Using supercomputers in the hunt for ‘cheapium’
January 6, 2014
In the search for cheaper materials that mimic their purer, more expensive counterparts, researchers are abandoning hunches and intuition for theoretical models and pure computing power.
In a new study, researchers from Duke University’s Pratt School of Engineering used computational methods to identify dozens of platinum-group alloys that were previously unknown to science but could prove beneficial in a wide range of applications.
Platinum is expensive, but it’s used to transform toxic fumes leaving a car’s engine into more benign gasses, to produce high octane gasoline, plastics and synthetic rubbers, and to fight the spread of cancerous tumors.
“We’re looking at the properties of ‘expensium’ and trying to develop ‘cheapium,’” said Stefano Curtarolo, director of Duke’s Center for Materials Genomics. “We’re trying to automate the discovery of new materials and use our system to go further faster.”
The research is part of the Materials Genome Initiative launched by President Barack Obama in 2011. The initiative’s goal is to support centers, groups and researchers in accelerating the pace of discovery and deployment of advanced material systems crucial to achieving global competitiveness in the 21st century.
The study appears in the Dec. 30 edition of the American Physical Society journal Physical Review X (open access) and is highlighted in a Viewpoint article in the same issue.
Databases and algorithms to screen thousands of potential materials
The identification of the new platinum-group compounds hinges on databases and algorithms that Curtarolo and his group have spent years developing. Using theories about how atoms interact to model chemical structures from the ground up, Curtarolo and his group screened thousands of potential materials for high probabilities of stability.
After nearly 40,000 calculations, the results identified 37 new binary alloys in the platinum-group metals, which include osmium, iridium ruthenium, rhodium, platinum and palladium.
These metals are prized for their catalytic properties, resistance to chemical corrosion and performance in high-temperature environments, among other properties. Commercial applications for the group include electrical components, corrosion-resistance apparatus, fuel cells, chemotherapy and dentistry. And because of their worldwide scarcity, each metal fetches a premium price.
Now it is up to experimentalists to produce these new materials and discover their physical properties.
In addition to identifying unknown alloys, the study also provides detailed structural data on known materials. For example, there are indications that some may be structurally unstable at low temperatures. This isn’t readily apparent because creating such materials is difficult, requiring high temperatures or pressures and very long equilibration processes.
“We hope providing a list of targets will help identify new compounds much faster and more cheaply,” said Curtarolo. “Physically going through these potential combinations just to find the targets would take 200 to 300 graduate students five years. As it is, characterizing the targets we identified should keep the experimentalists busy for 20.”
This research was supported by the DOD-ONR and the NSF.
Abstract of Physical Review X paper
We report a comprehensive study of the binary systems of the platinum-group metals with the transition metals, using high-throughput first-principles calculations. These computations predict stability of new compounds in 28 binary systems where no compounds have been reported in the literature experimentally and a few dozen of as-yet unreported compounds in additional systems. Our calculations also identify stable structures at compound compositions that have been previously reported without detailed structural data and indicate that some experimentally reported compounds may actually be unstable at low temperatures. With these results, we construct enhanced structure maps for the binary alloys of platinum-group metals. These maps are much more complete, systematic, and predictive than those based on empirical results alone.