When water vapor meets metal, the resulting corrosion can lead to mechanical problems that harm a machine’s performance. Through passivation, it also can form a thin inert layer that acts as a barrier against further deterioration. Either way, the exact chemical reaction is not well understood on an atomic level, but that is changing thanks to environmental transmission electron microscopy (TEM), which allows researchers to directly view molecules interacting on the tiniest possible scale.
Predicting grain boundary segregation in magnesium alloys through simulations and machine learning
Magnesium alloys hold promise as a lightweight material to reduce weight in automobiles and transportation systems, but low formability and strength prevent widespread adoption. Researchers at the University of Michigan have developed a predictive model to aid magnesium alloy optimization to overcome these challenges.






