Search results

Introduction Carbon nanotubes (CNTs) materials are well known as to their unique shape; rolled graphene sheets with a large number of hilicities and chiralities of graphene sheet rolled up like a scroll [1].
The catalyst was grained small before calcined in oven at 900 ºC for 10 hrs.
Fourier transform infrared (FTIR) spectra of the samples were performed in a scan range wave number of 4000-500 cm-1 with a resolution of 2 cm-1 at room temperature.
Samples N Tensile strength (MPa) Tensile Strain (%) Tensile Modulus (MPa) PDMS 5 7.137 ± 0.579 159.300 ± 10.6 8.396 ± 0.403 0.5 wt% PDMS/MWCNT- Al2O3 5 2.657 ± 0.773 102.700 ± 7.2 6.252 ± 1.152 1.0 wt% PDMS/MWCNT- Al2O3 5 2.014 ± 0.610 93.700 ± 17.3 5.027 ± 1.465 1.5 wt% PDMS/MWCNT- Al2O3 5 1.649 ±0.086 128.500 ± 8.5 2.555 ± 1.390 (N = number of samples) Conclusion The influence of processing on the properties of multiwalled carbon nanotubes/alumina hybrid compound filled PDMS composites was investigated.

Introduction Amorphous oxide semiconductors have potential for application to the next-generation electronics because of their wide energy gap (transparent to visible light), no grain boundaries, and relatively low growth temperature [1].
A number of studies have been proposed for achieving the higher performance of indium-based oxide thin film transistors such as the treatment methods, including the material dopant, surface treatment for the wettability, annealing in various temperatures and various ambient atmospheres [4-8].
The conductive behavior suggests the existence of a considerable number of mobile carriers without application of VGS.
It may cause oxygen defects, and the observed device behavior, high off current (low on/off ratio), is consistent with ISO films with considerable number of oxygen defects.

Experimental design In order to analysis all impacts on asphalt mixture to skeleton, study on variation of the coarse aggregate clearance rate with the particle size and grading.The aggregate is divided four factors: 16.0mm～13.2mm,13.2mm～9.5mm，9.5mm～4.75mm，4.75mm～2.36mm, their respective coarse aggregate content is means with X1, X2, X3, X4, The number of levels:n = 16.
Table 1 Coarse aggregate mixture uniform design Particle size and proportion serial number 16.0~13.2mm X1（％） 13.2~9.5mm X2（％） 9.5~4.75mm X3（％） 4.75~2.36mm X4（％） 1 68.51 14.79 8.87 7.83 2 54.58 10.42 1.09 33.91 3 46.14 2.59 30.44 20.83 4 39.75 36.44 2.23 21.58 5 34.48 20.66 29.44 15.42 6 29.95 8.13 9.67 52.25 7 25.94 60.97 8.59 4.50 8 22.32 32.14 9.96 35.58 9 19.01 15.38 47.16 18.45 10 15.95 1.32 23.27 59.46 11 13.10 46.26 31.75 8.89 12 10.42 24.29 22.44 42.85 13 7.90 7.50 71.38 13.22 14 5.51 65.56 11.75 17.18 15 3.23 35.09 55.90 5.78 16 1.05 15.06 39.32 44.57 Analysis on uniform test result The basalt stone is produced Tangshan City in the test, two kinds of forming method are inserted pound and vibration, VCA and skeleton strength value can be measured,date is shown in Fig.1 32.00 33.00 34.00 35.00 36.00 37.00 38.00 39.00 40.00 41.00 42.00 1 2 3 4 5 6 7 8 9
10 11 12 13 14 15 16 Sequence number Tamping vibration VCA(%) Fig. 1 VCA of uniform design test results As can be seen from Fig1, through two cases of ramming and vibrating, VCA trend combination is largely the same, that in the external power role in the case, the change trend of VCA and various aggregate formulation has good correlation.
The CBR test has some experience about the actual value of pavement structure, but it reveals the graded strength of asphalt mixture. 2 VCADRC of coarse aggregate clearance rate with uniform design test Grain size 16.0~13.2 mm X1（％） 13.2~9.5 Mm X2（％） 9.5~4.75 mm X3 （％） 4.75~2.36 mm X4（％） inserted pound VCADRC (%) vibration VCADRC (%) CBR 1 68.51 14.79 8.87 7.83 40.72 38.51 52.72 2 54.58 10.42 1.09 33.91 37.20 34.65 98.53 3 46.14 2.59 30.44 20.83 38.37 35.63 41.37 4 39.75 36.44 2.23 21.58 38.60 35.92 39.24 5 34.48 20.66 29.44 15.42 39.75 35.65 50.78 6 29.95 8.13 9.67 52.25 37.75 34.64 76.05 7 25.94 60.97 8.59 4.50 41.39 39.36 30.95 8 22.32 32.14 9.96 35.58 38.94 34.56 59.13 9 19.01 15.38 47.16 18.45 39.74 36.51 37.93 10 15.95 1.32 23.27 59.46 39.49 36.03 34.87 11 13.10 46.26 31.75 8.89 41.12 38.49 40.94 12 10.42 24.29 22.44 42.85 38.08 34.86 92.30 13 7.90 7.50 71.38 13.22 40.09

