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Use of computational thermodynamics software to determine the influence of CaO, FeO and SiO2 on hot metal dephosphorization efficiency
Journal of Materials Research and Technology ( IF 6.4 ) Pub Date : 2020-08-03 , DOI: 10.1016/j.jmrt.2020.07.036
Caio Vaccari Silva , Felipe Costa Broseghini , Eduardo Junca , Felipe Fardin Grillo , José Roberto de Oliveira

The properties of the mixtures used in hot metal dephosphorization, such as solid and liquid fraction phases, CaO and FeO activity and viscosity, are determinant for the process efficiency. The influence of these properties on hot metal dephosphorization were studied for CaO–FeO–SiO2 mixtures. The experiments were carried out at 1400 °C, in MgO-C crucibles, where the mixtures were added to the hot metal. Metal samples were taken at different times to measure the variation of phosphorus (P) content over time. The initial mixtures and final slags properties were determined by computational thermodynamics software FactSage 7.2. A parameter named Dephosphorization Factor (FDeP), that measures the efficiency of the initial mixtures and final slag, in hot metal dephosphorization was used. It was found that the FDeP presents a high correlation (R2) with the dephosphorization efficiency and can be used to predict which slag will be the most efficient.



中文翻译:

使用计算热力学软件确定CaO,FeO和SiO 2对铁水脱磷效率的影响

铁水脱磷中使用的混合物的性质(例如固相和液相部分的相,CaO和FeO活性和粘度)决定了工艺效率。研究了这些性质对CaO–FeO–SiO 2混合物的铁水脱磷的影响。实验是在1400°C的MgO-C坩埚中进行的,将混合物添加到铁水中。在不同时间采集金属样品,以测量磷(P)含量随时间的变化。初始混合物和最终矿渣的性质由计算热力学软件FactSage 7.2确定。名为脱磷因子(F DeP),用于测量初始混合物和最终矿渣在铁水脱磷中的效率。发现F DeP与脱磷效率具有高度相关性(R 2),可用于预测哪种炉渣将是最有效的。

更新日期:2020-08-03
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