Described in an upcoming issue of Phys. Rev. B (September 1, 2004), this method already has been used to virtually generate recipes for more than 1,700 structures, many of which have never before been analyzed.

The novel approach should prove valuable in guiding future bench testing and sparing countless hours of laboratory trial and error to generate amorphous metals.

Alloys for everyday materials like stainless steel are made by combining a metal with other elements. The resulting metals crystallize into lattices in which atoms line up in orderly arrangements.

Defects in these crystals inevitably weaken materials made from them, leading to fractures and corrosion.

Amorphous metals, otherwise known as metallic glass, lack these defects because they are disordered materials essentially frozen in place.

Consequently, they display remarkable corrosion resistance, strength and elasticity � the "spring-like" property coveted by tennis and golf champions.

Despite their promise, only small quantities of metallic glass have been generated to date because heated alloys require rapid cooling to freeze a glass into place.

Quick, uniform cooling of a large quantity of material is difficult, given that elements like to combine with one another in energetically favorable combinations, resulting in impurities that crystallize in an amorphous glass as it cools.

Using the new computational method, developed by Widom, scientists now can virtually predict what structures will crystallize out of an amorphous metal as it cools and how "spicing" a mixture with new elements prevents the emergence of these impurities.

Widom and his colleagues, including Yang Wang from the Pittsburgh Supercomputing Center, Marek Mihalkovic from the Slovakian Academy of Sciences and Don Nicholson from Oak Ridge National Laboratory, used powerful computing to systematically mix different amounts of elements in iron alloys and identify potential metallic glass compositions.

"Our method allows us to calculate energies associated with the formation of stable crystalline structures within these alloys," said Widom, a professor of physics.

These energies reflect the drive different element compositions have to crystallize out of an amorphous glass.

"We can identify an unstable mixture to quench into a glass, see what nearby structures are likely to crystallize out, and thwart their formation," he added.

Given this information, Widom then can virtually add new elements to an alloy recipe and see how they "confuse" the tendency of crystals to form.

"Metallic glass is not the most natural state to form as an alloy cools. To make it easy to form glass you want to rearrange things so that the crystalline alternatives are less likely to result," said Widom.

In work to date, Widom already has generated several potential glass alloy mixtures and has shown that "spicing" an iron alloy mixture with a small amount of the large element Yttrium facilitates metallic glass production.

Independent laboratory research at University of Virginia and at Oak Ridge National Laboratory confirms this finding.

"Ultimately, we would like to identify candidate mixtures that could be cooled in bulk to form novel metallic glasses," he said.

The new approach is sound, according to Widom, who has used it to propose structures for previously unsolved compounds and also has shown that it generates findings that match experimentally produced results, where they are available.

While this approach is highly promising to study iron-based metallic glasses that could be used in structures such as ship hulls, it also could be used to evaluate metallic glasses made from other alloys.

These include aluminum-based mixtures that could yield lightweight, stress-resistant metallic glasses for airplanes.

This research is supported by a three-year, $5.5 million grant from DARPA shared with others at University of Virginia, Oak Ridge National Laboratory and the Pittsburgh Supercomputing Center. All the data generated to date are available online at http://alloy.phys.cmu.edu

Related Links
Carnegie Mellon University
Pittsburgh Supercomputing Center
University of Virginia
Oak Ridge National Laboratory
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