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Online since: June 2019
Authors: Emine Güneri
This could be because of the radius of Cu+ (0.096 nm) is smaller than that of Au+
(0.137 nm) [19].
1d2=h2+k2+l2a2 (1)
To determine the preferred orientation of crystalline planes, the texture coefficients TC (hkl) are calculated using the Harris analysis technique given in equation (2) [22],
TC=I (hkl)Io (hkl)1N(IhklIo(hkl)) (2)
where Tc(hkl) is the texture coefficient of (hkl) plane, I(hkl) is the intensity measured for (hkl) plane, Io(hkl) is the intensity of (hkl) plane taken from standard data in PDF cart fitting in the X-ray diffraction pattern of material, N is total reflection number, n is diffraction peak number.
The defective location density (d) which gives the number of defects in the structure is calculated with equation (4) [22].
As is the previous reported results show that the energy band gap is reduced with increasing grain size and film thickness, which is consistent within this studies reported results [28, 29] (Fig.8).
Fig. 8 Variation of energy band gap and grain size with respect to doping ratio of Au-doped Cu2O films.
The defective location density (d) which gives the number of defects in the structure is calculated with equation (4) [22].
As is the previous reported results show that the energy band gap is reduced with increasing grain size and film thickness, which is consistent within this studies reported results [28, 29] (Fig.8).
Fig. 8 Variation of energy band gap and grain size with respect to doping ratio of Au-doped Cu2O films.
Online since: October 2013
Authors: Jie Chen, You Yang Wang, Hui Ping Si, Jun Hui Wu, Kai Yan Lin
Feedstock currently includes wood chip and wood pellets, treebark, crop residues (straw, nut shells and rice hulls), switch grass, organic wastes including distillers’ grain, gas from the sugarcane industry, chicken litter, dairy manure, sewage sludge and paper sludge[[] Sohi, S., Lopez-Capel, E., Krull, E., Bol, R.: Biochar, Climate change and soil: a review to guide future research, in CSIROL and Water Science Report series ISSN: 1834-6618. (2009)
].
Energy Sources 30(Part A), 38–44. (2008) ].obviously, the yields of the biochar or the by-product( biofuel) depend on the temperature in the pyrolysis on a large number, at the same time, which determines the properties of the biochar[[]Lehmann J, Gaunt J, Rondon M.: Biochar sequestration in terrestrial ecosystems-A review [J].
Meanwhile, the biochar from the corn stalk have a lower porosity with the temperature rising beyond 900℃,and the micro pore porosity and small pore number reaches the maximum on 900℃[[]FU P, HU S, XIANG J, et al.: Pyrolysis of maize stalk on the characterization of chars formed under different devolatilization conditions[J].
The Effect of Biochar on Heavy Metal in Soil Adsorption of heavy metal in biochar from the soil could involve a number of possible mechanism, including ion exchange, chemical exchange, surface precipitation and electrostatic attraction etc.
Soil physical properties, leaf SPAD and grain yield [J].
Energy Sources 30(Part A), 38–44. (2008) ].obviously, the yields of the biochar or the by-product( biofuel) depend on the temperature in the pyrolysis on a large number, at the same time, which determines the properties of the biochar[[]Lehmann J, Gaunt J, Rondon M.: Biochar sequestration in terrestrial ecosystems-A review [J].
Meanwhile, the biochar from the corn stalk have a lower porosity with the temperature rising beyond 900℃,and the micro pore porosity and small pore number reaches the maximum on 900℃[[]FU P, HU S, XIANG J, et al.: Pyrolysis of maize stalk on the characterization of chars formed under different devolatilization conditions[J].
The Effect of Biochar on Heavy Metal in Soil Adsorption of heavy metal in biochar from the soil could involve a number of possible mechanism, including ion exchange, chemical exchange, surface precipitation and electrostatic attraction etc.
Soil physical properties, leaf SPAD and grain yield [J].
Online since: September 2008
Authors: Daniel Monceau, Djar Oquab, Aurélie Vande Put
Thermal cycling is stopped at a certain number of cycles, depending on the system, before
complete spallation determined by critical mass change.
The bond coating shows alumina grain imprints which are characteristic of an inward growing oxide.
Net Mass Change versus number of cycles.
Vialas et al. [17] showed that this volume change can be either an increase or a decrease, and that the β/γ' phase transformation boundary can be either parallel to the surface or localized at BC grain boundaries.
Thus, the formation of a limited number of pegs could be a good compromise with regards to crack propagation given that pegs roughen the interface.
The bond coating shows alumina grain imprints which are characteristic of an inward growing oxide.
