Abstract

Recovering scandium from hydrometallurgical residue bears the potential of a better supply of an industry depending on imports from countries with more mineral resources than Europe. To recover scandium from unused metal production residue, strip liquors from a solvent extraction process are treated with an antisolvent to crystallize the ammonium scandium fluoride salt (NH4)3ScF6 with high product yields. However, high local supersaturation leads to strong nucleation, resulting in small crystals, which are difficult to handle in the subsequent solid-liquid separation. Reducing local supersaturation makes it possible to reduce nucleation and control crystal growth. Key operation parameters are the concentration of ethanol in the feed and its addition rate. The concentration of the antisolvent in the feed causes a shorter mixing time in the proximity of the antisolvent inlet, which leads to a smaller local supersaturation and therefore less nucleation and more crystal growth. Lowering the antisolvent addition rate enhances this effect. The crystal size distribution during and at the end of the fed-batch process is analyzed by SEM imagery of sampled and dried crystals. To produce reproducible crystal size distribution from SEM images the neural network Mask R-CNN has been trained for the automated crystal detection and size analysis.

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