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EBSD method is effective to measure the orientation relationships since it is easy to calculate localized textures and to obtain the statistical satisfactory analyses with Goss grains populating with significantly low number in the primary recrystallization matrix.
The mean grain diameters and frequencies of these grains were shown in Table 1.
The orientations of over 1000 grains surrounding Goss grains were measured to achieve the statistically satisfactory analysis, as well as {311}<011> grains.
It is supposed that Goss grains grow more preferentially than the other candidate grains due to the highest Σ9 frequency at the commencement of the grain growth.
Σ1 and Σ3 frequencies were higher around {311}<011> grains than Goss grains.

Consequently, the detector is removed as the temperature limiting factor in elevated temperature SEM grain observations.
The Problem Grain growth studies by SEM have particular requirements, specifically the ability to image grain boundaries by SEM.
Unfortunately, this detector is optimised for secondary electron imaging and is therefore unable to give grain orientation contrast.
Grain Orientation Contrast Grain orientation contrast is generated by electron channelling effects and is a naturally weak contrast mechanism.
This proportion, η is the backscattering coefficient and is determined primarily by incoming electron energy and the atomic number of the material (hence atomic number contrast).

Figure 5 distinctly reveal the grain boundaries of AM60 alloy in T4 condition.
With the addition of Mg-Ca master alloy, the number of nuclei and the nucleation rate likely increase.
Average grain sizes of AM60 alloy grain structure of AM60 alloy in T4 condition.
The basic principles of the heterogeneous nucleation theory indicate that the grain size of a cast alloy is directly proportional to the number of nuclei available in the melt which are capable of acting effectively during the solidification process.
The Al2Ca phase segregated around the growing primary magnesium crystals acts as diffusion barriers to the growth of the primary a-Mg grains, which minimizes the size of grains.

The alloy had a grain size of ~80 µm.
For other orientations, recovered grains and (sub)grains could be observed within the original grains (Fig. 2d).
Grain aspect ratio (AR), is close to ~1.1.
The number and the average misorientation of DBs increase with further deformation by ECAE, leading to fragmentation of original coarse grains into different orientation regions and finally to the development of fine equiaxed grains at high strains.
The recrystallized grains replace subgrains evolved over a small number of passes through continuous transformation of their boundaries.

At lower temperatures a number of electrically active twin boundaries increases but the most part of them remains inactive.
A width of these grains is varied from a few to 100 mm.
At liquid nitrogen temperature some additional twin boundaries give the EBIC contrast (Fig. 2b) but the relative number of electrically active twin boundaries still remains rather small.
Σ3 grain boundaries.
At liquid nitrogen temperature a number of electrically active twin boundaries increases but the most part of them still remains inactive.

Diffusion rates are greatly enhanced on grain boundaries (GB).
Introduction Grain boundaries (GB) have excess free volume and energy.
The faster GB diffusion is responsible for changes at the length scale of the grain.
Eq. 4 is used in this work to distribute diffusion coefficients to GB as a function of a random number p.
Gust: Fundamentals of Grain and Interphase Boundary Diffusion (Wiley, Chichester, 1995)

Classification of deformation methods of grain refinement in metallic materials The grain size in the most of as-cast industrial alloys is generally quite large (d>100 µm).
The formation of globular grains with high-angle grain boundaries occurs only in the regions of localized strain due to the preferential occurrence of metadynamic and static recrystallization.
All these factors result in the formation of a mix of high-angle and low-angle grain boundaries and regions of microstructure (colonies) with similar crystallographic orientations of α-grains.
The activation of grain boundary sliding results in an increase of the fraction of high-angle grain boundaries, spreading of crystallographic texture, formation of a very homogeneous equiaxed microstructure with the grain size d=10-15 µm (Figs. 2c and 3b).
The number of steps, temperature differences between them, iT∆ , and the total temperature drop between the first and last steps, ∆Т, number of strain passes on each step depend on the type of material and its initial microstructure.

