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Online since: June 2017
Authors: Ze Xu Hu, Si Meng, Qiu Xu Lu, Heng Xue Xiang, Zi Ye Chen, Pei Ling Wei, Mei Fang Zhu
Meanwhile, PPS fiber is a suitable material to produce the filter bag for the reduction of the pollution in industrial waste gases, including PM 2.5 and PM 10.
Table 2 DSC data for the neat PPS, PPS/GNPs and PPS/GNPs-g-PPS **.
It could be confirmed by t1/2, Table 3, and the relative crystallinity-time curves, Fig.6(b), which plotted with the data calculated according to formula 3 and formula 4
Table 3 TGA data for the neat PPS, PPS/GNPs, PPS/GNPs-g-PPS.
Table 2 DSC data for the neat PPS, PPS/GNPs and PPS/GNPs-g-PPS **.
It could be confirmed by t1/2, Table 3, and the relative crystallinity-time curves, Fig.6(b), which plotted with the data calculated according to formula 3 and formula 4
Table 3 TGA data for the neat PPS, PPS/GNPs, PPS/GNPs-g-PPS.
Online since: May 2021
Authors: Ruslan R. Safin, R.R. Kozlov, Dmitry B. Prosvirnikov
Comparison of the Physical Properties of WCM Obtained Using Washed and Unwashed Fibers Activated by Steam Explosive Treatment
For a comparative analysis of the properties of WCM from washed and unwashed fibers activated by steam explosive treatment, the density data are summarized in one graph in Fig. 2.
As can be seen from the comparative data, the density of the washed samples at a pressing temperature of 220 °C is significantly lower than that of the unwashed ones.
The washed fiber shows a reduction in amorphous content while maintaining the crystalline fraction.
Table 1 shows the data on the density of WCM from unwashed fibers activated by steam explosive treatment with the addition of NaHSO3.
As can be seen from the comparative data, the density of the washed samples at a pressing temperature of 220 °C is significantly lower than that of the unwashed ones.
The washed fiber shows a reduction in amorphous content while maintaining the crystalline fraction.
Table 1 shows the data on the density of WCM from unwashed fibers activated by steam explosive treatment with the addition of NaHSO3.
Online since: January 2016
Authors: Isidoro Giorgio Lesci, Norberto Roveri, Leonardo Ciocca, Odila Mezini
Moreover, when prototyped, the unique way to 3D-print HA are block reduction or molding techniques: no direct printing may be hypothesized, due to the isotropic/anisotropic contracture of the material during sintering.
Biomaterial characterization X-ray diffraction (XRD) spectroscopy XRD was performed for nanometric HA nanoparticles characterization; data were collected using a PANalytical θ/θ diffractometer (CuKα radiation; 40 kV and 40 mA) equipped with a real-time multiple strip (RTMS) detector.
Data were collected in the continuous mode, with Ni filtration of the primary beam, the divergence slits fixed at 1/41, 0.00231 Soller slits on the incident and secondary beams, a fixed1/41 antiscatter slit, and a fixed 5-mm RTMS slit.
The obtained data suggest that the size of the crystal domains is governed by electrostatic interactions with the collagen that restrict the growth of the primary crystallites along c-axis.
Biomaterial characterization X-ray diffraction (XRD) spectroscopy XRD was performed for nanometric HA nanoparticles characterization; data were collected using a PANalytical θ/θ diffractometer (CuKα radiation; 40 kV and 40 mA) equipped with a real-time multiple strip (RTMS) detector.
Data were collected in the continuous mode, with Ni filtration of the primary beam, the divergence slits fixed at 1/41, 0.00231 Soller slits on the incident and secondary beams, a fixed1/41 antiscatter slit, and a fixed 5-mm RTMS slit.
The obtained data suggest that the size of the crystal domains is governed by electrostatic interactions with the collagen that restrict the growth of the primary crystallites along c-axis.
Online since: September 2018
Authors: Pavel A. Akimov, Alexander M. Belostotskiy, Dmitry S. Dmitriev
(5)
In order to use the free field seismic response analysis data or the soil layers seismic response analysis data to solve the underground structure seismic response two main assumptions are made.
Thus, the free field seismic response analysis data can be used for computing of underground structure maximum seismic response within static formulation.
Dmitriyev, About contemporary approaches to reduction of computational dimension of problems of structural analysis within finite element method, International Journal for Computational Civil and Structural Engineering. 3(13) (2017) 19-33
Thus, the free field seismic response analysis data can be used for computing of underground structure maximum seismic response within static formulation.
