In situ conductometry for studying the homogenization of Al-Mg-Si alloys and predicting extrudate grain structure through machine learning

This dataset includes the in situ impedance and time/temperature data from [1], grain structure data created by extrusion simulation coupled with physically-based microstructural simulation [2], and the predictions of the feed-forward neural network GRAINN-1/2 [1].

[1] Österreicher, J. A., Zivanovic, D., Walenta, W., Maimone, S.,Hofbauer, M., Hovden, S., Tükör, Z., Arnoldt, A., Cerny, A. Kronsteiner, A., Antic, M., Zickler, G., Ehmeier, F., Mikulovic, M., Kunschert, G. (2024) . In situ conductometry for studying the homogenization of Al-Mg-Si alloys and predicting extrudate grain structure through machine learning. Materials & Design, 113070.

[2] Hovden, S., Kronsteiner, J., Arnoldt, A., Horwatitsch, D., Kunschert, G., & Österreicher, J. A. (2024). Parameter study of extrusion simulation and grain structure prediction for 6xxx alloys with varied Fe content. Materials Today Communications, 38, 108128.