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A Sulphide Capacity Prediction Model of CaO–SiO2–MgO–Al2O3 Ironmaking Slags Based on the Ion and Molecule Coexistence Theory

机译:基于离子和分子共存理论的CaO–SiO 2 –MgO–Al 2 O 3 炼铁渣的硫化物容量预测模型

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A sulphide capacity prediction model of CaO–SiO_(2)–MgO–Al_(2)O_(3) ironmaking slags has been developed based on the ion and molecule coexistence theory (IMCT) and verified by two groups of sulphide capacity data of CaO–SiO_(2)–MgO–Al_(2)O_(3) ironmaking slags by different researchers. A hot metal pretreatment slags of CaO–SiO_(2)–MgO–Al_(2)O_(3) with high binary basicity is also applied to verify the feasibility of the developed IMCT model. The predicted sulphide capacity of CaO–SiO_(2)–MgO–Al_(2)O_(3) ironmaking slags at 1773 K as well as high alumina CaO–SiO_(2)–MgO–Al_(2)O_(3) ironmaking slags in a temperature range of 1773–1873 K by the developed IMCT model has higher accuracy than the measured as well as the predicted by other sulphide capacity prediction models. The calculated equilibrium mole numbers, mass action concentrations of structural units or ion couples and optical basicity are recommended to represent slag composition for correlating with sulphide capacity of the slags compared with mass percentage of components or binary slag basicity. The developed IMCT model can calculate not only the total sulphide capacity of the slags but also the respective sulphide capacity of free CaO and MgO in the slags. Largely increasing Al_(2)O_(3) content from 15 to 25% and decreasing CaO content from 40 to 34%, MgO content from 9 to 4% can improve contribution of free CaO from 97 to 99% while decreasing contribution of free MgO from 3 to about 1% to the total sulphide capacity of CaO–SiO_(2)–MgO–Al_(2)O_(3) ironmaking slags.
机译:基于离子分子共存理论(IMCT),建立了CaO–SiO_(2)–MgO–Al_(2)O_(3)炼铁渣的硫化物容量预测模型,并通过两组CaO的硫化物容量数据进行了验证–研究人员研究了–SiO_(2)–MgO–Al_(2)O_(3)炼铁炉渣。还使用具有高二元碱度的CaO–SiO_(2)–MgO–Al_(2)O_(3)的铁水预处理渣验证了开发的IMCT模型的可行性。 CaO–SiO_(2)–MgO–Al_(2)O_(3)炉渣在1773 K时的预测硫化物容量以及高氧化铝CaO–SiO_(2)–MgO–Al_(2)O_(3)炼铁的预测硫化物容量通过开发的IMCT模型在1773–1873 K温度范围内的炉渣具有比所测得的以及其他硫化物容量预测模型所预测的更高的精度。建议使用计算出的平衡摩尔数,结构单元或离子对的质量作用浓度和光学碱度来表示与成分的质量百分比或二元碱度相比,与熔渣的硫化能力相关的熔渣成分。开发的IMCT模型不仅可以计算炉渣的总硫化物容量,而且可以计算炉渣中游离CaO和MgO的各自的硫化物容量。 Al_(2)O_(3)含量从15%大幅增加到25%,CaO含量从40%降低到34%,MgO含量从9%降低到4%可以将游离CaO的贡献从97%提高到99%,同时减少游离MgO的贡献CaO–SiO_(2)–MgO–Al_(2)O_(3)炼铁渣的总硫化容量的3%到大约1%。

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