Dmitriyev, About contemporary approaches to reduction of computational dimension of problems of structural analysis within finite element method, International Journal for Computational Civil and Structural Engineering. 3(13) (2017) 19-33
Online since: October 2010
Authors: Mei Zhou, Kun Song, Xiao Ming Yang
Test
Materials and mix proportion
Materials
Cement: Dunshi brand P▪O42.5cement; bentonite: the natural sodium bentonite made in Jilin province, whose main chemical composition is showed in table 1; clay: local clay which is made into mud form by grinding, screening (2.5 mm mesh) and size reduction. [4]; sand: river sand which has 2.75 fineness modulus 2612kg/m3 compact bulk density, 40.3% porosity and 1% moisture content; gravel: crushed stone which apparent density, 1451 kg/m3 compact bulk density, 43.1% porosity; water reducer: FDN-I non-air entraining water reducer made in Beijing, which has 20% water-reducing rate and many characteristics such as low mixing amount, low shrinkage, highly effective slump loss resistant; crumb rubber: the crumb rubber (Fig 1) made from waste tyre with crushing, dust removal, cleaning and gradation.
Table 1 Chemical composition of bentonite / % composition SiO2 FeO K2O TiO2 Al2O3 CaO Na2O MnO Fe2O3 MgO P2O5 Alkali content 65~70 0.65~ 0.81 0.9~1.09 0.13~0.16 15~16.5 0.96~1.5 1.86~2.1 0.01~0.02 2~2.3 1.77~2.3 0.035~ 0.037 0.5~0.55 Fig. 1crumb rubber Fig. 2 Particle size distribution map of crumb rubber Table 2 Chemical composition of crumb rubber% composition C O Si Ca Zn Cl Al S Fe Mg Na K Cu Ni P Br content 62.0 23.7 3.0 2.8 2.2 1.1 1.1 1.0 1.0 0.9 0.5 0.2 0.2 0.1 0.1 0.1 Table 3 Sieve data of crumb rubber sieve residue amount m1 (5mm) m2 (2.5mm) m3 (1.25mm) m4 (0.63mm) m5 (0.315mm) m6 (0.16mm) group 1 0g 0.1g 6.1g 100.3g 139.3g 78.3g group 2 0g 0.1g 5.7g 149.9g 155.4g 89.4g Mix proportion We designed the experimental mix proportion on condition that sand ratio and the amount of cementitious material didn’t change.
Then we used this section of data to do the linear fitting(Fig 4).
Table8 Elastic modulus of crumb rubber plastic concrete No. elastic modulus No. elastic modulus RPC-1 2.6182×103 RPC-9 4.9833×103 RPC-2 5.6784×103 RPC-10 5.1694×103 RPC-3 2.3380×103 RPC-11 2.8577×103 RPC-4 2.5630×103 RPC-12 2.7814×103 RPC-5 3.7427×103 RPC-13 5.2016×103 RPC-6 2.1441×103 RPC-14 0.5554×103 RPC-7 5.4707×103 RPC-15 4.5837×103 RPC-8 1.1412×103 RPC-16 4.9104×103 Using the experimental data of table8 as sample, we got this regression equation with software MATLAB.
Table 1 Chemical composition of bentonite / % composition SiO2 FeO K2O TiO2 Al2O3 CaO Na2O MnO Fe2O3 MgO P2O5 Alkali content 65~70 0.65~ 0.81 0.9~1.09 0.13~0.16 15~16.5 0.96~1.5 1.86~2.1 0.01~0.02 2~2.3 1.77~2.3 0.035~ 0.037 0.5~0.55 Fig. 1crumb rubber Fig. 2 Particle size distribution map of crumb rubber Table 2 Chemical composition of crumb rubber% composition C O Si Ca Zn Cl Al S Fe Mg Na K Cu Ni P Br content 62.0 23.7 3.0 2.8 2.2 1.1 1.1 1.0 1.0 0.9 0.5 0.2 0.2 0.1 0.1 0.1 Table 3 Sieve data of crumb rubber sieve residue amount m1 (5mm) m2 (2.5mm) m3 (1.25mm) m4 (0.63mm) m5 (0.315mm) m6 (0.16mm) group 1 0g 0.1g 6.1g 100.3g 139.3g 78.3g group 2 0g 0.1g 5.7g 149.9g 155.4g 89.4g Mix proportion We designed the experimental mix proportion on condition that sand ratio and the amount of cementitious material didn’t change.
