[Editors] MIT: Sales method pays off for materials scientists

[Elizabeth Thomson]

MIT News Office
Massachusetts Institute of Technology
Room 11-400
77 Massachusetts Avenue
Cambridge, MA  02139-4307
Phone: 617-253-2700
http://web.mit.edu/newsoffice/www

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MIT: Sales method pays off for materials scientists

--Data mining used to predict crystal structures
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For Immediate Release
WEDNESDAY, JULY 19, 2006
Contact: Elizabeth A. Thomson, MIT News Office
Phone: 617-258-5402
Email: thomson at mit.edu

or

Anne Trafton, MIT News Office
Phone: 617-253-7147
Email: trafton at mit.edu

PHOTO AVAILABLE


CAMBRIDGE, Mass.--The same computer methods used by online sales 
sites to suggest books to customers can help predict the crystal 
structures of materials, MIT researchers have found.

These structures are key to designing new materials and improving 
existing ones, which means that everything from batteries to airplane 
wings could be influenced by the new method.

The scientists report their findings in the July 9 online edition of 
Nature Materials.

Using a technique called data mining, the MIT team preloaded the 
entire body of historical knowledge of crystal structures into a 
computer algorithm, or program, which they had designed to make 
correlations among the data based on the underlying rules of physics.

Harnessing this knowledge, the program then delivers a list of 
possible crystal structures for any mixture of elements whose 
structure is unknown. The team can then run that list of 
possibilities through a second algorithm that uses quantum mechanics 
to calculate precisely which structure is the most stable 
energetically - a standard technique in the computer modeling of 
materials.

"We had at our disposal all of what is known about nature," said 
Professor Gerbrand Ceder of the Department of Materials Science and 
Engineering, leader of the research team. Ceder compared the database 
of crystal structures to the user database of an online bookseller, 
which can make correlations among millions of customers with similar 
interests. "If you tell me you've read these 10 books in the last 
year and you rate them, can I make some prediction about the next 
book you're going to like?"

The data-mining algorithm captures the physics of crystal structures 
in nature (provided by the preloaded database) and makes 
sophisticated correlations to generate an informed list of candidate 
structures based on historical knowledge. These candidate structures 
were previously assembled by scientists manually in a time-consuming 
and subjective process that often amounted to guesswork. The new 
algorithm, combined with a quantum mechanics algorithm, forms a 
two-pronged strategy that will make the process faster and more 
accurate.

Ceder's team of computational modelers can already determine, in the 
space of just a few days, atomic structures that might take months or 
even years to elucidate in the lab. In testing on known structures of 
just two elements, Ceder's group found the new algorithm could select 
five structures from 3,000-4,000 possibilities with a 90 percent 
chance of having the true structure among the five.

"It's all about probability and correlations," Ceder said. "Our 
algorithm gives us the crystal structure with a certain probability. 
The key was realizing we didn't need more than that. With a short 
list of candidate structures, I can solve the problem precisely with 
quantum mechanics."

According to Ceder, the new technique will enable a big leap forward 
in true computational design of materials with specific properties. 
For example, "If somebody wants to know whether a material is going 
to have the right bandgap to be a solar cell, I can't calculate the 
bandgap if I don't know the structure," he said. (Bandgap determines 
many properties such as electrical conductivity.)  "And if I 
calculate the bandgap using the wrong structure, I may have a totally 
irrelevant answer. Properties depend on structure."

Contributing to the work were graduate students Christopher Fischer 
and Kevin Tibbetts, both of materials science and engineering, and 
former postdoctoral associate Dane Morgan, now at the University of 
Wisconsin at Madison.

This work was funded by the National Science Foundation and the 
Institute for Soldier Nanotechnologies.

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Elizabeth A. Thomson
Assistant Director, Science & Engineering News
Massachusetts Institute of Technology
News Office, Room 11-400
77 Massachusetts Ave.
Cambridge, MA  02139-4307
617-258-5402 (ph); 617-258-8762 (fax)
<thomson at mit.edu>

<http://web.mit.edu/newsoffice/www>
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