MSE 2024
Lecture
26.09.2024
Quantifying slip, twinning and grain boundary sliding in zinc coatings for over 500 grains
DK

Dennis König (M.Sc.)

Eindhoven University of Technology

König, D. (Speaker)¹; Hoefnagels, J.¹; Mornout, C.¹; Slokker, G.-J.¹; Vermeij, T.²
¹Eindhoven University of Technology; ²Swiss Federal Laboratories for Materials Science and Technology (EMPA), Thun (Switzerland)
Vorschau
22 Min. Untertitel (CC)

The steel industry utilizes zinc coatings in order to protect their products from the corrosive environment and thus ensure the longevity of the work piece. Zinc is a HCP crystal with an inherently brittle and anisotropic nature, which leads to an early failure of the coating. Understanding the plasticity of the zinc coatings can therefore help to guide the industry to adjust the processing parameters to avoid early failure during the forming processes.

In this study we investigated the plasticity of a zinc coating in great detail, by using SEM-DIC and EBSD. The skin passed zinc coating consists of a collection of zinc grains varying from a 100 µm down to 10 µm, which results in a complex plasticity behaviour. We apply an InSn speckle pattern to receive a DIC resolution in the order of 40 nm. In combination with the crystal orientation (obtained through EBSD) we are able to determine the active slip systems, with a new methodology called SSLIP [1]. We also demonstrate that the SSLIP methodology can be modified in order to determine deformation twinning systems and also the activity of grain boundary sliding. The determination of all the different plastic mechanisms was performed on over 500 grains.

The large number of analysis is used to study the relationship between different properties on a stochastic scale. Our studies reveal correlations between different parameters, such as crystal (mis)orientation, grain boundary sliding direction & magnitude, slip systems etc. and thus allows us to understand the deformation of zinc coatings in great detail.

References

[1] Vermeij, T., Peerlings, R. H. J., Geers, M. G. D., & Hoefnagels, J. P. M. (2023). Automated identification of slip system activity fields from digital image correlation data. Acta Materialia, 243, 118502.

Abstract

Abstract

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