Then we used this section of data to do the linear fitting(Fig 4).
Table8 Elastic modulus of crumb rubber plastic concrete No. elastic modulus No. elastic modulus RPC-1 2.6182×103 RPC-9 4.9833×103 RPC-2 5.6784×103 RPC-10 5.1694×103 RPC-3 2.3380×103 RPC-11 2.8577×103 RPC-4 2.5630×103 RPC-12 2.7814×103 RPC-5 3.7427×103 RPC-13 5.2016×103 RPC-6 2.1441×103 RPC-14 0.5554×103 RPC-7 5.4707×103 RPC-15 4.5837×103 RPC-8 1.1412×103 RPC-16 4.9104×103 Using the experimental data of table8 as sample, we got this regression equation with software MATLAB.
Online since: December 2022
Authors: Paramita Jaya Ratri, Nila Tanyela Berghuis, Delta Rosalina Naiggolan
According to data from the Indonesian plantation directorate, the sugarcane plantation area reached 418,990 hectares spread across Indonesia in 2020 with a total production of around 2,120,000 tons.
Adsorption kinetics and thermodynamic parameters were also analyzed by interpreting experimental data.
Based on Fig. 7 and data in Table 1, adsorption process of Pb(II) ions follows a pseudo-second-order adsorption kinetics model, it shows that the rate of adsorption of lignin bagasse and lignin-Mg(OH)2 to Pb(II) ions per time is directly proportional to the square of the capacity of the empty adsorbent (Qe-Qt).
So that at the beginning of the adsorption process there was a significant reduction in adsorption capacity and the adsorption rate decreased when it reached equilibrium.
Based on the data in Table 2, the RL value for Pb(II) metal adsorption with lignin-Mg(OH)2 and lignin bagasse adsorbents has an RL value > 0 which indicates that the adsorption process is favourable [27].
Adsorption kinetics and thermodynamic parameters were also analyzed by interpreting experimental data.
Based on Fig. 7 and data in Table 1, adsorption process of Pb(II) ions follows a pseudo-second-order adsorption kinetics model, it shows that the rate of adsorption of lignin bagasse and lignin-Mg(OH)2 to Pb(II) ions per time is directly proportional to the square of the capacity of the empty adsorbent (Qe-Qt).
So that at the beginning of the adsorption process there was a significant reduction in adsorption capacity and the adsorption rate decreased when it reached equilibrium.
Based on the data in Table 2, the RL value for Pb(II) metal adsorption with lignin-Mg(OH)2 and lignin bagasse adsorbents has an RL value > 0 which indicates that the adsorption process is favourable [27].
Online since: May 2011
Authors: S.K. Sharma
Typical polarization plots showing the corrosion of amorphous, nanocrystalline and crystalline forms of Ti60Ni40 in 0.5 HNO3 are shown in Fig 1 and the polarization and weight loss data on these alloys in 0.1 M, 0.5 M and 1 M HNO3 are given in Table I [90].
Some typical polarization plots in 0.5 M H2SO4 is shown in Fig. 2 and the corresponding values of Icorr, Ecorr and weight loss data (including those in 0.5 M NaCl) are mentioned in Table 2.
Weight loss data obtained from different states of Ti60Ni40 also confirm the results of polarization studies (see Table 1 and Table 2).
They suggested that improvement in oxidation resistance occurs by reduction in the driving force or the mobility of the rate controlling element in the nanocrystalline state [49].
The polarization results are also supported by the weight loss data obtained in different aqueous media for amorphous, nanocrystalline and crystalline states. 2.
Some typical polarization plots in 0.5 M H2SO4 is shown in Fig. 2 and the corresponding values of Icorr, Ecorr and weight loss data (including those in 0.5 M NaCl) are mentioned in Table 2.
Weight loss data obtained from different states of Ti60Ni40 also confirm the results of polarization studies (see Table 1 and Table 2).
They suggested that improvement in oxidation resistance occurs by reduction in the driving force or the mobility of the rate controlling element in the nanocrystalline state [49].
The polarization results are also supported by the weight loss data obtained in different aqueous media for amorphous, nanocrystalline and crystalline states. 2.
Online since: October 2011
Authors: Fang Ling Fan, Chao Fu Wei, Shuai Yin
The fractal-based metrics changed due to human activities,which also cause the reduction of fragmentation-based metrics.
