Abstract

This paper introduces a novel method for characterizing fracture mechanisms in multi-component materials using 3D image data gained by X-ray computed tomography (CT) measurements. In mineral liberation, the understanding of these mechanisms is crucial, particularly whether fractures occur along the boundaries of mineral phases (intergranular fracture) and/or within mineral phases (transgranular fracture). Conventional techniques for analyzing fracture mechanisms are focused on globally comparing the surface exposure of mineral phases extracted from image measurements before and after fracture. Instead, we present a virtual reassembling algorithm based on image registration techniques, which is applied to 3D data of multi-component materials before and after fracture in order to determine and characterize the individual fracture surfaces. This enables us to conduct a local quantitative analysis of fracture mechanisms by voxelwise comparing adjacent regions at fracture surfaces. A quantitative analysis of fracture mechanisms is especially important in the context of recycling processes. As primary deposits are decreasing worldwide and the focus is shifting on reducing wast, the interest in secondary raw materials has increased. However, lower-concentrated, but valuable materials are often overlooked in recycling routes designed for higher-concentration materials and dissipate. Therefore, efforts are being made to enrich valuable elements, such as lithium, as engineered artificial minerals through pyrometallurgical processes. The subsequent liberation through comminution processes, such as crushing, is essential for the recovery of valuable minerals. A better understanding of crushing processes, especially fracture mechanisms in slags, is crucial for the success of recycling. The reassembling algorithm presented in this paper is evaluated through a simulation study, followed by an application to a naturally occurring ore and a slag resulting from a recycling process.

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