System Bits: August 13

Analyzing ad hoc networks; nanomanufacturing boost.

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Analyzing ad hoc networks
Now that the basic protocols of the Internet are more than 30 years old, network scientists are increasingly turning attention to ad hoc networks in which communications networks set up, on the fly, by wireless devices. Here, unsolved problems still abound.

Most theoretical analyses of ad hoc networks have assumed that the communications links within the network are stable. But that often isn’t the case with real-world wireless devices — as anyone who’s used a cellphone knows.

Recently, researchers from the Theory of Distributed Systems Group at MIT’s Computer Science and Artificial Intelligence Laboratory presented a new framework for analyzing ad hoc networks in which the quality of the communications links fluctuates. Within that framework, they provide mathematical bounds on the efficiency with which messages can propagate through the network, and they describe new algorithms that can achieve maximal efficiency.

In the past, some researchers have tried to model the unreliability of network links as random fluctuations. But if real randomness is assumed, then the randomness can be counted on. Somehow that can be used in the algorithm and maybe randomness itself is giving an assumption that’s too strong, the researchers suggested.

Instead, the MIT researchers modeled the fluctuations in the links’ quality as the willful manipulations of an “adversary,” which can’t control all the links in the network: Some will remain up throughout the execution of the communication algorithm. But the bandwidth of the others can be changed at will, and the network designer doesn’t know in advance which links are reliable and which aren’t.

The algorithm needs to work for all possible adversaries, some of which are benign and some of which might be doing the worst possible thing for the algorithm. In the new research, they weakened the adversary significantly.

Nanomanufacturing gets a boost
Using a technique with potential applications in nanoelectronics, optoelectronics and bioengineering, Georgia Tech researchers have ‘painted’ the Mona Lisa on a substrate surface approximately 30 microns in width. They believe the technique could potentially be used to achieve nanomanufacturing of devices because the team was able to vary the surface concentration of molecules on such short-length scales.

The image was created with an atomic force microscope and a process called ThermoChemical NanoLithography (TCNL). Going pixel by pixel, the Georgia Tech team positioned a heated cantilever at the substrate surface to create a series of confined nanoscale chemical reactions. By varying only the heat at each location, the researchers controlled the number of new molecules that were created. The greater the heat, the greater the local concentration. More heat produced the lighter shades of gray, as seen on the Mini Lisa’s forehead and hands. Less heat produced the darker shades in her dress and hair seen when the molecular canvas is visualized using fluorescent dye. Each pixel is spaced by 125 nanometers.

Georgia Tech researchers have created the "Mini Lisa" on a substrate surface approximately 30 microns in width. The image demonstrates a technique that could potentially be used to achieve nano-manufacturing of devices because the team was able to vary the surface concentration of molecules on such short length scales.  Source: Georgia Tech

Georgia Tech researchers have created the “Mini Lisa” on a substrate surface approximately 30 microns in width. The image demonstrates a technique that could potentially be used to achieve nano-manufacturing of devices because the team was able to vary the surface concentration of molecules on such short length scales. Source: Georgia Tech

 

By tuning the temperature, the team manipulated chemical reactions to yield variations in the molecular concentrations on the nanoscale. The spatial confinement of these reactions provides the precision required to generate complex chemical images like the Mini Lisa.

Production of chemical concentration gradients and variations on the sub-micrometer scale are difficult to achieve with other techniques, despite a wide range of applications the process could allow. The Georgia Tech TCNL research collaboration produced chemical gradients of amine groups, but expects that the process could be extended for use with other materials.

They envision TCNL will be capable of patterning gradients of other physical or chemical properties, such as conductivity of graphene.

~Ann Steffora Mutschler