Interaction of elements in dilute Mg alloys: a DFT and machine learning study

A Machine Learning Enabled Ultra-Fine Grain Design Strategy of Mg-Mn-Based Alloys

“…In addition, compared to most algorithms, the decision tree model is not a complete black box; the decision tree nodes can be computed, and a tree diagram can show the whole classified workflow. Because of this advantage, the decision tree model is often used to find classification criteria and routes [37,38,60]. Therefore, we visualized the decision tree model in the next part to further explore paths to prepare ultrafine grains.…”

Effects of Alloying Elements on the Dissolution and Precipitation Behaviour of Fe in Mg-Al Alloy Melts

“…Our previous study successfully resulted in the Ni in the Mg material being below 5 ppm using a directional solidification purification method [25]. As Fe impurities are inevitably incorporated into the Mg alloys during the commercial melting and casting process, the Fe solution in the Mg alloys and the effects from Fe on the properties of Mg alloys have been studied for a long time [18][19][20][21][22]. Based on the current available synthesizing process, many micro-alloying methods have been proposed and have been proven to be successful strategies for Fe removal in Mg alloys [29][30][31][32][33].…”

“…It has been experimentally observed that there is a tolerance limit for the content of Fe in the Mg alloys, and the corrosion rate can be rapidly increased if the content of Fe is higher than the tolerance limit, where it is later found the theoretical description of the tolerance limit is the thermodynamic equilibrium critical point for the Fe situated in the proper phases [33]. Especially, the detailed tolerance values of impurity Fe in the Mg-Al based alloys are important for the Al-containing Mg-based system, because the presence of Al will combine RE or Zr to form compounds and counteract the purification effects of Rare-earth elements and Zr [18,21].…”