journal article·2025-12Open access

In Situ CT of Clinch Points – Enhancing Interface Detectability Using Electroplated Patterns of Radiopaque Materials

Daniel Köhler, Alrik Dargel, Juliane Troschitz, Maik Gude, Robert Kupfer

Abstract

Abstract A clinch point’s quality is usually assessed using ex situ destructive testing methods. These, however, are unable to detect phenomena immediately during the joining process. For instance, elastic deformations reverse and cracks close after unloading. In situ methods such as the force-displacement evaluation are used to investigate a clinching process, though deviations in the clinch point geometry cannot be derived with this method. To overcome these limitations, the clinching process can be investigated using in situ computed tomography (in situ CT). When investigating the clinching of aluminum parts in in situ CT, the sheet-sheet interface is hardly visible. Earlier investigations showed that radiopaque materials can be applied between the joining parts to enhance the detectability of the sheet-sheet interface. However, the layers cause strong artefacts, break during the clinching process or change the clinch joint’s properties significantly. In this paper, a minimally invasive method to enhance the interface detectability is presented. First, the aluminum oxide layer is removed by etching. Second, the specimen is electroplated with copper or gold, respectively. In some cases, a mask is applied to create a cross-shaped plating pattern. Then, the plated specimen is clinched with a non-plated counterpart and the interface detectability of the clinch points is assessed in CT scans. It is shown that a copper plating of 2.6–4 μm can visualize some parts of the interface, while 7–9 μm is suitable to enhance the detectability of the sheet-sheet interface almost continuously.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced X-ray and CT Imaging · Electrical and Bioimpedance Tomography · Medical Imaging Techniques and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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