Electron microscopy enables study of individual atoms in graphene

22 Nov 2012

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Electron microscopy at the Department of Energy's Oak Ridge National Laboratory is providing unprecedented views of the individual atoms in graphene, offering scientists a chance to unlock the material's full potential for uses from engine combustion to consumer electronics.

Graphene crystals were first isolated in 2004. They are two-dimensional (one-atom in thickness), harder than diamonds and far stronger than steel, providing unprecedented stiffness, electrical and thermal properties. By viewing the atomic and bonding configurations of individual graphene atoms, scientists are able to suggest ways to optimise materials so they are better suited for specific applications.

In a paper published in Physical Review Letters, a team of researchers from Oak Ridge National Laboratory and Vanderbilt University used aberration-corrected scanning transmission electron microscopy to study the atomic and electronic structure of silicon impurities in graphene.

"We have used new experimental and computational tools to reveal the bonding characteristics of individual impurities in graphene. For instance, we can now differentiate between a non-carbon atom that is two-dimensionally or three-dimensionally bonded in graphene. In fact, we were finally able to directly visualise a bonding configuration that was predicted in the 1930s but has never been observed experimentally," said ORNL researcher Juan-Carlos Idrobo. Electrons in orbit around an atom fall into four broad categories - s, p, d and f - based on factors including symmetry and energy levels.

"We observed that silicon d-states participate in the bonding only when the silicon is two-dimensionally coordinated," Idrobo said. "There are many elements such as chromium, iron, and copper where the d-states or d-electrons play a dominant role in determining how the element bonds in a material."

By studying the atomic and electronic structure of graphene and identifying any impurities, researchers can better predict which elemental additions will improve the material's performance.

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