2002
DOI: 10.1016/s1359-6454(02)00078-2
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Grain growth in anisotropic systems: comparison of effects of energy and mobility

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Cited by 171 publications
(95 citation statements)
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“…Peaks in anisotropic distributions commonly reach values of 5 to 10 MRD and, even in a relatively isotropic material (Al), peaks in excess of 3 MRD are commonly observed [3]. Furthermore, based on the results of experiments [4,5] and computer simulations in two and three dimensions [6][7][8][9][10], the GBCD is inversely correlated to the grain boundary energy. The only available comprehensive experimental data indicates that the logarithm of the population is approximately linear with the energy, which is consistent with the results of a three-dimensional computer simulation [6,10,11].…”
Section: Introductionmentioning
confidence: 99%
“…Peaks in anisotropic distributions commonly reach values of 5 to 10 MRD and, even in a relatively isotropic material (Al), peaks in excess of 3 MRD are commonly observed [3]. Furthermore, based on the results of experiments [4,5] and computer simulations in two and three dimensions [6][7][8][9][10], the GBCD is inversely correlated to the grain boundary energy. The only available comprehensive experimental data indicates that the logarithm of the population is approximately linear with the energy, which is consistent with the results of a three-dimensional computer simulation [6,10,11].…”
Section: Introductionmentioning
confidence: 99%
“…The exact mechanisms underpinning the occurrence of AGG are still unclear and remain a subject of much interest and research. Though debate on specific mechanisms exists, most authors agree that the formation of AGG is related to low-energy, high-mobility grain boundaries such as ∑3 and its variants (e.g., ∑9 and ∑27) [8][9][10][11][12][13][14][15][16]. This is of note as Grain Boundary Engineering (GBE) is a specific type of thermomechanical process used to improve material properties by altering their grain boundary network and often resulting in increased frequency of ∑3 boundaries [17,18].…”
Section: Introductionmentioning
confidence: 99%
“…Recently, computer simulation becomes indispensable in exploring the details of grain growth and validating the analytical models. Simulation models for this purpose include the Potts model, [4][5][6][7][8][9] the vertex model, [10][11][12][13][14] the phase field model 1,[15][16][17][18][19][20] and others. Though the Potts model has advantages in the simplicity of switching rules, it is still not intuitive to scale the Monte Carlo time to the physical time.…”
Section: Introductionmentioning
confidence: 99%