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The substructure of a single grain in an electron backscatter diffraction (EBSD) data map is studied, focusing on the influence of the grain boundary configuration on the misorientation to the average grain orientation of data points close to the grain boundary.
These orientation variations were attributed to grain-grain interactions.
and a small number of misorientation boundaries (low mean θptp) or to fragment boundaries having higher misorientations (high mean θptp).
Depending on the orientation of the boundary plane (which can not be characterised by 2D EBSD measurements of plane sections) and the misorientation axis between the crystallites a number of misorientation angles that minimise the surface energy of the boundary can be found.
Sutton and Vitek [6] suggest that the boundary will split up in a number of shorter sections having misorientation angles that are alternately higher and lower than the average misorientation angle.

Because of poor ductility in Mg alloys owing to their limited number of slip systems at ambient temperatures, most SPDs of these alloys are carried out at elevated temperatures.
The rate of grain refinement by MDF is accelerated when the initial grain is finer [7].
This is presumably attributed to the role of grain boundaries in grain refinement.
The former contributes dominantly to grain fragmentation when the grain is coarse, and the latter, when the grain is fine [9].
The grain size was larger than those of MDFed Mg alloys having an initial finer grain.

The grain-boundary between ZnO grains was observed using HR-TEM.
Fabricated MLCVs were thickness of functional layer of 17 µm and the number of 7 grains between internal electrodes of Au, which have V1mA,=5.6 V and capacitance=100 pF.
However, we could not clearly distinguish the grain-boundary layer between ZnO grains from the observation.
The differences of atomic numbers among Zn,Sr and Co in the varistors seem to be relatively small.
The p-type compounds (SrCoO3) detected by EDS would be the layer of grain-boundary between ZnO grains (n-type).

One of these processes reported in a number of experimental works is the paradoxial cementite dissolution [1, 2, 5–9].
The number of anvil rotations by HPT is given for each curve.
The derivative break at 210°C becomes invisible with increasing rotations number.
However, by increasing number of anvil rotations by HPT (i.e. with decreasing grain size), the Fe3C input into Js(T) curve flattened and disappeared (Fig. 4).
Yet, with increasing number of anvil rotations by HPT, the size of the cementite particles decreases drastically.

As a result of the experiments, it was determined that twist extrusion leads to more grain refinement at high temperatures with more number of passes compared to equal channel angular pressing.
Fig. 6, 7 shows the variation of hardness with temperature and number of passes in TE and ECAP process respectively.
As the temperature increases the hardness also increases with increase in number of passes in both the process.
The grains which were bigger in previous passes have become oriented in one direction and narrowed down as thick banding of the grain.
· From the microstructural studies it appears that the grain boundaries are well defined and oriented with more number of passes which leads to grain refinement from 47µm to 38µm.

A number of studies have shown changes in the bead microstructure through the use of shaped laser beams [4,5].
These distributions have been developed following a number of investigations (6-10).
The grain size is large with grains extending from the surface of the bead to the interface.
Although the grains in the Gaussian deposit have the highest aspect ratio it also has the smallest average grain size, Fig 4(b).
The grain size in the HAZs are shown in Fig.4.

Since the grain size has a very important influence on its mechanical properties and corrosion resistance it is significant to study the average grain size of TWIP steel.
The commonly used method of grain size measurement in industry is metallographic method.
The laser ultrasonic nondestructive testing method is composed by a number of disciplines, relevant research has focused on the mechanism of laser ultrasonic [6,7], the characteristics of laser ultrasonic in medium transmission, the method of ultrasonic receiving and laser ultrasonic detection technology, etc.
The larger the average grain size is, the more serious the attenuation is.
Therefore, increasing the number of samples will be benefit to improve the prediction accuracy of the model.

The liquid metal flow speed between different grains was affected by the relative position and morphology between different grains, and also affected by the initial inflow speed of the liquid metal.
The number of grains takes any number smaller than the maximum nucleation number, the maximum nucleation number can be calculated using the formula for nucleation density [12], and the expression is as equation (13), （13） Where ∆Tmax is maximum nucleation undercooling, ∆Tσ is standard deviation undercooling, nmax is the maximum nucleation density.
Numerical Calculation Correspond to the x and y axis (the horizontal direction is x) in coordinate system, the computational grid number of phase field and solute field both are 1200×1200, the grid size is 1 × 10-8m (Δx = 1 × 10-8m ), set the initial nucleus as the ball with the grids number radius R=10.
In Fig.4, the large velocity absolute value area is close to the solid crystal region, and the corresponding abscissa grid number is between 700 and 800.
When the horizontal grid number is above 1100, the absolute value of velocity is gradually reduced to a value close to the initial value.

When changing a position of the sample, different numbers of grains with the same orientation prove to be in the reflecting position, so that the measured intensity of Xray reflection shows significant fluctuations.
ΔA y1 y2 y2 y1 Ω  φ θ A0 number of grains n at the irradiated surface ΔA, whereas the value of intensity I, averaged by all positions of the sample, is proportional to the mean number of grains n, giving an input into the obtained reflection:   sin 0 c zzi a A nI (1)         sin4 4 0 c z zz a AJ nJ nI , where z - the coefficient, taking into account absorption of X-rays depending on the depth of their penetration z; J - the multiplicity factor of the given reflection; Ω =  - the solid angle, depending on the geometry of X-ray measurement and containing normals to planes, giving input into intensity of the diffraction line [2-3]; А0 - the cross-section area of the initial beam; ca - the area of one grain at the surface of sample.
For different positions and orientations of sample the number of grains n within the area ΔA oscillates near the main value n.
As a result of each rotation new grains prove in the reflecting position, so that changes in their orientation and their number result in fluctuations of the registered intensity.
Hence the PF section {111} with  = 55-60° characterizes grains of component <100>, and PF section {200} with  = 55-60° grains of component <111>.

It is widely accepted that the dominant deformation mechanism of fine-grained superplasticity is through grain boundary sliding (GBS) that occurs in fine-grained materials.
An equiaxial fine-grained microstructure with a grain size of 7.4 mm was obtained after FSP; however, this microstructure was unstable at high temperatures.
An equiaxed and fine-grained microstructure with an average grain size of ~7 mm was obtained by applying FSP [9] to this alloy.
The average grain size of SZ was estimated by linear intercept grain size method and was calculated by multiplying the average intercept length by 1.74 [23], which is correction factor [24]; the grain aspect ratio (GAR) was also calculated.
Acknowledgement This work was supported by the JSPS KAKENHI Grant Number JP15K06494, the JST A-STEP FS Stage Project Number 13409342, and the Japan Aluminum Association (JAA) Aluminum Research Grant FY 2010, 2011, 2015, and 2016.