  This paper introduces a novel method for characterizing fracture mechanisms
in composite materials using 3D image data gained by 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 composite 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 geometallurgical
recycling processes. As primary deposits are decreasing worldwide, the focus is
shifting to secondary raw materials containing low concentrations of valuable
elements such as lithium. To extract these elements, they can be enriched as
engineered artificial minerals in the slag phase of appropriately designed
cooling processes. The subsequent liberation through comminution processes,
such as crushing, is essential for the extraction 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.
