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Cover of the 2007 Annual Report
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Cover of the 2007 College Directory
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PAST ANNUAL REPORTS

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David Anderson, Jerahmie Radder, Mike Frankowski, Jeremy Lore, Chris Clark, Andrew Herr, John Schmitt, Walter Guttenfelder, Kan Zhai, Alexis Briesemeister, Konstantin Likin, Simon Anderson, Jane Lu and Joe Talmadge.

From left, back row: Professor David Anderson, graduate student Jerahmie Radder, Associate Instrumentation specialist Mike Frankowski, and graduate students Jeremy Lore, Chris Clark and Andrew Herr. Middle: graduate students John Schmitt and Walter Guttenfelder, Assistant Scientist Kan Zhai, graduate student Alexis Briesemeister and Scientist Konstantin Likin. Front: Associate Scientist Simon Anderson, graduate student Jane Lu and Associate Scientist Joe Talmadge. (Large image)

Electrical and Computer Engineering

The quasi-symmetrical stellarator:
A step forward for plasma research

A project by UW-Madison researchers has come one step closer to making fusion energy possible. The team, headed by Electrical and Computer Engineering Professor David Anderson and Research Assistant John Canik, recently proved that the Helically Symmetric eXperiment (HSX), a magnetic plasma chamber called a stellarator, can overcome a major barrier in plasma research: stellarators lose too much energy to reach the high temperatures needed for fusion.

The HSX is the first stellarator to use a quasi-symmetric magnetic field. The reactor itself looks futuristic: Twisted magnetic coils wrap around the warped-doughnut-shaped chamber, with instruments and sensors protruding at odd angles. However, the semi-helical coils that give the HSX its unique shape also direct the strength of the magnetic field, confining the plasma in a way that helps it retain energy.

The team designed and built the HSX with the prediction that quasisymmetry would reduce energy loss, or transport. As the team’s latest research shows, that’s exactly what it does. “You can actually measure the reduction in transport that you get,” says Canik.

The next step for the project is to establish how much symmetry in the coils is necessary for low transport rates. They hope to make the coils easier to engineer, with the mindset that the principles used in the HSX someday could be incorporated into fusion generators, the reason that Anderson and his team began designing the HSX 17 years ago.

“It’s an exciting field. It’s something where one can contribute positively to mankind with an energy source that’s completely sustainable, doesn’t involve nuclear proliferation or radioactive waste, with a limitless fuel supply,” says Anderson. “Plus, the machines look cool.”

Low temperatures provide a cool way to study tiny circuits

Lynn H. Matthias Professor Robert Blick’s method of studying single-electron devices isn’t just cool, it’s super-cool.

Blick and his research group are studying nanoscale electrical-mechanical systems (NEMS) at ultra-low temperatures, conditions that they hope will unlock the secrets of electron circuits.

NEMS are very tiny systems, confining a single electron with both electrical and mechanical degrees of freedom: charge and spin. However, within these degrees of freedom lies more complexity. Like light, electrons are simultaneously particles and waves, properties that programmers could manipulate if they can master them.

Blick and his colleagues can study these quantum mechanical properties by supercooling the NEMS to within thousandths of a degree of absolute zero, or about 459 degrees below zero on the Fahrenheit scale.

At these low temperatures, researchers can observe how single electrons move through circuits without the thermal noise generated at higher temperatures. Blick and his team hope not only to document the quantum mechanical properties, but also to manipulate them, enabling the circuit to store more information.

“Once we’ve identified how a single-electron circuit works, we can increase the temperature and see whether we can maintain the device operation at real ambient temperature conditions,” says Blick.

The UW-Madison group is unique in its use of silicon to fabricate the NEMS. Most researchers use gallium arsenide, because it traditionally has higher-quality samples. However, the industry standard for circuit manufacture is silicon, so Blick’s group committed to studying properties of circuits that could have greater market impact. “We’re working in extreme conditions, but it’s always focused on engineering circuits for the future,” says Blick.

Making the connection for cell-signaling networks

Though McFarland-Bascom Professor Robert Nowak initially developed a model that could trace telephone networks for intelligence purposes, he learned recently that he could apply it in an area outside of information technology. In collaboration with Genetics Professor Audrey Gasch, Robert Nowak is applying his model to a network that has long baffled biologists: cell protein signaling.

In living cells, networks of signaling proteins communicate information from the cell surface to the nucleus, prompting certain genes to turn “on” or “off.” Thus, cells can adapt to environmental changes. If scientists could understand and regulate this gene modulation, it could open new research opportunities into areas of human disease and cell growth, biosensor development and biofuel manufacturing.

Unfortunately, it is impossible to directly measure protein signaling interactions on a large scale in vivo. Current knowledge of cell-signaling networks is limited to datasets gathered by cell-study technology and theory based on knowledge of protein reactions. “With our technique, we can mine that data and look at it collectively from a network-centric perspective,” says Nowak.

Currently, scientists can determine which proteins are involved in a pathway, but not their order. By applying his network tomography model, Nowak can reconstruct cell signaling networks from genomic datasets and show the most likely sequence of proteins in a pathway. The model also can show how closely certain proteins interact. For example, if two proteins appear together in a number of pathways, they are more likely to operate closely in sequence. “Roughly speaking, cell-signaling networks are not very different from the telephone network or the Internet,” says Nowak.

Next, he hopes to optimize the model by augmenting information from genomic datasets with knowledge from other cell-study methods.

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