http://www.physorg.com/news100279584.html

Algorithm could help chipmakers work with tangles of nanotubes

by David Orenstein
Concerned that current methods for making computer chips might become
stymied as components keep shrinking, many engineers are looking for circuit
building blocks with improved electrical properties.
Among the most promising are stringy carbon nanotubes that capably form
transistors to switch current on and off. But the nanotubes tend to grow
with unpredictable kinks and bends that could cause bad wiring connections.
This week at the Design Automation Conference in San Diego, a group of
Stanford engineers will present a way to design circuits that should work
even when many of the nanotubes in them are twisted and misaligned.

"The question is what's next in chip technologies," says Subhasish Mitra, an
assistant professor of electrical engineering and computer science. "That's
why nanotechnology is important. But you want to make sure that you are not
in a lab making something that chip designers cannot actually use."

To prevent that, he and electrical engineering Professor H.-S. Philip Wong,
working with chemistry Professor Chongwu Zhou at the University of Southern
California, have been looking closely at how nanotubes end up resting on the
surfaces of experimental chips.

"It's not as bad as a plate of noodles," Mitra says. "You want to create
transistors out of these things, and hook up these transistors and make them
turn on and off independently. But if twisted carbon nanotubes, for example,
short out the circuit, you lose the opportunity to do that."

Making messy workable

What Mitra, Wong and graduate students Nishant Patil and Jie Deng have
realized is that if nanotubes are always going to be somewhat askew,
engineers will have to design circuits that can work regardless of where and
how the tubes lie. They started by coming up with a single circuit element,
a NAND gate, that was immune from the vagaries of its underlying nanotube
layout.

From that single element that could function despite misalignments, they
abstracted and generalized the math to come up with an algorithm that can
guarantee a working design for any circuit element, Mitra says, even when a
large number of nanotubes are misaligned.

Using simulations developed by Wong and Deng, the group has been able to
show that not only do the algorithm's designs work, but they also don't
appear to exact a significant financial, speed or energy price compared to
traditional designs, Mitra says.

The key to determining whether a circuit element is immune to nanotube
misalignment is breaking up each circuit element into a fine grid that can
be analyzed mathematically. Doing this in the abstract with models allows
engineers to determine which grid squares nanotubes must pass through and
which they shouldn't traverse to make a design work correctly. To eliminate
unwanted connections, nanotubes in so-called "illegal" regions can then be
either chemically etched away or rendered electrically irrelevant in other
ways.

The Stanford algorithm takes this all several steps further, applying
sophisticated mathematics to automatically determine where the legal and
illegal regions should be in the design of a circuit element with a
particular function.

"You not only determine whether something is immune or not, but can
automatically generate circuit designs that are guaranteed to be immune,"
Mitra says.

While the algorithm can overcome all the bad connections that errant
nanotubes make, it cannot guarantee that a nanotube will always make a
desired connection. Nanotubes also have other problems that remain unsolved,
Mitra points out. Some, for example, always conduct electricity instead of
switching on and off like a semiconductor should.

The group's next step is to move beyond simulation to build and test real
circuit elements according to the algorithm's output. While more work is
necessary to deliver the promise of nanotube technology, solving the
misalignment problem would be a significant step.

"Carbon nanotube transistors show great promise as extensions to silicon
transistors due to their fast speed, small size and lower energy
consumption," Patil says. "Using this technique, we can make larger and more
complex circuit blocks with them."

Wong speculates that the advance could eventually spill over from chips to
assist engineers facing analogous challenges.

"A similar methodology can be applied to many emerging technologies," he
says. "The concept of not having to define everything with high precision is
germane to engineering robust systems."

The Microelectronics Advanced Research Corporation supported the research.

Source: Stanford University
-- 

Ken

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