A combined ionic and electronic electrical conductivity model for iron silicate slags

The transition towards a net zero emission society poses the metals industry with a twofold challenge of both increasing the production output while simultaneously decreasing its own CO2 emissions. To achieve both goals, more focus should be put on metals recycling, increasing the recycling yields and decarbonizing the existing technologies to do so. Current production technologies can be inefficient, leading to metal losses in the slag and significant CO2 emissions from burning coke for heat and as a reducing agent, particularly in blast furnaces. A potential solution to both problems is to utilize a submerged electric arc furnace (SAF) which functions both as a settling and reduction furnace. This furnace operates via Joule’s law in which heat is generated via the conversion of electricity via the slag’s resistance. As such, both the heat generation and the furnace’s temperature profile are highly dependent on the slag’s electrical conductivity. Electrical conductivity in iron silicate slags happens via both ion movement, the ionic conductivity, and via electron hopping between transition metal cations (Fe2+/Fe3+), the electronic conductivity. As a result, an overall electrical conductivity model needs to take into account both conduction mechanisms. In the present work, the ionic contribution is modelled via the Nernst-Einstein equation in which the mobility of the cations is expressed as a function of the slag’s structure, and can thus be linked to the slag composition and temperature. For the electronic conduction, an empirical expression for the electronic transference number as a function of the slag’s iron oxidation state is used. This model was then verified with several experimental datasets of quaternary SiO2-Al2O3-CaO-FeOx systems which showed that the model can estimate the available experimental data.