Tuesday, 17 March 2009

Silicon-organic hybrid material could speed Internet access

A newly developed silicon-organic hybrid material could be key to superfast, all-optical networks of the future, researchers say.

The material combines silicon with a small organic molecule called DDMEBT that enables light-to-light interactions due to its nonlinear properties.

Materials are said to exhibit a ‘nonlinear optical response’ if their properties are affected by the intensity of light, which in turn affect how the light propagates.

This nonlinear response enables the light-to-light interactions necessary for data processing in all-optical networks.

Because DDMEBT is difficult to flexibly structure into optical circuitry, the researchers have combined it with silicon technology.

Similar to how snowflakes during a heavy storm tend to fill all the gaps between bricks, the small DDMEBT molecules are deposited into gaps between separate silicon waveguides on an integrated optical circuit.

These slots measure only tens of nanometres wide and control the propagation of light beams.

“With pure silicon,” explained Lehigh University physicist Ivan Biaggio, "you can build waveguides that enable you to control light beam propagation, but you cannot get ultrafast light-to-light interaction.”

"We need higher-speed switching to achieve a higher bit rate. Organic materials can do this, but they are not terribly good for building waveguides that control propagation of tightly confined light beams."

"We have combined the two approaches," he said in a press release.

"We start from a silicon waveguide designed to guide the light between two silicon ridges. Then we use molecular beam deposition to fill the space between the ridges with the organic material [DDMEBT], creating a dense plastic with high optical quality and high nonlinearity where the light propagates.”

The resultant device is said to demonstrate the best all-optical demultiplexing rate yet recorded for a silicon-organic hybrid device.

Demultiplexing is the process of deciphering and splitting a combined signal into its component data streams.

More information is available from Lehigh University’s press release.

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