Advanced metal alloys are in everything from cars to electronics, but creating new ones for specific uses isn’t always easy.
The problem is at the atomic level: at the boundaries between the crystalline grains that make up most metals. When two metals are mixed, the atoms of the secondary metal might collect along the boundaries or might spread through the lattice of atoms within the grains.
Exactly what they do largely determines the overall properties of the resulting material – things such as strength, hardness, corrosion resistance and conductivity – but it’s hard to know what that will be.
Researchers at Massachusetts Institute of Technology, US, may have now found a way, however. In a paper in Nature Communications, Christopher Schuh and colleagues describe using computer simulations and machine-learning to produce detailed predictions that could guide the development of new alloys for a wide variety of applications.
They also suggest that previous decisions to dismiss possible alloys might have been wrong.
Traditionally, Schuh says, engineers designing new alloys either skip over the issue or just look at the average properties of the grain boundaries as though they were all the same – even though they’re not.
His team decided to examine the actual distribution of configurations and interactions for a large number of representative cases, then use an algorithm to extrapolate from these specific cases to provide predicted values for a range of possible alloy variations.
They examined more than 200 combinations of a base metal and an alloying metal, based on those that had been described on a basic level in the literature, then simulated some of these compounds to study their grain boundary configurations.
These were used to generate predictions using machine learning, which were then validated with more focused simulations. The predictions were found to closely match the detailed measurements.
As a result, they say, they were able to show that many alloy combinations previously ruled out as unviable are in fact feasible.
The new database is now available in the public domain, and the researchers are forging ahead with their analysis.
“In our ideal world, what we would do is take every metal in the periodic table, and then we would add every other element in the periodic table to it,” Schuh says.
“So you take the periodic table, and you cross it with itself, and you would check every possible combination.”
For most of those combinations, basic data are not yet available, but as more and more simulations are done and data collected, this can be integrated into the new system, the researchers say.
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