Collector-metal behaviour in the recovery of platinum-group metals from catalytic converters

A commercial pyrometallurgical process for the extraction of platinum-group metals (PGM) from a feedstock slag was analysed with the use of a model based on computational fluid dynamics. The results of the modelling indicate that recovery depends on the behaviour of the collector phase. A possible method is proposed for estimation of the rate at which PGM particles in slag are absorbed into an iron collector droplet that falls through it. Nanoscale modelling techniques (for particle migration or capture) are combined with a diffusion-controlled mass-transfer model to determine the iron collector droplet size needed for >95% PGM recovery in a typical process bath (70 mm deep) in a realistic time-scale (<1 h). The results show that an iron droplet having a diameter in the range 0.1–0.3 mm gives good recovery (>90%) within a reasonable time. This finding is compatible with published experimental data. Pyrometallurgical processes similar to that investigated should be applicable to other types of waste that contain low levels of potentially valuable metals.

Computational modelling-a key component in materials processing

Computational analysis software is now widely accepted as a key industrial tool for plant design and process analysis. This is due in part to increased accuracy in the models, larger and faster computer systems and better graphical interfaces that allow easy use of the technology by engineers. The use of computational modelling to test new ideas and analyse current processes helps to take the guesswork out of industrial process design and offers attractive cost savings. An overview of computer-based modelling techniques as applied to the materials processing industry is presented and examples of their application are provided in the contexts of the mixing and refining of lead bullion and the manufacture of lead ingots.