Instead, a number of evolutionary microstructure morphologies can be observed during the eutectic solidification with increasing departures from equilibrium.
In particular, the progressive transition from a regular lamellar to an anomalous eutectic structure has been reported in a number of systems, e.g.
Microstructure analysis reveals a number of complex morphologies in the droplets with decreasing diameter (increasing cooling rate), including the eutectic, cellular and dendrite morphologies.
Cui, Microstructural evolution from dendrites to core-shell equiaxed grain morphology for CoCrFeNiVx high-entropy alloys in metallic casting mould.

As the core is desaturated, the water in the pore is emptied, leaving only small amount of water in the interstitial near the grain contacts.
Lithology Number of cores Holes Fractures Obviously Small amount Barely none Obviously Small amount Barely none Rhyolite 50 7 4 39 3 10 37 Tuff 36 4 1 31 4 4 28 Volcanic Breccia 39 5 2 32 2 5 32 Based on these results, it is obvious that 25mm or 38mm diameter core samples are not accurate in representing the complex characteristics of volcanic reservoir correctly due to its size limit.
Lithology Number of cores Measured T2 cutoff (ms) Distribution range Average Rhyolite 21 8.03-179.46 87.91 Tuff 16 11.57-103.72 52.02 Volcanic breccia 15 3.22-86.4 36.28 Table 3 Static of measured T2 cutoff sub-classified by lithology.
Lithology Number of cores Measured T2 cutoff (ms) Distribution range Average Gray rhyolite 3 41.60～71.97 54.50 White rhyolite 3 103.72～179.46 135.90 Green rhyolite 3 49.94～86.40 69.43 Gray spherules rhyolite 3 124.52～124.52 124.52 White spherules rhyolite 2 34.65～86.40 60.53 Rhyolitic crystal tuff 4 71.97～103.72 83.51 Rhyolitic volcanic breccia 4 11.57～41.60 22.78 Crystal volcanic breccia 3 71.97～86.40 81.59 Andesitic tuff breccia 2 3.22～3.87 3.54 Purple andesite 2 24.04～28.86 26.45 4.

Introduction The flow stress values of metal is fundamental quantity to characterize the pressure processing properties .Besides, The flow stress values is also the main parameters to calculate processing power and essential parameters to institute sensible process planning [1, 2].The good grains structure which make the steel with excellent overall performance can be obtained through the rational control of rolling process In the Pressure processing [3].
Where P is the input vector; T is the target output vector; goal is set to the error sum of squares, Its default value is 0, spread is the width coefficient, the default value of 1, MN is the largest number of the hidden layer neurons, Its default value is the number of the input samples group, DF is the displaying frequency of neurons on the increase.
Table 1 Training parameters and training results of neural network Training Parameters Training results The largest Spread Training times Training error Acturality/Target number of 200 0.5 78 0.000995708/0.001 hidden layer 1 63 0.000956971/0.001 neurons 1.5 65 0.000956083/0.001 Training target 0.001 2 66 0.000987726/0.001 2.5 63 0.000935329/0.001 Table 2 Simulation results of RBF neural network Experiment Simulation Relative Simulation Relative Simulation Relative Value[MPa] Value s=1 error(%) Value

