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We aim to study grain boundary diffusion in tin by atomistic simulation.
Simulation of Sn Grain Boundary Diffusion.
Simulation models of Sn grain boundaries.
Grain boundary plane Tilt axis Cell size (a=5.95Å) Number of atoms (101) [010] 6.00a x 5.70a x 15.1a 3720 (201) [010] 6.00a x 5.89a x 14.8a 3840 (210) [001] 6.71a x 5.40a x 14.8a 4020 (310) [001] 6.32a x 5.40a x 14.8a 3720 Figure 2.
The MD simulations using the potential show that the effect of stress on Sn grain boundary diffusion depends on the type of grain boundaries.

The deterioration of the tolerance characteristics of electrical degradation by the addition of Y was probably caused by an increase in the number of willemite (Zn2SiO4)-type particles or a decrease in the number of spinel (Zn2.33Sb0.67O4)-type particles, but this deterioration was reduced by adding Zr.
Moreover, the reduction in the average ZnO grain size due to the addition of Y was a major factor in the increased varistor voltage, and the ZnO grain growth was inhibited by the formation of an unknown compound after adding Y.
fluencing the increase in varistor voltage was the decreased average ZnO grain size.
Although the cause of the increase in the number of willemite-type particles with increasing Y is currently unclear, it is likely that the increase in the number of spinel-type particles or decrease in the number of willemite-type particles deteriorates the tolerance characteristics of the electrical degradation.
The decrease in ZnO grain size caused an increase in the total surface area of the ZnO grains.

Rotating bending fatigue tests were carried out for maraging steels with different grain size in moist air in order to investigate the effects of humidity, grain size and reversion austenite on fatigue strength of the steel.
Fatigue strength was decreased by humidity, and the decrease in fatigue strength was large in larger grain sized steel.
The mean grain sizes were about 21µm, 40µm and 105µm.
The decrease in fatigue strength is large with increase in grain size.
The decrease was marked in larger grain size and caused by the acceleration of crack initiation and its propagation.

When the number of RPW cycle increased, the size of the Mg2Si particles decreased, and the grain size of the matrix alloy reached the minimum when 200 RPW cycles was used.
it shows that several different Mg2Si grains grew together and formed a cluster-like Mg2Si particles, and the interface between different Mg2Si grains was clearly observed, the SADPs of the A, B, C grains in Figure 5 (a) are shown in Figure 4(b), (c) and (d) respectively , according to these SADPS, we can conclude that the A, B, C grains are Mg2Si.
However, the grain size of the matrix alloy increased when the number of RPW cycles increased, according to Hall-Petch relationship, the increase in grain size will reduce the mechanical properties.
Therefore, taking the above factors, the Mg2Si/Mg-5Zn-2.5Er composite materials reached the optimum properties when the number of RPW cycle was 200.
(2) RPW deformation technique can be used to effectively refine the grain size of the Mg2Si particle and magnesium matrix alloy, when the number of RPW cycles increased, the size of the Mg2Si particle decreased, and the grain size of the matrix alloy reached the minimum when 200 RPW cycles was used

Different ORs exist between the γ-fcc and the α'-bcc crystal lattices and each OR determines the maximum number of the possible α' variants inherited from a parent grain.
However, when the number of variants Viα' available per parent grain is too small, more than one potential parent can be derived from all considered variants.
The γ orientations of the resulting cells (the γ grains) were randomly tossed.
The number of these variants was variable.
One limit for the reconstruction is the number of differently oriented variants available per parent grain.

Homogenization annealing before cold rolling will lead the initial fine grains become to be larger, even abnormal grain growth takes place during that course.
All the grains are fine in uniform grain size of ~20 μm.
The abnormal grains are ~10 times of fine grains as pointed out in the red line regions in Fig. 2(a).
A lemon-shape abnormal grain is shown in the red circle region surrounded by a large number of fine grains, and it could cause inhomogeneous deformation at the region around that abnormal grain.
Therefore, it can be concluded that, grains with uniform size can make deformation homogeneous, no matter the grains are fine or coarse.

Moreover, it appears that significant grain refinement was achieved after 2 complete revolutions and thereafter the microstructures do not really vary after additional numbers of turns.
The average grain size and the fraction of high-angle grain boundaries (HAGB) are plotted in Fig. 2 as a function of the number of HPT turns.
(d) (c) (b) (a) Fig.1: EBSD images of AlMgSi alloy after HPT deformation for (a) 1, (b) 2, (c) 4 and (d) 5 turns Fig.2: Average grain size and the fraction of HAGB versus number of turns.
The evolution of torsion texture versus number of turns can be interpreted with the aid of the key given Fig. 3 (f) which shows the positions of the texture components.
The microstructures after HPT revealed considerable grain refinement characterized by the formation of submicrometer grains of about 500 nm and a high fraction of high-angle grain boundaries. 3.

Increase in amplitude dependent damping in ultrafine-grained copper is due to dislocation but not grain boundary contribution.
There is a set of non-equivalent energy positions for atoms and grain boundary dislocations in grain boundaries, which results in the existence of a relaxation times spectrum.
Grain size is also indicated for several temperatures in Fig. 3b.
The analysis of IF experimental data [8] gives value k = 1.3, which is close to k = 1.14, obtained in [4], and suggests growth of new grains on the GB of deformed grains.
At ε0 > 2.5×10-4 values of IF depend on number of cycling, see arrow from n.1 to n.7 cycle.

First, all annealed samples exhibited abnormal grain growth, which was manifested by the presence of large grains that were surrounded by regions of small grains (bimodal grain distributions).
(e) 250nm (a) 250nm (c) T T T 250nm (b) T T T 250nm (d) T T T In order to determine the average grain sizes and grain size distribution, a number of representative TEM micrographs were evaluated using a linear intercept method [10].
To ensure accurate and statistically meaningful counting of the number of intersections of a random line with the grain boundaries, a specially designed system for data acquisition and analysis was used.
The average grain sizes were estimated from 250 grains.
For example, samples annealed for 5h have grains with sizes of about 60 nm and 100 nm while for those annealed for 24h have a large number of grains with sizes larger than 100 nm.

Shows the samples with different content of sintering adds Sample number Additive types and content Sample1 Sample2 Sample3 No additive 0.5wt% SiO2 0.5wt% SiO2 and 0.5wt%MgO Optical transmittance spectra.
The grain boundaries were clean, and the average grain size was about 30μm.
Sample number Additive types and content Sample4 Sample5 Sample6 0.3wt% MgO 0.5wt% MgO 1.0wt% MgO Action mechanism of MgO.
The redundant MgO has a pinning effect on the grain boundaries so as to decrease the grain size.
The grain size decreased with the increasing MgO.