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Due to the limitations of the data, various production equipment and maintenance of the electric arc furnace steelmaking plant were not included in the system.
Steelmaking process and continuous casting process data were all derived from the literature [14,15].
Cut-off approach system contains only one life cycle, the information requires less data, easy to operate, but does not consider the recycling of the environmental load and environmental benefit, a simplified evaluation method with doubts; waste valuable system include primary and secondary life cycle, the category is more complete, but also requires more data, and only consider the environmental load or environmental benefit, which is not comprehensive.
(d) The practice in the BOF process are required to add some scrap, so we need to estimate the theory of environmental impact data of 100% iron ore to use mathematical calculation method.
Cut-off approach system contains only one life cycle, the information requires less data, easy to operate, but does not consider the recovery of the environmental load and environmental benefit.

Procedure and Experimental Data.
The binary energy parameters aij for the miscible mixtures were obtained from vapor-liquid equilibrium data reduction using the following thermodynamic equations:
Parameters b – binary liquid-liquid equilibrium data from this work.
Data Vol.40 (1995). p. 578 [5] K.
Data.

Considering the uncertainty ±0.523 kJ mol-1 in the thermodynamic data for the iron-wüstite references [8,9], the overall accuracy of the data was estimated to be 1.6 kJ mol-1.
The study evidences the effect of the A- and B- site substituents on the thermodynamic data.
Fig. 5 presents typical relationships between the nonstoichiometry and the thermodynamic data of the La0.7Sr0.3MnO3-δ and La0.7Ca0.3MnO3-δ (0.019<δ<0.053) samples.
The reduction in stoichiometry from 0.019 to 0.046 has an opposite effect on 2OΔH and 2OΔS depending on the A-site substituent.
The data are tentatively interpreted as indicating an increase of order in the oxygen sublattice in the Sr-containing sample.

Vast amounts of data accumulated by the remote monitoring system for new energy vehicles makes data processing necessary.
Information redundancy is found when vast amounts of acquisition parameters are in data processing.
Method Data Description The data used is from the remote monitoring system for new energy vehicles operating in Shanghai EXPO.
The data contains 7 attributes and 10421 records.
Accordingly, data acquisition and data transmission can be optimized.

Results and discussion AFM and SEM data.
According to SEM data, an etching speed was about 6.2 nm/s.
Comparison of the AFM and SEM data shows that the size and concentration of pores on the skin-layer surface are quite different from those in the underlying porous layer.
IR spectroscopy data.
Based on the data obtained, it can be assumed that at first, a part of the surface area of as-formed PS layer was partially passivated with hydrogen and it contained a lot of dangling bonds, which played a role of nonradiative recombination centers.

With the help of the experimental data, a mathematical model has been developed to predict the pressure of the stiff layer of air under different wheel speed.
With the help of experimental data, a mathematical model has been developed to predict the pressure of the stiff layer of air.
With the reduction of wheel speed, air pressure is also reduced, and it has been shown in Fig. 4 very distinctly.
It has been found that the model shows close matching with the experimental data.
Reduction in the wheel speed reduces the values of air pressure considerably as shown in Fig. 6 and Fig. 7.

Gradual Fe concentration reduction near preliminary contaminated slab surface and Fe concentration increase near opposite surface were observed.
The presence of these impurities in silicon bulk leads to chip yield and reliability reduction.
This value is twice less than the Fe penetration value (~ 400 mcm) known from previously published data [1].
Exact account of averaging effect is complicated since the electron diffusion length L increases with every etching process due to Fe concentration reduction.
Data represented its concentration were calculated by simple subtraction of Fe concentration value from total recombination centers concentration.

A further reduction in oxide charge was observed after annealing at 1100 °C in N2O, down to a value of 4×1013 cm-2.
It is previously known that the formation of SiO2 in the presence of nitrogen reduces the oxide charges [14] and this could be possible reason for large reduction in the oxide charges for the RCA compared to the standard cleaning.
Electrical capacitance-voltage (CV) measurements (data not shown) on the p-type shows also a negative flatband shift which is in good agreement with previously reported results on p-type 4H-SiC and Al2O3 MOS structures [13].
Annealing at high temperatures results in rearrangement of the atoms at the interface, resulting in a reduction of these traps.

It is established that ultrasonic treatment of the semiconductor in the process of formation of an ensemble of nanoclusters leads to reduction of dispersion of their sizes.
In the framework of this model, a possibility of the ultrasound-stimulated the size dispersion reduction of strained InAs/GaAs quantum dots doped with an isovalent impurity are analyzed.
The theory explained experimental data on the creation of an array of uniform InAs QDs doped with Bi [12].
Numerical calculations were carried out for the following parameters: w = 1011 s-1; e0 = 0,00001; tdi = 0,001 ms; K = 6500 eV/nm3; cl = 3500 m/s; ri(Ga3+) = 0,062 nm; ri(In3+) = 0,092 nm; ri(As3+) = 0,069 nm; ri(Bi3+) = 0,12 nm; ri(Sb3+) = 0,082 nm; ri(P3+) = 0,044 nm; cm2/s;6 cm2/s.19 There are no data in the scientific literature concerning the temperature dependences of the diffusion coefficients for Bi and Sb in InAs.
The obtained results qualitatively agree with the experimental data of Ref. [11].

Although smart materials in building may contribute to energy demand reduction and be considered as innovative technology with multiple values, currently available sustainability assessment tools would not allow the adequate evaluation of smart materials in buildings.
Such design strategies include energy demand reduction from lower heat gain within the building, energy supply of energy from on-site renewables [5], and multi-functionality and higher efficiencies of resource uses [4,6].
Reduction of energy use and carbon emission is to improve the energy performance and most illustrated in smart material façade design.
Phase change materials, smart glazing, and movable solar shading are identified among the promising adaptive façade systems and components in terms of energy reduction potential [7].
Besides, self-cleaning coating made of smart materials contributes to overall reduction of environmental impact and elimination of pollutants.