The Temperature and Structure Dependence of Surface Tension of CaO-SiO2-Na2O-CaF2 Mold Fluxes

Gao, Qiang; Min, Yi; Jiang, Maofa

doi:10.1007/s11663-018-1207-x

Cited by 15 publications

(8 citation statements)

References 29 publications

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“…The vibrational bands of Fe 3+ in the MF region also have been verified in our previous studies by comparing the Raman spectra of Fe 2 O 3 -bearing glass with Fe 2 O 3 -free glass. 44,45) Meanwhile, the peak width of [FeO 4 ] 5− tetrahedron and [FeO 6 ] 9− octahedron has an obvious change, indicating that the structural behavior of Fe 3+ is apt to be affected by slag composition. The detailed reason will be discussed in the following section 3.4.…”

Section: Raman Spectramentioning

confidence: 99%

Structural Evolution of Molten Slag during the Early Stage of Basic Oxygen Steelmaking

et al. 2020

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Section: Raman Spectramentioning

confidence: 99%

Structural Evolution of Molten Slag during the Early Stage of Basic Oxygen Steelmaking

et al. 2020

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“…Some studies , indicated that temperature might affect melt structure, but previous experiment showed that the structures of CaO–SiO 2 –Al 2 O 3 –Fe x O slags changed only slightly with the temperature over a range of 1673–1873 K. Hence, the influence of temperature on the oxygen bond database can be ignored. All the oxygen bond values corresponding to the slag with a specific composition in any temperature of 1673–1873 K can be obtained from the database.…”

Section: Resultsmentioning

confidence: 98%

“…where a i and b i are the constants corresponding to the binary silicate melt composed of SiO 2 and i, which can be determined by correcting the viscosity data of the CaO−SiO 2 −Al 2 O 3 system and are listed in Table 3. Some studies 51,52 indicated that temperature might affect melt structure, but previous experiment showed that the structures of CaO−SiO 2 −Al 2 O 3 −Fe x O slags changed only slightly with the temperature over a range of 1673−1873 K. Hence, the influence of temperature on the oxygen bond database can be ignored. All the oxygen bond values corresponding to the slag with a specific composition in any temperature of 1673−1873 K can be obtained from the database.…”

Section: ■ Experimental Sectionmentioning

confidence: 99%

Viscosity Estimation of Multicomponent Slags of the CaO–SiO₂–Al₂O₃–Fe_xO System Based on Microstructure Analysis

et al. 2020

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Slag viscosity is key factor of liquid steel refining and the smooth slag tapping of entrained flow coal gasifiers, and the accurate estimation of slag viscosity can provide a guidance for the selection of industrial raw material and the control of industrial process. In this study, a structure-related viscosity model about the multicomponent slags of the CaO−SiO 2 −Al 2 O 3 −Fe x O system is developed based on the flow mechanism of silicate melt to improve slag viscosity behavior. The present estimation model improved the expression of activation energy equation on the basis of the model proposed by Nakamoto and expanded the application from the ternary CaO−SiO 2 −Al 2 O 3 system to the quaternary CaO−SiO 2 −Al 2 O 3 −Fe x O system. Then, the structural roles of all the components were clarified, and the types of oxygen bonds were defined by Raman spectroscopy. The fractions of various oxygen bonds were obtained, and the database of oxygen bonds in any composition within the range of experimental slags was generated by utilizing the Lagrange interpolation method. The result showed that the present model had an advantage in estimating slag viscosity within the compositional range of this experiment slag, and the mean deviations between the viscosities calculated by the present model and measured or published viscosities were within 20%. The model will offer a reference for the estimation and adjustment of slag behavior in the metallurgical slag or coal slag, especially for the iron-rich system.

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“…The representation of the structural parameters can be done by the notation Q n where n is the number of bridging oxygen [65] corresponding to the pair Q 0 -SiO4 4-, Q 1 -Si2O7 6-, Q 2 -SiO3 2e Q 3 -Si2O5 2- [66]. The interaction between structural parameters Q n can modify the structure of a chemical system, as demonstrated by Equation 18.…”

Section: Mo2 Oxidesmentioning

confidence: 99%

Viskositas: Viscosity Prediction of Multicomponent Chemical Systems

dos¹

2022

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Viscosity in the metallurgical and glass industry plays a fundamental role in its production processes, also in the area of geophysics. As its experimental measurement is financially expensive, also in terms of time, several mathematical models were built to provide viscosity results as a function of several variables, such as chemical composition and temperature, in linear and nonlinear models. A database was built in order to produce a nonlinear model by artificial neural networks by variation of hyperparameters to provide reliable predictions of viscosity in relation to chemical systems and temperatures. The model produced named Viskositas demonstrated better statistical evaluations of mean absolute error, standard deviation and coefficient of determination (R 2 ) in relation to the test database when compared to different models from literature and 1 commercial model, offering predictions with lower errors, less variability and less generation of outliers.

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The Temperature and Structure Dependence of Surface Tension of CaO-SiO2-Na2O-CaF2 Mold Fluxes

Cited by 15 publications

References 29 publications

Structural Evolution of Molten Slag during the Early Stage of Basic Oxygen Steelmaking

Structural Evolution of Molten Slag during the Early Stage of Basic Oxygen Steelmaking

Viscosity Estimation of Multicomponent Slags of the CaO–SiO₂–Al₂O₃–Fe_xO System Based on Microstructure Analysis

Viskositas: Viscosity Prediction of Multicomponent Chemical Systems

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The Temperature and Structure Dependence of Surface Tension of CaO-SiO2-Na2O-CaF2 Mold Fluxes

Cited by 15 publications

References 29 publications

Structural Evolution of Molten Slag during the Early Stage of Basic Oxygen Steelmaking

Structural Evolution of Molten Slag during the Early Stage of Basic Oxygen Steelmaking

Viscosity Estimation of Multicomponent Slags of the CaO–SiO2–Al2O3–FexO System Based on Microstructure Analysis

Viskositas: Viscosity Prediction of Multicomponent Chemical Systems

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Product

Resources

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Viscosity Estimation of Multicomponent Slags of the CaO–SiO₂–Al₂O₃–Fe_xO System Based on Microstructure Analysis