Net Mass Change versus number of cycles.
Vialas et al. [17] showed that this volume change can be either an increase or a decrease, and that the β/γ' phase transformation boundary can be either parallel to the surface or localized at BC grain boundaries.
Thus, the formation of a limited number of pegs could be a good compromise with regards to crack propagation given that pegs roughen the interface.
Online since: July 2004
Authors: A.M. Lyakhovitch, A.M. Dorfman, M.A. Shirobokov
With an increase in film
thickness the sticky layer disappears and the number of cone-shaped formations increase and they
eventually coalesce.
In view of these premises, with further increase of film thickness increase, which ensures an even higher degree of cross-linking, could well be supposed to cause the growth in the number of cones, with the formation of extended structures (ridges, for example) as they coalescence.
Judging by the size, they correspond to the grain boundaries of the steel substrate.
In view of these premises, with further increase of film thickness increase, which ensures an even higher degree of cross-linking, could well be supposed to cause the growth in the number of cones, with the formation of extended structures (ridges, for example) as they coalescence.
Judging by the size, they correspond to the grain boundaries of the steel substrate.
Online since: October 2011
Authors: Guo Jun Zhang, Cai Qian Shi, Hong Nan Li
A number of similar engineering practices indicate that the maximum adiabatic temperature rise is mainly subjected to the control of concrete mix composition and internal and the temperature difference between inside and outside is mainly controlled by the moisture and insulation measures, which are the two major critical factors controlling mass concrete slab temperature cracks, providing references to future similar mass concrete construction.
1.
Water block slab of section B is shown in Figure 2. 5 Mass Concrete Construction 5.1 Make full preparation of rain and snow protection A building in Dalian is proposed for the grain trading center of Northeast Asia, adjacent to this project.
The practice of a number of similar projects indicate that maximum adiabatic temperature rise of mass concrete is mainly subjected to the control of concrete mix composition, whereas the internal and external temperature difference is controlled by moisture and insulation measures, which are two crucial factors controlling temperature cracks in mass concrete slab, providing references to similar mass concrete construction in future.
Water block slab of section B is shown in Figure 2. 5 Mass Concrete Construction 5.1 Make full preparation of rain and snow protection A building in Dalian is proposed for the grain trading center of Northeast Asia, adjacent to this project.
The practice of a number of similar projects indicate that maximum adiabatic temperature rise of mass concrete is mainly subjected to the control of concrete mix composition, whereas the internal and external temperature difference is controlled by moisture and insulation measures, which are two crucial factors controlling temperature cracks in mass concrete slab, providing references to similar mass concrete construction in future.
Online since: May 2018
Authors: Bondan Tiara Sofyan, Dewi Lestari Natalia, Risly Wijanarko, Irene Angela
These numbers however, declined on samples with higher compaction pressure of 359 MPa due to the formation of porosities caused by entrapped gas that failed to exit the sample of which compaction pressure was considered to be overwhelmingly high.
AlNbO4 is responsible to control the grain boundaries so that densification can occur at lower temperature.
AlNbO4 is responsible to control the grain boundaries so that densification can occur at lower temperature.
Online since: April 2015
Authors: Ming Jun Peng, Yong Sun, Yong Hua Duan
The present work further extended the calculations of the enthalpies of formation to a number of AlB2-type diborides.
(1) Where h is the Planck’s constant, k is Boltzmann’s constant, NA is the Avogadro number, n is the number of atoms in the molecule, M is the molecular weight, and ρ0 is the density, respectively.
As the number of valence electron is increased, the bonding band becomes filled and further filling electrons are donated predominantly into the metallic band as shown in the case of AlB2.
Roughly speaking, the number of the d- pπ bonding bands is formally the same as that of the low-lying pπ states [12].
Li, Grain refining mechanism of Al-3B master alloy on hypoeutectic Al-Si alloys, Trans.
(1) Where h is the Planck’s constant, k is Boltzmann’s constant, NA is the Avogadro number, n is the number of atoms in the molecule, M is the molecular weight, and ρ0 is the density, respectively.
As the number of valence electron is increased, the bonding band becomes filled and further filling electrons are donated predominantly into the metallic band as shown in the case of AlB2.
Roughly speaking, the number of the d- pπ bonding bands is formally the same as that of the low-lying pπ states [12].
Li, Grain refining mechanism of Al-3B master alloy on hypoeutectic Al-Si alloys, Trans.
Online since: September 2011
Authors: Yong Hui Pan, Mao Gang Wu, Fang Bao
Both the above and nether sewing threads have been sewed in the middle along the same fabric grain direction.
