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Early stages of cluster forming in Al-Mg-Si alloys

Tuesday (27.09.2016)
16:45 - 17:00
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Increasing world population, global warming and diminishing resources have led to high environmental awareness in society and industry. In the area of transportation, maximizing the energy efficiency of vehicles by lightweight design has gathered a lot of interest in recent years. A great potential for weight reduction is seen in aluminum based alloys, due to their good strength to weight ratio. However, they often show only limited formability relative to other alloys like steels. Since aluminum alloys are age-hardened one approach for improving formability in crack critical areas of a component is to expose the material locally to a short-term heat treatment. By this, the hardening clusters are locally dissolved and thus the necessary forming forces are significant lowered. Finally the material gains its former strength by natural ageing. Since the very early clusters have only sizes of about a few atoms and occur within minutes after natural aging, only methods with high spatial resolution are suitable to study the detailed processes in cluster coarsening. 3D atom probe tomography possesses a very high spatial resolution, however, the probing conditions in ultra high vacuum lead to relatively long transfer times, which make it difficult to study the early stages of natural aging.

In this contribution we present first atom probe tomography results of the extreme early stages of cluster formation during natural aging at room temperature in a commercial Al-Mg-Si alloy. By using an atom probe instrument equipped with a cryo-transfer system in the ScopeM facility at ETH in Zurich, it was possible to decrease transfer times drastically and thus reaching natural aging times of only a few minutes. By probing different natural aging stages from a few minutes up to several hours the evolution of cluster forming could be observed. The evolution of cluster coarsening, of cluster number density, of the chemical composition of the clusters and the nearest neighbor analyses are discussed in detail.


Dr. Julia Wagner
Karlsruhe Institute of Technology
Additional Authors:
  • Alexander Kahrimanidis
    Daimler AG
  • Dr. Stephan Gerstl
    ETH Zurich