A workflow to assess the recoverability of secondary raw materials via physical separation

Printed circuit boards represent an extraordinarily challenging fraction for the recycling of waste electric and electronic equipment. Due to the closely interlinked structure of the composing materials, the selective recycling of copper and closely associated precious metals from this composite material is compromised by losses during mechanical pre-processing. This problem could partially be overcome by a better understanding of the influence of particle size and shape on the recovery of finely comminuted and well-liberated metal particles during mechanical separation. Here, we propose a workflow to quantify the role of the size and shape of such particles in various separation processes. As a case study, we compare an analytical heavy liquid separation to a new type of eddy current separator. Using X-ray computed tomography, we were able to distinguish metallic and non-metallic phases and determine the size and 3D microstructure of individual particles. For both separation processes, we trained a particle-based separation model that predicts the probability of individual particles to end up in the processing products. In particular, elongated particles were found to display a negative correlation between particle size and sphericity of metallic particles. In line with this correlation, the predicted metal recoveries are positively correlated with particle size but negatively correlated with sphericity in both separation processes. The suggested workflow is easily transferred to other recycling material systems. It allows to quantify the role of 3D geometrical particle properties in separation processes and provide robust predictions for the recoverability of different raw materials in complex recycling streams.