Researchers have discovered a new class of extremely hard alloys using a novel method for finding new materials that combines data analytics and electron microscopy.
The materials—discovered by a team of engineers from Lehigh University—are strong enough that they could potentially withstand severe impact from projectiles, making one possible application as military armor for vehicles or soldiers, researchers said.
“These alloys sometimes possess unexpected and superior mechanical properties relative to those of conventional alloys as well as enhanced oxidation resistance and magnetic properties,” lead researcher Jeffrey M. Rickman, professor of materials science and engineering and physics at the university, told Design News.
|An X-ray energy-dispersive spectroscopy (EDS) map of the as-cast microstructure of a hard alloy predicted from Lehigh University researchers' analysis. Lettered panels are X-ray intensity maps associated with different elements comprising the alloy that permit deduction of the spatial distributions of these elements. (Image source: Lehigh University)|
Rickman and his team employed a fairly new method of materials discovery called materials informatics, or the application of the methods of data science to materials problems, he said. They combined this with experimental tools—including electron microscopy—to glean insight into the physical mechanisms leading to the observed behavior in the new class of materials, called high-entropy alloys (HEAs).
Specifically, researchers combined two complementary tools to screen HEAs and identify promising ones: a canonical-correlation analysis and a genetic algorithm with a canonical-correlation analysis-inspired fitness function.
They implemented this process using a database for which mechanical property information exists and highlighting new alloys with high hardnesses. They validated the methodology by comparing predicted hardnesses with alloys fabricated in a laboratory using arc-melting, identifying alloys with very high measured hardnesses.
“The methods used here identify those factors that are most correlated with the mechanical properties of the alloys in a database,” Rickman said. “Once these correlations are established quantitatively, one can then use a genetic algorithm to test candidate alloys based on these correlations.
HEAs are currently sought-after materials and the subject of much study by materials scientists because they contain numerous, disparate elements that—when combined—may result in materials with superior qualities like Rickman described.
"We thought that the techniques that we have developed would be useful in identifying promising HEAs," Rickman said. "However, we found alloys that had hardness values that exceeded our initial expectations. Their hardness values are about a factor of 2 better than other, more typical high-entropy alloys and other relatively hard binary alloys."
The team published a paper on their work in the journal Nature Communications.
Narrowing it Down
The specific value of the work by the Lehigh team is to demonstrate that the discovery process the team used is useful for identifying promising materials from a plethora of possibilities, Rickman said.
“These tools can be used in a variety of contexts to narrow large experimental parameter spaces to accelerate the search for new materials," he said.
The team plans to continue its work to use these techniques to identify promising alloys having other desirable properties beyond the ones examined in the current research, such as oxidation resistance, Rickman told Design News.
“This is possible as the methods are quite general,” he said. “We also aim to understand better mass transport, i.e., diffusion, in these complex alloys.”
Elizabeth Montalbano is a freelance writer who has written about technology and culture for more than 20 years. She has lived and worked as a professional journalist in Phoenix, San Francisco and New York City. In her free time she enjoys surfing, traveling, music, yoga and cooking. She currently resides in a village on the southwest coast of Portugal.
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