The microstructure of the upper surface region of S1 consists of fine equiaxed grains and rapidly grown large grains as shown Fig. 3(a).
Journal Title and Volume Number (to be inserted by the publisher) (a) upper surface of S1 (b) center of S1 (c) upper surface of S2 (d) center of S2 Fig. 3 Microstructure of T6 treated bar Crystallographic details.
It can be clearly known that the large grains rapidly grow consuming the fine equiaxed grains during the solution treatment.
The inverse pole figures in Fig. 4 show the crystallographic orientation of fine equiaxed grains and rapidly grown large grains.
These results suggest that grain growth behavior during the heat treatment have some relation with crystallographic orientation of grains.

Results show that an increase in the number of FSP passes considerably enhances the dispersion of the SiC particles in the stir zone and also breaks down the SiC particles.
In this research, the effect of FSP pass number on dispersion level of SiC particles was investigated.
Table 1 shows the grain size variation at the different FSP conditions.
On the other hand, an increase in FSP pass number illuminates the agglomeration of the SiC particles.
Also the higher passes causes the SiC particles to break down which intensifies the pinning effect due to the presence of a higher number of dispersed particles.

Introduction Reasonable simulation and visualization of microstructure evolution during hot deformation can show the distribution and evolution of grains intuitively．It has important theory significance and practical utility prospect for studying microstructure evolution and determining reasonable hot forming process．Because of the complexity of the deformation mechanism，nucleation behavior，interaction between grains and the large number of factors influencing the grain boundary mobility，the simulation on microstructure evolution during hot deformation is very difficult[1, 2] ．
Generation of initial microstructure An initial grain structure is obtained by simulating normal grain growth with modified Monte Carlo method according to the mechanism of grain boundary migration．In the modified Monte Carlo stochastic simulation technique which models grain growth，the complexity of the grain structure is approximated by discretizing the continuum microstructure on a two dimensional，square mesh（site） with periodic boundary conditions．Each site is assigned a random integer between 1 and Q，where Q is the total number of grain orientations introduced in the simulation，representing the orientation of the grain to which it belongs．Neighboring sites with different orientations form grain boundary sites．For each site on the grain boundary，its orientation is changed to one of the nearest neighbor orientations randomly．If the grain boundary energy decreases or maintains unchanged，the new orientation will be accepted．Grain growth occurs as a result of the change in the orientations
The energy can be expressed by the formula： （1） where J is the contribution from each elementary boundary between the analyzed site and its neighbors．In the case of isotropic material，J=1．Si ，Sj are the orientations of the analyzed site i and its neighboring site j，respectively，is the Kronecker delta function （2） The total number of orientations not only ensures the grains with same orientation impinge infrequently，but also ensures the computation time acceptable．The site size needs to ensure the computational efficiency as well as the accuracy．In the present simulation，the initial mean grain size is about 600mm．A 200´300 grid system with a grid spacing of 40mm is used to discrete the region．And the total number of grain orientations Q was taken to be 432．The initial microstructure of Ti-15-3 alloy is shown in Fig. 1．
At the beginning of the simulation，a constant number of nuclei is provided．Thereafter，only the growth of nuclei is admitted during the recrystallization simulation process．Assuming that there is no grain boundary motion between deformed matrix grains，a two dimensional grid system with a grid spacing of 10mm is used to discretize the region．Each site of the grid is considered as a potential nucleus．Firstly，we select sites situated at the boundaries of any deformed grains randomly．If nucleation at the site does not take place and the distance between the site with already recrystallized embryos accords with the recrystallized grain size，the nucleation attempt is considered to be successful．The embryo is given a new orientation randomly，such that no two nuclei have the same orientation．Repeat above procedure till the number of nuclei accords with the recrystallized grain density in the simulating region．
When the nucleation sites situated at the grain boundaries have been covered up with nuclei，the same procedure is performed for nucleation within the deformed grains．In order to make the simulation more time efficient，we select sites within the deformed grains randomly，where the number of nuclei does not satisfy the demand，to carry out the nucleation experiment．