Synergetic Strengthening of Grain Refinement and Texture in Gradient Zircaloy-4 by Surface Mechanical Rolling Treatment
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A Zircaloy-4 rod was subjected to surface mechanical rolling treatment (SMRT) to form a gradient structure, and the evolution of the resulting sub-grain-boundary property and texture across the gradient structure was characterized using electron backscattered diffraction. Dual-gradient structures in grain size and orientation were formed; the grain size was refined from several microns at the center to approximately 400 nm at the topmost surface. Texture analysis revealed that the c-axis gradually tilted from a random orientation toward the parallel-to-radial direction on the radial–tangential plane. The SMRT-induced formation of the dual-gradient microstructure is attributed to the formation of gradient distributions of stress and strain, which resulted in various deformation mechanisms (twinning and dislocation) being active at different depths. During the SMRT process, twinning and dislocations were activated to refine the grains. When the dual-gradient microstructure formed, twinning was mainly activated at the subsurface near the matrix, whereas dislocations were activated across the entire gradient. The geometrically necessary dislocation density increased with decreasing depth and then slightly decreased near the surface. The synergetic strengthening of the dual-gradient microstructure resulted in a gradient distribution of the microhardness near the surface. Thus, the Zircaloy-4 rod exhibited a good combination of strength and ductility.
Keywordsmicrohardness microstructure gradient nanomaterials rolling texture gradient Zircaloy-4
This work was supported by the National Natural Science Foundation of China (Grant Nos. 51471129, 51671158, and 51621063). The authors would also like to thank Dr. X. D. Zhang at the Center for High-Performance Computing, Network Information Center of Xi’an Jiaotong University for assistance with the finite element simulations. The authors also wish to acknowledge the computational resources provided by the HPC platform of Xi’an Jiaotong University. Finally, we thank Tiffany Jain, M.S., from Liwen Bianji, Edanz Group China (www.liwenbianji.cn/ac), for editing the English text of a draft of this manuscript.