Maruyama, T., Tsurekawa, S., and Watanabe, T.: Grain boundary engineering based on fractal analysis for control of segregation-induced intergranular brittle fracture in polycrystalline nickel. Acta Mater. 60, 6200 (2012).
16.Kobayashi, S., Kobayashi, R., and Watanabe, T.: Control of grain boundary connectivity based on fractal analysis for improvement of intergranular corrosion resistance in SUS316L austenitic stainless steel. Acta Mater. 102, 397 (2016).
17.Brandon, D.G.: The structure of high-angle grain boundaries. Acta Metall. 14, 1479 (1966).
18.Watanabe, T. and Grain boundary engineering: Historical perspective and future prospects. J. Mater. Sci. 46, 4095 (2011).
19.Fortier, P., Miller, W.A., and Aust, K.T.: Effects of symmetry, texture and topology on triple junction character distribution in polycrystalline materials. Acta Metall. Mater. 43, 339 (1995).
20.Mandelbrot, B.B., Passoja, D.E., and Paullay, A.J.: Fractal character of fracture surfaces of metals. Nature 308, 721 (1984).
21.Kobayashi, S., Tsurekawa, S., and Watanabe, T.: A new approach to grain boundary engineering for nanocrystalline materials. Beilstein J. Nanotechnol. 7, 1829 (2016).
22.Dubuc, B., Quiniou, J.F., Roques-Carmes, C., Tricot, C., and Zucker, S.W.: Evaluating the fractal dimension of profiles. Phys. Rev. A 39, 1500 (1989).
23.Charkaluk, E., Bigerelle, M., and Iost, A.: Fractals and fracture. Eng. Fract. Mech. 61, 119 (1998).
24.Bober, D.B., Lind, J., Mulay, R.P., Rupert, T.J., and Kumar, M.: The formation and characterization of large twin related domains. Acta Mater. 129, 500 (2017).
25.Schuh, C.A., Minich, R.W., and Kumar, M.: Connectivity and percolation in simulated grain-boundary networks. Philos. Mag. 83, 711 (2003).
26.Cao, F., Wei, J., Dong, J., and Ke, W.: The corrosion inhibition effect of phytic acid on 20SiMn steel in simulated carbonated concrete pore solution. Corros. Sci. 100, 365 (2015).
27.Subramanian, V., Chandramohan, P., Srinivasan, M.P., Velmurugan, S., and Narasimhan, S.V.: Corrosion of cupronickel alloy in permanganate under acidic condition. Corros. Sci. 49, 620 (2007).
28.Randle, V., Hu, Y., and Coleman, M.: Grain boundary reorientation in copper. J. Mater. Sci. 43, 3782 (2008).
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