Researchers believe they now understand how graphene - a featureless, one-atom-thick sheet of carbon atoms - lying on an equally featureless iridium surface, self-created a kind of "muffin tin" that formed identically sized and spaced muffins out of applied iridium atoms. "At the outset," writes Sandia researcher Peter Feibelman, who devised the explanatory simulation published in Physical Review B, "this seemed quite a mystery." The mystery started in 2005, when German scientists discovered that a graphene flake lying atop an iridium crystal unexpectedly caused new iridium atoms, deposited atop the flake, to arrange themselves into evenly spaced cluster arrays. With both the iridium support layer and the graphene layer perfectly flat, how the iridium quantum dots formed was a puzzle. More so because the newly introduced iridium atoms form a moiré pattern (a regular, ordered array) atop the graphene instead of a planar second surface.
Feibelman's simulation suggests that in regions where half the graphene flake's carbon atoms sit directly above iridium atoms of the underlying crystal, iridium atoms added on top of the graphene flake make it buckle. These regions do not occur randomly, and in fact form the regular array needed to explain the nanodot moiré pattern.
The buckling weakens tight links between the graphene's neighboring carbon atoms, freeing them to attach to the added iridium atoms. Furthermore, buckling not only allows the carbon atoms that buckle upward to capture deposited iridium atoms, but also causes the carbon atoms that buckle down to attach firmly to the metal below.
This orderly nanoscopic arrangement could have numerous applications, Feibelman says. "The rigorous periodicity of the nanodot arrays is a huge advantage compared to amorphous or 'glassy' arrangements where everything has to be described statistically," he explained. For example, similar quantum dot arrangements on graphene could keep information packets separate and "addressable" for data storage, or provide a ready-made environment for quantum computing.
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Source: Sandia National Laboratories
Pic courtesy Randy Montoya
