Exceptionally durable and hard metal alloys discovered with combination technique
Exceptionally durable and hard metal alloys discovered with combination technique lead image
Sarker et al. have discovered alloys that could revolutionize the world we live in. While made of cheap metals like iron and boron, the metallic glasses have three times the hardness of steel and wear-resistance rivaling commercial coatings. These alloys also promise strength-to-weight advantages comparable to carbon-reinforced composites but are cheaper to make and recycle.
“We need structural materials that are significantly superior to the current steels,” said author Apurva Mehta. “For instance, our ambition of net zero emission by 2050 will need a new generation of structural alloys that are stronger, lighter and last longer.”
Most of the widely used structural materials today, like steel, are single element alloys. Multi-element alloys could be superior, but as the number of principal elements in an alloy increases, the number of possible combinations grows exponentially.
To help narrow down the endless possibilities, Mehta and his group used machine learning to inform high throughput experiments. The method allowed the researchers to identify promising alloys in a fraction of the time it would take with experimentation alone.
“In material science, you cannot use traditional machine learning approaches. Taking just pure data driven approaches does not work because there’s not that much data and what is available is very biased,” Mehta said. “Additionally, generating new data is very expensive.”
The initial results are highly promising, Mehta said. The alloys’ use in all modes of transportation can massively increase fuel efficiency. Eventually the group hopes to find alloys that replicate diamond-like structural properties at a fraction of the price.
“These are exceptional alloys,” Mehta said. “And we have only just begun.”
Source: “Discovering exceptionally hard and wear-resistant metallic glasses by combining machine-learning with high throughput experimentation,” by Suchismita Sarker, Robert Tang-Kong, Rachel Schoeppner, Logan Ward, Naila Al Hasan, Douglas G. Van Campen, Ichiro Takeuchi, Jason Hattrick-Simpers, Andriy Zakutayev, Corinne E. Packard, and Apurva Mehta, Applied Physics Reviews (2022). The article can be accessed at https://doi.org/10.1063/5.0068207 .
This paper is part of the Autonomous (AI-driven) Materials Science Collection, learn more here .
