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Daryl Chrzan is a member of the Electronic Materials Program at Lawrence Berkeley National Laboratory.

It can take three decades before a new alloy makes its way from a glimmer in a scientist's mind to,say, the body of an airplane. That's because the development of alloys requires years of experiments to characterize the materials' mechanical properties. But what if you could model those characteristics in a computer? UC Berkeley engineer Daryl Chrzan is doing just that. He uses computational materials science to predict the properties of materials from the bottom up. His research could impact fields as diverse as nanotechnology and aeronautics.

"The intent of our work is to start with the properties of atoms and predict the larger scale properties that we experience everyday," says Chrzan, a professor in the Department of Materials Science and Engineering.

The outer radius of a telescoping multi-walled carbon nanotube piston, seen in this transmission electron microscope image, is only 12.6 nanometers at its largest point, nearly 10,000 times thinner than a human hair. (courtesy Lawrence Berkeley National Laboratory)

Already, researchers use computational tools to gain insight into the optical and electronic properties of certain materials. Predicting the mechanical properties, how a piece of metal will bend, for example, is a much harder problem though. That's because the number of degrees of freedom of a typical solid, how many ways the atoms can move, is "enormous," Chrzan says. A typical cubic centimeter of a metal contains 10 to the 22nd (10 followed by 22 zeros) atoms. Storing even the initial conditions of those atoms would require more computer memory than exists in the world, he explains. The difficulty is compounded by the fact that the structure of a material is not symmetric--defects are what allow it to bend in the first place.

However, using supercomputers at Lawrence Berkeley National Laboratory's National Energy Research Scientific Computing Center (NERSC), Chrzan and his colleagues can run day-long calculations on the behavior of 400 or so atoms. Then they can begin to scale up those measurements and make general predictions about the material.

"We're trying to start at the nanoscale and move up," Chrzan says.

Indeed, Chrzan and graduate student Elif Ertekin have recently focused on carbon nanotubes, sheets of carbon atoms that resemble rolls of chicken wire fused at the seam. Many researchers, including UC Berkeley physicist Alex Zettl, are studying carbon nanotubes as key building blocks for nanodevices. For example, Zettl has demonstrated pistons and conveyor belts fashioned from nanotubes. Several years ago, Zettl built an electric nanomotor that's 300 times smaller than the diameter of a human hair.

A series of scanning electron microscope pictures of the spinning rotor of a nanomotor. The entire electric motor is about 500 nanometers across, 300 times smaller than the diameter of a human hair. (courtesy Zettl Research Group, Lawrence Berkeley National Laboratory and University of California at Berkeley)

"When I saw that motor, the first thing I wanted to know is how much torque you could get out of it," Chrzan says. "if the drive shaft is going to be a carbon nanotube, you need to determine how much torque a carbon nanotube can withstand."

Computational limitations restricted them to running the atomic-scale calculations on nanotubes of just 36 or so atoms around. But thanks to several formulas they've devised, they're now able to predict the torsional stiffness of "every carbon nanotube on the planet" regardless of its size.

"You can now model the rotation behavior of nanotubes that are larger than what's possible to compute directly using atomic scale calculations," Chrzan says. "But that's just the elastic response. It doesn't tell us how the tubes will deform plastically."

The mechanical properties of materials, including nanotubes, are not entirely dictated by the average properties of the material but rather the defects within it, he explains. In the case of nanotubes, these defects are tiny particles that move around on the rolled up sheet. Those defects, called dislocations, lead to plastic deformation of the material.

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"Again, we're developing a description of the energetics of the dislocations so we can go beyond the atomic scale in describing the properties of these defects," Chrzan says. "By doing that, we can explore the material's larger scale behaviors."

As Chrzan's techniques are proven out, they may become useful tools for nanoengineers selecting materials and designing devices on the smallest scale. Someday, they could even speed up the invention of brand new macroscale materials like aerospace alloys for high-performance applications.

"Making high quality alloys is something of a black art," Chrzan says. "The hope is computational materials science can help us speed up the process. We can now start to unravel mysteries at the atomic scale at just astounding levels of detail."

Daryl C. Chrzan's home page

Chrzan Computational Material Science Group

"Nanoscience's Master Mechanic" by David Pescovitz (ScienceMatter@Berkeley, Volume 2, Issue 11)

National Energy Research Scientific Computing Center (NERSC)

Zettl Research Group

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© 2006 UC Regents. Updated 6/1/06.