In this paper, land-use map and planning map are used instead of Remote Sensing image or satellite data.
Scaling functions for landscape pattern metrics derived from remotely sensed data: Are their subpixel estimates really accurate?
Monitoring the evolution of the Pasig- Potrero alluvial fan, Pinatubo Volcano, using a decade of remote sensing data.
In this paper, land-use map and planning map are used instead of Remote Sensing image or satellite data.
Scaling functions for landscape pattern metrics derived from remotely sensed data: Are their subpixel estimates really accurate?
Monitoring the evolution of the Pasig- Potrero alluvial fan, Pinatubo Volcano, using a decade of remote sensing data.
Online since: September 2013
Authors: Ren Jin Sun, Hao Wang, Lu Meng
The basic data of the plant is as follows:
Table 1 Producing and economic index
Project
Unit
Index
Production index
Processing ability
104tons
1000
Consumption of fresh water
t/h
586
Bought electric quantity
108KWh
3.78
Comprehensive energy consumption
MJ/t crude oil
3018
Plant cover aera
km2
1.98
Economic index
Construct investment
108USD
30.11
Sales revenue
108USD
51.00
Total cost expenses
108USD
41.32
Unit processing cost
USD/ t
36.03
Exchange: 1USD=6.1668CNY
Wherein, the internal rate of return is 15% and investment pay-back time is 8.3 year.
The reduction of original products and increase of new products are shown in Table 4, which lead to profit increase of 1.21×104 thousand USD.
Table 5 Basic data for calculation Project PSA Toluene disproportionation and adsorption stripping Energy recycling Total (104 USD) Aggregate investment 729.45 29178.00 121.58 30029.03 Cost 251.03 3075.49 -1552.82 1773.70 Sales revenue 759.32 15172.95 - 15932.27 Profit 508.29 12097.45 1552.82 14158.57 After-tax profits 340.55 8105.30 1040.39 9486.24 Reference the discount rate 12% With calculation, the net financial reaches 4.21×105 thousand USD, the dynamic payback period is 4.2 years, the internal rate of return IRR = 17%.
Compared with the basic economic data of Table 1, this equipment successfully meets the requirements of the economy.
The reduction of original products and increase of new products are shown in Table 4, which lead to profit increase of 1.21×104 thousand USD.
Table 5 Basic data for calculation Project PSA Toluene disproportionation and adsorption stripping Energy recycling Total (104 USD) Aggregate investment 729.45 29178.00 121.58 30029.03 Cost 251.03 3075.49 -1552.82 1773.70 Sales revenue 759.32 15172.95 - 15932.27 Profit 508.29 12097.45 1552.82 14158.57 After-tax profits 340.55 8105.30 1040.39 9486.24 Reference the discount rate 12% With calculation, the net financial reaches 4.21×105 thousand USD, the dynamic payback period is 4.2 years, the internal rate of return IRR = 17%.
Compared with the basic economic data of Table 1, this equipment successfully meets the requirements of the economy.
Online since: August 2022
Authors: Kholidina Imanda Harahap, Henniza Rahmi, Metta Winni
The data obtained were carried out by the Saphiro-Wilk normality test, One-Way ANOVA test (p<0.05) and Least Significance Difference test.
GIC (Control) 10 5.28 0.07 GIC+2%HA 10 5.59 0.05 GIC+5%HA 10 6.25 0.09 GIC+8%HA 10 6.56 0.06 Based on the Saphiro Wilk test, it was found that the data were normally distributed (p>0.05).
When data were analyzed by using one-way ANOVA test and Least Significance difference test there was a significant difference at 0.005 level of significant (p<0.005), as can be seen on Table 4-7.
In RMGIC which containing HEMA, hydrogen bond will be formed between HEMA polymer and polycarboxylic acid through oxidation of reduction and reactions.
GIC (Control) 10 5.28 0.07 GIC+2%HA 10 5.59 0.05 GIC+5%HA 10 6.25 0.09 GIC+8%HA 10 6.56 0.06 Based on the Saphiro Wilk test, it was found that the data were normally distributed (p>0.05).
When data were analyzed by using one-way ANOVA test and Least Significance difference test there was a significant difference at 0.005 level of significant (p<0.005), as can be seen on Table 4-7.
In RMGIC which containing HEMA, hydrogen bond will be formed between HEMA polymer and polycarboxylic acid through oxidation of reduction and reactions.