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By applying a grain refining technology by means of TMCP to this composition, it will be possible to obtain massive products with an extremely fine structure or nano-crystalline structure through the rolling process.
In Photo. 1 with low magnification, ǩ-grains with the size of about 1 Ǵm (Al particles) and Ǫ-grains (Zn particles) exist together.
Photo. 2 with high magnification shows Ǫ-grains, the size of which was verified to be about 30 nm.
Ǫ-grains are nano-crystalline as predicted theoretically. 0 20 40 60 80 100 Al Zn mass% Liq.
ǭtotal = (4n – 3)ǭ (1) where n is the number of accumulation, andǭis the strain amplitude (r0.1 %). 3.

D=K λ / β cosθ (2) Where D is the size of crystal grain, K is dimensionless constant (0.9), θ is the X-ray diffraction angle, λ is wavelength of X-ray radiation, and β is the full width at half maximum (FWHM) of diffraction peak.
The crystal grain size of TiO2 bulk and carbon-doped TiO2 calculated by Scherrer equation are given in the following Table 1.
This shows that doping concentration up to certain value effectively inhibits TiO2 grain growth probably by staying at grain boundaries thereby decreasing the crystallite size and increasing the surface area [41].
It was estimated that the average grain size of the doped TiO2 lies between 7-12 nm, which is approximately in accord with the XRD results.
But further increase in amount of carbon as dopant decreases the photocatalytic activity due to the fact that the recombination rate of the charge carriers increases exponentially with the dopant concentration as the average distance between the trap sites decreases with increasing the number of dopants confined within a particle.

The XRD spectrum from 100C6/Ti sample before thermal treatment, figure 1, shows that in addition to iron and Fe3C, the appearance of peaks of characteristic of titanium with a reduction in the number and intensity of the substrate peaks.
The XRD spectra from samples treated at the temperature interval of 400 to 1000°C for one hour, show a progressive reduction in intensities and number of titanium peaks and substrate phases, and on the other hand, a progressive increase in intensities and number of the titanium carbide (TiC) reflections.
It results in a consumption of the titanium layer and the increase of TiC peaks in number and intensity with annealing temperature.
This may indicate that these films have an open structure with voids along the grain boundaries.

The grain size is about 10 μ{TTP}956 m.
(a) (b) Fig 3: Reflectivity curves of samples number 1 to 8 Figure 3(a) shows the results from holding the carbonyl iron powder content constant at 20%wt in the surface layer, while varying the graphite powder content in bottom layer.
The reflectivities of samples number 1 to 4 are shown.
The reflectivity measured from samples number 5 to 8 with their absorption bandwidth and their absorption peaks can be seen in Table 2.
Sample number 7 has the best absorbing performance; at 17.1 GHz it displays an absorption peak of 15.94 dB, with an effective bandwidth of about 5.7 GHz.

The model of the workpiece meshing type is tetrahedral and grid units number are 45803, the number of nodes are 10349.
Analog initial step is set -1, the interval step number of the definition database is stored as 25.
Materials performance and drive parameters Materials and nature Material AISI 1008 Poisson's ratio 0.3 Young's modulus 210Gpa Yield stress 218Mpa Crack threshold 0.45 Fracture unit 4 Driving condition parameters Active mold die top die Top die movement direction -Y Lid movement rate 15mm/sec Analog total number of steps 300 Store database 25 Analog step 0.019mm Shear friction factor 0.12 Simulation analysis Plastic flow velocity vector analysis.Figure 2 is a velocity vectors shown in the top die from the load beginning in step 173, the loading process, and before the end of the load in step 207 interception analysis.
When the pressure reaches a critical value of the plastic flow instability, the material will produce the grain boundary cracks, breakage, shear start.

Near infrared refers to the electromagnetic waves, which between visible wavelength area and mid-ir area, its wavelength is about for 780 ~ 2500nm, wave number range is about 12500cm-1～4000cm-1.
After being aged determining the seed germination rate: Placing soybean seed samples in petri dishes, each dish 50 grain.
Within this range, comparing the misjudgment numbers.
Fig.3 shows, the misjudgment numbers of Standard normalized (NORMALIZE) is obviously less than others'.
Fig.3 The relationship between misclassifications and principal components in calibration set with four preprocessing methods 2.2 Correction and Forecasting Result Analysis In a model calibration process, the number of principal components is the main factor for establishing model.

