Mining for Molecules in the Milky Way

Clouds like this one are the raw material for new stars and planets. We know that complex chemistry builds prebiotic molecules in such clouds long before the stars and planets are formed. There is a good chance that some of these interstellar molecules may find their way to the surface of young planets such as the early Earth, and provide a head start for the chemistry of life. For the first time, we now have the capability to make a very thorough and methodical search to find all the chemicals in the clouds," said Anthony Remijan, of the National Radio Astronomy Observatory (NRAO).

In the past three years, Remijan and his colleagues have used the GBT to discover ten new interstellar molecules, a feat unequalled in such a short time by any other team or telescope.

The scientists discovered those molecules by looking specifically for them. However, they now are changing their strategy and casting a wide net designed to find whatever molecules are present, without knowing in advance what they'll find. In addition, they are making their data available freely to other scientists, in hopes of speeding the discovery process. The research team presented its plan to the American Astronomical Society's meeting in St. Louis, MO.

As molecules rotate and vibrate, they emit radio waves at specific frequencies. Each molecule has a unique pattern of such frequencies, called spectral lines, that constitutes a "fingerprint" identifying that molecule. Laboratory tests can determine the pattern of spectral lines that identifies a specific molecule.

Most past discoveries came from identifying a molecule's pattern in the laboratory, then searching with a radio telescope for that set of spectral lines in a region of sky. So far, more than 140 different molecules have been found that way in interstellar space.

The new study reverses the process. The astronomers will use the GBT to study a cloud of gas and dust in detail, finding all the spectral lines first, then later trying to match them up to molecular patterns using data-mining software.

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