A combined neural network and mechanistic approach for the prediction of corrosion rate and yield strength of magnesium-rare earth alloys
N Birbilis, MK Cavanaugh, AD Sudholz, SM Zhu… - Corrosion …, 2011 - Elsevier
Corrosion Science, 2011•Elsevier
Additions of Ce, La and Nd to Mg were made in binary, ternary and quaternary combinations
up to∼ 6wt.%. This provided a dataset that was used in developing a neural network model
for predicting corrosion rate and yield strength. Whilst yield strength increased with RE
additions, corrosion rates also systematically increased, however, this depended on the type
of RE element added and the combination of elements added (along with differences in
intermetallic morphology). This work is permits an understanding of Mg–RE alloy …
up to∼ 6wt.%. This provided a dataset that was used in developing a neural network model
for predicting corrosion rate and yield strength. Whilst yield strength increased with RE
additions, corrosion rates also systematically increased, however, this depended on the type
of RE element added and the combination of elements added (along with differences in
intermetallic morphology). This work is permits an understanding of Mg–RE alloy …
Additions of Ce, La and Nd to Mg were made in binary, ternary and quaternary combinations up to ∼6wt.%. This provided a dataset that was used in developing a neural network model for predicting corrosion rate and yield strength. Whilst yield strength increased with RE additions, corrosion rates also systematically increased, however, this depended on the type of RE element added and the combination of elements added (along with differences in intermetallic morphology). This work is permits an understanding of Mg–RE alloy performance, and can be exploited in Mg alloy design for predictable combinations of strength and corrosion resistance.
Elsevier
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