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The improvement of mixing conditions in vacuum refining unit plays an important role in enhancing the purity and decarburization of molten steel. A numerical simulation is established to calculate the transport and mixing process of tracers in a water model of Single‐Snorkel Refining Furnace. The results show that the transport process of tracer in water model consists of one main circulation stream (inside the ladle and the vacuum chamber) and two side circulation streams (inside the ladle). The injection of KCl tracer can enhance the downward stream velocity and the stream deviates to the axial center of the ladle. After a while (about 30 s), the downward stream gradually returns to the state when the tracer is not injected. The difference between the transport process of pure water tracer and KCl solution tracer is that the KCl solution tracer flows downward at a higher pace from the vacuum chamber to the bottom of the ladle and later disperses rapidly from the bottom to the nozzle‐located side wall of the ladle. The upward transport process of KCl tracer is slowed down due to the existence of “dead zone” at the bottom of the nozzle‐located side wall of the ladle.

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Intensive heat and mass transfer between continuum fluids and discrete particulate materials occur in the current working-horse blast furnace (BF) inronmaking process. To optimize the operation, its energy efficiency and sustainability, discrete particle models are very helpful when they are incorporated with flow, heat and mass transfer, and chemical reaction models. Here, a transient discrete element method-based virtual BF model is developed through scaling. The scaled model can simulate the process significantly faster and makes it practical to track the whole process of iron ore reduction from burden charge to the cohesive zone. The model is applied to an experimental BF and the predictions are tested against available experimental results and those of computational fluid dynamics models. The results demonstrate that the scaled virtual BF model can reasonably predict in-furnace flow state, temperature distribution, iron ore reduction and the characteristics of the cohesive zone. The particle scale BF model can provide detailed information of particle motion, temperature and chemical reactions, enabling fundamental understanding and further optimization and control of the process. The scaled BF model can be extended to study the effects of raw material properties and operation parameters on BF performance.

The (H2dabco)[Na(BF4)3] undergoes a static-to-dynamic phase transition at 403/386 K. Crystal structure analysis reveals that H2dabco2+ and/or BF4− undergo disordering.

Reversible phase transitions in [C3H4NS]2[KCo(CN)6] exhibit switch-type dielectric transitions around 210 K and 237 K. The small displacements and/or thermal vibrations of the cations cause the phase transitions.