With the development of sewage treatment technology, a number of methods are now available for the elimination of ammonia nitrogen, each having its own advantages, disadvantages, and limitations.
Sathy Chandrasekhar[8] believes that the essence of activation is to deprive kaolin of its hydroxyls in the aluminum-oxygen octahedron so that the coordination number of aluminum atoms in kaolin changes from 6 to 4 or 5.
The ammonium ion exchange capacity of the material may be given as the total CEC, which is defined by the number of equivalents of fixed charges per amount of the material.
The mesh-like pore canals run through the material, which has fine and evenly-distributed grains.

Plan-View STEM Analysis In this sample, it was considered difficult to obtain a clear atomic resolution HAADF-STEM image due to crystal defects and grain boundaries in cross-sectional observation, so plan-view STEM observation was performed.
As the HAADF image intensity strongly depends on the atomic number, heavy atoms are observed brighter, and light atoms such as oxigen are difficult to be observed.
Considering the difference in the number of overlapping Ga atoms along the observation direction (<001>direction), k-Ga2O3 produces a contrast difference in the atomic columns in the HAADF image.
In Fig. 3(b), the yellow atomic columns have higher contrast intensity than red columns because the number of overlapping atoms at the yellow columns is larger in observation from <001> direction.

Conventional damage mechanics studies, since then, are getting of prosperity by probabilistic theory: damage evolution functions of solid structure under random loading condition were, based on micro-mechanics-model, set up by Silberschmidt and Chaboche[2]; damage-rupture development mechanism on discontinuous stochastic composite material reinforced by fibers was analyzed with statistics by Wu and Li [3]; mechanical characters of solid brittle material coupled with plane grain cracks submitting to correlated random distribution were investigated by Ju and Tseng who, on the basis of micro-mechanics and mean-volume theory, invited Legedre-Tchebycheff orthogonal polynomial algorithm into analyses[4]; by the help of flat noise generator simulation for random factors influential over medium damage mechanism from both external and internal aspects, continuous damage mechanics was furthered by Silberschmidt based on his early studies [5].
Acknowledgements This work was supported by the National Natural Science Funds (Grant No: 51109118), the China Postdoctoral Science Foundation (Grant No: 20100470344), Fundamental project fund of Zhejiang Ocean University (Serial number: 21045032610), Initiating project fund for doctors of Zhejiang Ocean University (Serial number: 21045011909) and Project of Education Department in Zhejiang (Serial number: Z201119560) References [1] W.

The level of reduced wheel pressure was gradually increased with number of cycles.
Compressive strength was determined on cubic specimens 100x100x100mm, flexural strength using prismatic specimens 40x40x160 mm commonly used for fine-grained composites.
Number of cycles Reduced wheel pressure [kN] Reduced axle pressure [kN] Age of MSC [days] 0 30 60 1 Up to 0.5 mil. 30 60 1. – 8. 0.5 – 1.0 mil. 60 120 8. – 14. 1.0 – 1.5 mil. 60 120 15. – 21. 1.5 – 2.0 mil. 60 120 22. – 28. 2.0 – 2.5 mil. 60 120 29. – 35. 2.5 – 3.0 mil. 60 120 36.
Measured area Reduced wheel load [kN] Number of cycles Maximal extortion [mm] kst [kN/mm] Left 30 0.5 mil. 1.378 21.8 Right 30 0.5 mil. 1.352 22.2 Left 60 1.0 mil. 1.672 35.9 Right 60 1.0 mil. 1.646 36.5 Left 60 1.5 mil. 1.662 36.1 Right 60 1.5 mil. 1.648 36.4 Left 60 2.0 mil. 1.670 35.9 Right 60 2.0 mil. 1.666 36.6 Left 60 2.5 mil. 1.787 33.6 Right 60 2.5 mil. 1.828 32.8 Left 60 3.0 mil. 1.672 35.9 Right 60 3.0 mil. 1.616 37.2 Determination of mechanical properties was carried out using non-destructive and destructive testing, of which detailed results are shown in Tab. 3.