Due to the number of the main factors and the seam pucker grade of subjective evaluation has been fixed, we set the corresponding node number of the input layer, hidden layer, and output layer of network is 5, 25 and 1 respectively, and let the weight coefficient of SFCM clustering m=2.
We uses ordinary BP neural network to evaluate seam pucker, and sets the number of hidden layer equal to 6 and the objective error equal to 0.1.
The optimizing iteration number of BP network is about 35000.
By large numbers of testing, we find the convergence speed of our algorithm is very fast on the same objective error 0.1, and the iteration number of SFCM is about 103 degree.
Due to the number of the main factors and the seam pucker grade of subjective evaluation has been fixed, we set the corresponding node number of the input layer, hidden layer, and output layer of network is 5, 25 and 1 respectively, and let the weight coefficient of SFCM clustering m=2.
We uses ordinary BP neural network to evaluate seam pucker, and sets the number of hidden layer equal to 6 and the objective error equal to 0.1.
The optimizing iteration number of BP network is about 35000.
By large numbers of testing, we find the convergence speed of our algorithm is very fast on the same objective error 0.1, and the iteration number of SFCM is about 103 degree.
Online since: January 2010
Authors: B.D. Shanina, Valentin Gavriljuk
The knowledge of these energies can be useful for estimation of atomic distribution in the
solid solutions as well as for studies of segregation phenomena at grain boundaries and other crystal
lattice defects.
Let us consider the γ-Fe (Fig. 1a): the number of the nearest neighbors per atom Z is equal to 12, the number of atoms in the elementary cell is equal to 4, and the total number of atomic bonds per cell is equal to 24 because the each bond is taken twice into account.
Three Fe atoms are identical, and each of them has 4 nearest Me and 8 nearest Fe neighbors, so that Fe has the following number of bonds: nFe-Me = 4 and nFe-Fe = 8.
The total number of bonds is equal to nMe-Fe+3⋅(nFe-Me+nFe-Fe).
Values of E1(Fe-Fe) and E(Fe-C) are found from the system of equations for the number of bonds: 84E1(Fe-Fe)+108E0(Fe-Fe) + 6E(Fe-C)= Estruct(Fe32C) 24 E1(Fe-Fe)+6 E(Fe-C) = Estruct(Fe4C) (8) The first equation is related with the total bond energy in crystal cell Fe32C taking into account the changed bonding energy for 14 Fe atoms.
Let us consider the γ-Fe (Fig. 1a): the number of the nearest neighbors per atom Z is equal to 12, the number of atoms in the elementary cell is equal to 4, and the total number of atomic bonds per cell is equal to 24 because the each bond is taken twice into account.
Three Fe atoms are identical, and each of them has 4 nearest Me and 8 nearest Fe neighbors, so that Fe has the following number of bonds: nFe-Me = 4 and nFe-Fe = 8.
The total number of bonds is equal to nMe-Fe+3⋅(nFe-Me+nFe-Fe).
Values of E1(Fe-Fe) and E(Fe-C) are found from the system of equations for the number of bonds: 84E1(Fe-Fe)+108E0(Fe-Fe) + 6E(Fe-C)= Estruct(Fe32C) 24 E1(Fe-Fe)+6 E(Fe-C) = Estruct(Fe4C) (8) The first equation is related with the total bond energy in crystal cell Fe32C taking into account the changed bonding energy for 14 Fe atoms.
Online since: November 2012
Authors: Lan Min Wang, Zhong Xia Yuan, Wang Nai, Wang Qian
Typical loess seismic landslides in valley city
Research has shown that the loess in valley city is the self weight collapse loess and intensity collapse loess which has characteristics as low water content, low density, macropores, low viscous grain content, loose structure, up-growth of joint and the granular space structure.
Among the samples, the number of loess landslides is 53 which accounting for 50.5% of the total number of landslides.
The number of loess-mudstone landslides is 42 which accounting for 40.0%.
The number of loess landslide is 12, loess-mudstone interface landslide is 2 and loess-mudstone landslide is 8.
The number of loess landslide is 11, loess-mudstone interface landslide is 3 and loess-mudstone landslide is 6.
Among the samples, the number of loess landslides is 53 which accounting for 50.5% of the total number of landslides.
The number of loess-mudstone landslides is 42 which accounting for 40.0%.
The number of loess landslide is 12, loess-mudstone interface landslide is 2 and loess-mudstone landslide is 8.
The number of loess landslide is 11, loess-mudstone interface landslide is 3 and loess-mudstone landslide is 6.