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The material subjected to forward/forward deformation did, however, have a slightly greater number of low angle boundaries, i.e. boundaries < 15° misorientation, whilst the forward/reverse material had some grains containing little evidence of substructure.
On annealing both materials had significantly reduced levels of low angle boundaries but only the forward/forward material had an increased number of high angle boundaries and a reduced grain size, indicating recrystallisation had only occurred in this material.
For the F/F material all grains have a significant substructure, whereas for the F/R reverse material there appears to a more bimodal distribution of grains with some having high levels of substructure and other grains having virtually no substructure.
Grain sizes for material as-deformed and annealed for 1 hour at 400°C Test Deformed grain size (µm) Annealed grain size (µm) 0.25F/0.25F 42 28 0.25F/0.25R 60 62 conditions the number of low angle boundaries is quite similar with there being at most 10% more boundaries for the F/F case.
For both the F/F and F/R cases there is significant substructures developed but there is a slightly reduced number of low angle boundaries for the F/R as well as some grains with little or no substructure This in turn has a dramatic influence on recrystallisation response with no evidence of recrystallisation in the F/R material whereas the F/F is completely recrystallised.

Upon extrusion, the as-cast coarse grains underwent pronounced grain refinement and the second phases were broken up and formed stringers in the extrusion direction.
The grain size was measured using the software of Image-Pro Plus 5.0 with the grain number of more than 1000.
The average grain size of dynamic recrystallized (DRXed) grain for the Mg alloy extruded at 270 ºC, 300 ºC and 330 ºC was about 1.47, 2.50 and 4.46 μm, respectively.
Fig. 2 IPF figures of the Mg-Zn-Ca alloy extruded at (a) 270 ºC, (b) 300 ºC, (c) 330 ºC It has been reported that high extrusion temperature result in large nucleation and migration rate of grain boundaries [5], a higher nucleation rate during extrusion process will increase the fraction of DRXed grains, and the higher migration rate of grain boundaries can lead to a rapid grain growth during extrusion, which is responsible for the large grain size at 330 ºC.
Fig. 4 Pole figures of the Mg-Zn-Ca alloy extruded at (a) 270 ºC, (b) 300 ºC, (a) 330 ºC ED (b) (c) (a) (0001) (10-10) (a) 0.0 0.1 0.2 0.3 0.4 0.5 0.00 0.02 0.04 0.06 0.08 0.10 0.12 Number fraction Schmid factor m=0.2057 0.1 0.2 0.3 0.4 0.5 0.00 0.02 0.04 0.06 0.08 0.10 0.12 Number fraction Schmid factor m=0.2384 0.0 0.1 0.2 0.3 0.4 0.5 0.00 0.02 0.04 0.06 0.08 0.10 0.12 Number fraction Schmid factor m=0.2386 (c) (b) The tensile properties of the Mg alloys were strongly dependent on their microstructure including grain size, texture, second phase, etc.

They are numbered from #1 to #8 for further processing.
Crystal grain short-circuit grain boundary ITO film’s pattern The ITO film is composed of a number of grains in different sizes, and there are grain boundaries among them [2-11].
Thus, some electrons that are obstructed by grain boundary and can only move within one grain in ITO film are able to flow into another grain through the bridge.
For the ITO film with lower sheet resistance, the number of ∆ is small in unit length, the number of ∆ that it is short-circuited by the grains of second layer is small, and so the effect of conduction modulation is not remarkable.
Conclusion It can be known from above analysis that the film is composed of a number of grains, for many materials, scattering effect of a number of barriers ∆ is very remarkable on carriers, thus, the film is changed into insulators.

The number of simultaneous cutting edges.
The square endmill used experiment is 8-flute with a diameter of φ6mm (MOLDINO ES8WB0600LN), with the 38degrees Helix angle, TiAlN coating and made of ultrafine grain cemented carbide.
Next, the effect of number of endmill flutes is examined with the constant number of simultaneous cutting edges.
All were in the same condition: φ6mm square end mills, Helix angle 38degrees, TiAlN coating and made of ultra-fine grain cemented carbide.
Secondly, while keeping the number of simultaneous cutting edges, the number of flutes in endmills was changed to examine the number of flutes with the best accuracy.

There are many studies on the formation of sub grain and fine grain size to less than 1 µm (ultra fine grain) which explain the formation of fine grain.
The shear band are clearer and most dense at higher number of ECAP passed, see in Figure 1 (d) and (e).
According to reference [1, 2] this phenomenon is due to which dislocations which is increased with increasing number of pass (Fig. 2 (b) and (e)).
Heat up temperature take the same visible difference in the growth of the grain size after ECAP with different number of pass.
For a larger number of pass, the deformation energy received by metal increase so the heat energy will produce more recrystallization [1, 2].

Then by the same FESEM, the surface morphology was studied to see the grain size and the porosity of each film based on the number of coatings.
There is difference in the grain size of each deposition times as each has bigger grain size which increase with the deposition times.
When the grain size increase, it is hard for the current to flow.
Smaller grain size will increase the current flow between the grains and so increase in the I-V.
Summary The thickness of TiO2 increase due to the number of deposition times and this is also due to the grain size of each deposition time which also increases with the number of coatings.

Properties like grain volume and porosity are useful in design and development of grain storage units.
Abbreviations used L Length of the grain, mm V Grain volume, mm3 W Width of the grain, mm S Grain surface area, mm2 T Thickness of the grain, mm Ra Aspect ratio of grain Dp Equivalent diameter of a spheroid having same volume as that of grain, mm Bulk density, g/cc Sphericity of grain True density, g/cc Porosity, % θ Angle of repose α Angle of friction umf Minimum fluidization velocity, m/s Materials and Methods The present investigation based on engineering properties of paddy which is mainly grown in the coastal climate of Odisha, India.
Figure 1 (Moisture measurement by handy data logging moisture meter) Physical Properties After randomly selecting number of paddy grains, their principal dimensions like length, width and thickness are measured with the help a digital venire calliper.
Paddy grains are longitudinal with two pointed ends.
This implied that grains are heavier than water.

This statistical cut off was set to be one plus the average number of different slip systems active in all grains.
The matrix grains with the highest stored energy are associated with the highest number of nuclei.
We assumed the total number of nuclei Ntot as tot rand GB stab trans N N N N N = + + +
Then the ratio of Fstab to Ftrans was related to the absolute numbers of stable grains nstab and grains with transition bands ntrans, which were derived with the nucleation spectra models described above.
For a use in a space resolved growth model like a cellular automaton absolute numbers have to be predicted.

Fig. 3 - Distribution of number of pixels in Fig. 4 - Pattern quality averaged in bcc grains bcc and fcc grains as a function of square root of number of pixels in each grain.
Figure 3 shows the distribution of number of pixels in bcc and fcc grains.
In case of bcc, number of small grains composed of less than 10 pixels is large enough to show the highest portion.
The distribution of bcc grains shows a long tail toward large number of pixels, which reflects the large polygonal ferrite grains.
Square root value of number of pixels in a grain that is proportional to grain size is used.

The mathematical model of grain drying plays an essential role in developing grain dryer structure and obtaining the drying technological parameters.
It is very important to establish an accurate mathematical model for predict the grain germination rate and moisture content in the grain drying process.
The achievement is using real-time measured data from sensors to provide a large number of measured data for the simulation system, and adjusting the prediction for the further production process.
Complexity analysis and process control for grain drying[D].
A model-predictive controller for grain drying[J].