Briefs

The team's ultimate goal: a public online database that could aid the design of materials for almost any application, from nanostructure computer components to ultralight, high-strength alloys for airplanes.

Applied to a protein database containing "essentially all the known data on protein structure," Morgan said, data mining "assists researchers in exploring the structure, properties and functions of other proteins."

Now Morgan and colleagues have shown that data mining can also make the search for new materials easier. They describe their work in a recent paper in Physical Review Letters.

Authors are Stefano Curtarolo (Ph.D. 2003); Morgan; Gerbrand Ceder, the R.P. Simmons Professor of Computational Materials Science; Kristin Persson, an MIT postdoctoral associate when the work was conducted; and John Rodgers of Toth Information Systems in Canada. Curtarolo, now an assistant professor at Duke University, wrote his thesis on the work and is continuing to develop it in collaboration with his MIT colleagues.

The new MIT technique "establishes patterns among the many thousands of different possible structures" for a given mixture of materials, he said. "These patterns can then be used to greatly reduce the number of structures the computer has to explore."

To date, the MIT team has tested the technique on a relatively small homegrown database. Recently, however, they received funding from the National Science Foundation to produce a public online database "that will allow the whole computational materials community to contribute calculated data," Morgan said.

We believe this database and associated data-mining tools will become a standard tool for scientists studying new materials systems," Curtarolo concluded.

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