Oak Ridge National Laboratory (ORNL) is partnering with the Big Three U.S. automakers and foundry firm Nemak to develop a 300 °C capable, high-strength cast aluminum alloy to help vehicles achieve 54.5 miles per gallon by 2025.

This target means engineering a material that is 25% stronger than current alloys and durable at temperatures 50°C higher—a necessity for high-efficiency turbocharged engines—and to do this while keeping costs low for automotive manufacturers and consumers.

“Aluminum has been in mass-scale production for more than a century, but current cast aluminum alloys cannot withstand the temperatures required by new advanced combustion regimes,” says ORNL principal investigator Amit Shyam.

Researchers are using high-performance computing to speed development of high-temperature alloys for automotive cylinder heads. Image credit: ORNL.Researchers are using high-performance computing to speed development of high-temperature alloys for automotive cylinder heads. Image credit: ORNL.Researchers are using ORNL's integrated computational materials engineering (ICME)—the integration of materials information, captured in computational tools, with engineering product performance analysis and manufacturing-process simulation—to tailor new alloys at the atomic level to achieve desired properties such as strength and ease of manufacturability. In the race to meet the U.S. Environmental Protection Agency's fuel efficiency targets, ORNL is scaling ICME to run on the Energy Department’s Titan supercomputer, one of the world's fastest computers.

Using Titan’s speed and parallel processing power, ORNL researchers can predictively model new alloys and select only the best candidates for further experimentation. This predictive capability dramatically reduces the time, energy and resources devoted to casting trial alloys.

“Using approximately 100,000 cores simultaneously on Titan, we can increase the speed and scale of our first-principles quantum mechanics calculations by at least an order of magnitude,” says ORNL researcher Dongwon Shin.

Before the shift to Titan, Shin was using a Linux cluster with approximately 300 cores to create atomistic simulations of single elements diffusing to intermetallic precipitates within the alloy. Now researchers can achieve larger-scale simulations on Titan that are closer to real-world scenarios.

The team is also verifying the computational models through atomic-scale imaging and analytical chemistry measurements. ORNL’s scanning transmission electron microscopy and atom probe tomography allow researchers to identify and examine the location and chemistry of each atom in the alloy matrix, precipitates and the interfaces between them.

ORNL and collaborators are creating a database that captures their aluminum alloy materials discoveries. This materials genome approach will help guide efforts to improve ICME capabilities and accelerate the development of new high-performance materials.

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