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

<p>This dataset includes the <em>in situ</em> 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].</p> <p>[1] &Ouml;sterreicher, J. A., Zivanovic, D., Walenta, W., Maimone, S.,Hofbauer, M., Hovden, S., T&uuml;k&ouml;r, 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. <em>Materials &amp; Design</em>, 113070.</p> <p>[2] Hovden, S., Kronsteiner, J., Arnoldt, A., Horwatitsch, D., Kunschert, G., &amp; &Ouml;sterreicher, J. A. (2024). Parameter study of extrusion simulation and grain structure prediction for 6xxx alloys with varied Fe content. <em>Materials Today Communications</em>, <em>38</em>, 108128.</p>