Search results

The microstructure of the samples comprises cubic grains with smooth surfaces and non-uniform particle distribution in the images.
The melt phase surrounds the irregularly shaped grains, and a few isolated micropores exist in the microstructure, implying partial melting of the NASICON phase.
Thus, the porosity observed in all the samples does not prevent the mobile ion movement between the grains and grain boundaries.
The inset in the EDX spectrum beside each SEM micrograph indicates the atomic and weight percentage of all the various elements present in the samples except Li which cannot be detected by the EDX machine due to the smaller size and lower atomic number.
The microstructure of the samples comprises cubic grains with smooth surfaces and non-uniform particle distribution, indicating crystallization and consistent with the XRD data.

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 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.

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.

There were significant differences in the cell number between the naked and coated samples after culturing for 3 and 5 days (p<0.05).
For the proliferation tests, the cells number was determined with a hemocytocounter.
From Fig.4b, it can be seen that the dense MgF2 coating, which is composed of fine grains sized in nanoscale, is covered on the surface of HF treated Mg-Zn-Zr alloy.
Meanwhile, there were significant statistical differences in the cell number between the two specimens after culturing for 3 and 5 days (p<0.05).
Moreover, there were significant statistical differences in the cell number between the two specimens after culturing for 3 and 5 days (p<0.05).

The results showed thatthe DGGE profiles of the 16fecal samples were highly polymorphic.The number of DGGE bands, considered indicative of the total species richness, did not vary predictably among the threedifferent samples.The DNAsequences were analyzed and the dominant bacteria in sheep fecal were found to beBacteroides, Clostridium, and Ruminococcus.Specially,non-transgenic sheep had more Alistipesfinegoldii and Clostridiumlentocellum, transgenic sheep with VP1 hadmore Clostridiumdrakei and Clostridium populeti and transgenic sheep with SB-SW had moreBarnesiellaintestinihominis and Clostridiumljungdahlii.
It is estimated that gut bacteria can only cultivate the total number of bacteria in the intestines of 10% to 50%[3].
PCR-DGGE techniques have been found in analyzing bacterial diversity in waste water[7], ruminal fluid[8], and kefir grains[9].
The number of DGGE bands, considered indicative of the total species richness, did not vary predictably among the three different samples.
Discussion In this study, we found that the number of DGGE bands, considered indicative of the total species richness, did not vary predictably among the three different samples.For example, Clostridium,Bacteroidesand Ethanoligenens were found in all samples.

It represents the frequency of occurrence of earthquakes as a function of magnitude: , (1) where N is the cumulative number of earthquakes with magnitude larger than M and a and b are constants.
Analysis and results The data is separated into different depth ranges for calculation of the frequency magnitude distribution according to the number of the events.
As normal stress levels increase with depth, the earth becomes more close-grained, resulting in a greater area of contact.
For example, the small events may precede the big earthquake and the big event always accompanied with a number of aftershocks.
The probability (P) that a magnitude event will develop into a larger event is given by the ratio of the number .

Assume Y is diffraction intensity and X is diffraction angle(2θ), so the target function for fitting is, (1) where stands for the total diffraction intensity of crystal fraction at X, is the t-th diffraction intensity at X, stands for the total intensity of non-crystalline fraction, and N is the number of crystal diffraction peaks.
For the non-crystalline fraction, the Seventh Polynomial is selected for interpolation and fitting, that is, (3) Select the proper undetermined coefficients ft,At,Pt,Wt,a,b,c,d,e,f,g,h , trying to make the curve Ycal(X) determined by calculating and experimental curve Yobs(X) overlapping, so the following evaluation function, (4) tends to zero, that is, the minimal value, where m is the number of discrete data points in Tibetan medicine XRD patterns.
The obtained peak type data after making peak resolution Serial number Peak intensity [CPS] Peak position[º] FWHM[º] 14# a 104.8 15.03 1.338 b 143.1 17.67 2.596 c 69.36 20.59 2.361 d 135.8 22.91 2.214 25# a 101.9 15.9 4 b 221.6 21.99 3.713 27# a 98.49 15.43 0.0629 b 200 15.52 4.913 c 170.4 22.3 3.504 50# a 76.42 18.56 6.984 Note: Here the a,b,c,d are signs marked in Fig. 1-4.
It can be found in Fig.2 that there are two crystal peaks with large FWHM, the crystalline grain being large, which the specific data can be seen in Table 1.For the sample 27#, it presents 'Twin Peak' as a whole, yet being a little different from sample 25#.
Handling this kind of pattern with peak resolution proves to be a little difficult, for its being sensitive to peak height and peak number.

Silica sand, with a specific gravity of 2.61 and grain sizes ranging from 105 to 120 μm, was used in the study.
It is rational that the value of cracking number is highest around middle of specimen because the cement matrix stress is theoretically maximized at the around middle of sector.
It is obvious that, there is significant difference in number of cracking distribution between all the specimen(when compared at same tensile stress).
As the replacement of EXA 10% the total width decrease, but the number of cracks increase.
The shrinkage compensating UHS-SHCC ties exhibited crack distribution, and the resulting greater number of cracks.

Now, the development of seismic rock physics research has actually exceeded the seismic interpretation of the requirements of a large number of rock physics theory tentacles out into the seismic data has been unable to distinguish the pore space.
Rock and fluid properties through a variety of research and development of effective medium model, speed and attenuation factors of a large number of experimental tests have summed up the experience in relation to certain formulas, rock physics model thus has been able to establish a means of allowing people to rock composition, such as porosity and particle structure, fluid saturation and stress, many of the reservoir rock to quantify the elastic and inelastic characteristics.
For the reservoir rock is usually high pressure tends asymptotically towards the flat line, after reaching vary only the first step confining pressure and pore pressure between, there is no absolute "effective pressure Guidelines"; pressure depends on the grain boundaries.
In a large number of speed porosity theoretical formulas and empirical relationships, the time average equation is widely used in accordance with the mineral composition and pore fluid rocks to estimate the seismic velocity, or speed based on the measured value and the rock type and pore fluid composition to estimate porosity.
A large number of experimental observations indicate that the velocity almost always increases with frequency and when the waves propagate through the rock always decay.