Definition 2: Function hierarchy matrix is upper triangular matrix, is the total nodes of function tree, diagonal element is the serial number of function (can be character type), non-diagonal element is 0 or 1, presume i, j is the node of the function tree, connect the line of i and j.
Different industry can give out its function unit table that fit with its demand based on its prosperity, and classify number its function unit, at the same time, construct its corresponding meta-module table, the relationship between function unit and meta-module table in this paper see in figure 4.
This paper analyzed the product’s function for mature products, used function hierarchy matrix and function incidence matrix to express function and its relationship that is beneficial to realize computer programming, established function unit table as a basis for the grain size of function decomposition that is avoid too thick or meticulous.
This paper also discussed the corresponding relationship between the structure of function unit table and meta-module table, the mapping relationship between the decomposition results of combine function and “function--structure”, lay the foundation for mature product’s modularization Acknowledgments This work was supported by the open foundation of Huaian Research Institute of Hohai University, the national natural science foundation of China under Grant number 51175146 and the Fundamental Research Funds for the Central Universities under grant number 2012B14014.

In particular, plate shaped particles are very common, and in these cases the microstructural parameters (particle size, number density, volume fraction etc.) that are most important to control for strengthening are not obvious.
For each aging duration, the average θ' precipitate plate length (L), thickness (th) and number density (N) was measured from micrographs taken with the electron beam oriented parallel to the [001]α zone axis of the Al matrix.
v θ' α soft impingement solute depleted zone {100} plane (i) (ii) (iii) Fig. 2 Evolution with ageing time of the yield strength (σy), the precipitate number density (N), length (L), thickness (th) and volume fraction (Vf).
To calculate the yield strength, the contributions of the matrix and the grain boundaries GROWTH COARSENING GROWTH COARSENING GROWTH COARSENING N L Vf σy th θ' θ' {111} α Slip plane λ (σ0) as well as from the solutional solute (σSS) must also be considered.
This is very different to the case of spherical particles where the size, number density and volume fraction of particles are the key microstructural parameters.

Mean field theory made in terms of several surface integrals is also used to coarse grain the molecular interactions between molecules resulting in rapid computational speed.
The cavity of graphene sheet comprises both the bulk and absorption regimes, from which the usual van der Waal equation could be used to deduce the number density of CO2 in the bulk regime while the multi-scale technique has to be incorporated into the modified van der Waals equation to take into account the interactions between molecules.
Theory Here, double layered graphene sheets are considered and we assume the carbon atoms are smeared across the surface of graphene so that mean field theory could be used to approximate the pairwise interactions between CO2 and the host structure, which is given by Eh=ηπ-A21h4+1S-h4+B51h10+1S-h10, (1) where η, A, B, S and h denote the number density of carbon atoms on graphene, the attractive constant, the repulsive constant, the separation between two graphenes and the height S ≥ h ≥ 0, respectively.
The total number density of CO2 in the system is therefore n=nad+nbulk.
However, the number density given by Eq. (3) suffers from singularities when the temperature T becomes zero or the external pressure P becomes infinity, which is physically infeasible.

It results a large number of cracking products (Fig. 1), which significantly reduces qualified rate.In the paper, samples prepared by different melting temperature and holding time were analyzed by SEM and XRF.
Table1 Preparation Processs of Cu-Bi master alloy Sample number Melt temperature/℃ Holding time/s 1# 1100 120 2# 1150 120 3# 1200 120 4# 1150 60 5# 1150 180 6# 1150 120 7# 1150 120 Results and Discussion Phase and Microstructure.
The figure shows that there is a white phase, which is proved to be bismuth by EDS analysis(shown in Fig.3(b)), existing on the grain boundary, and it distributes uniform comparatively.
Acknowledgments The authors would like to acknowledge the financial support of the National Natural Science Foundation of China under granted number 50974063 and Institute of Research and Engineering Innovation and Technology Fund under granted number JUST.GCY-2010-03.