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Defect Structures and Electronic Properties of Graphene


Graphene and related materials have remarkable physical properties, such as high carrier mobilities. These properties provide many opportunities for applications, such as for novel high-speed microelectronics based on graphene rather than silicon. Experiments indicate the presence of defect structures in graphene that alter its electronic properties in potentially useful ways. Scanneling tunneling microscropy (STM) reveals characteristic patterns that distinguish one kind of defect but another, but do not directly show the atomic positions. Modeling has coevolved with experiment to solve the atomic structure of these defects. Using geometric principles to identify likely defect structures in graphene, and density functional theory electronic structure methods to simulate the STM images, the defects observed experimentally were matched to computational predictions and thus identified.

Defect Structures and Electronic Properties of Graphene
Figure: Experimental scanning tunneling microscopy (STM) images (left) for defects in graphene and corresponding simulated STM images (right). The defects shown have been identified as a rotational grain boundary (top) and divacancy (bottom).


Graphene, carbon in the form of a flat sheet, has remarkable physical properties, such as high mobility of charge carriers and large strength, that present many opportunities for applications. Defects in graphene decrease the high mobility of charge carriers in graphene; therefore, it is desirable to reduce or eliminate them. Conversely, one may desire to tune the properties of graphitic materials by intentionally creating and manipulating defect structures.

One class of defects, frequently observed in scanning tunneling microscope (STM) images of ultrahigh-vacuum graphene growth via Si desorption from SiC, exhibits regions, with diameters of order several nanometers, of strongly perturbed electronic structure completely surrounded by unperturbed graphene. The finite range of the electronic structure perturbation suggests that these defects could be created or healed by the motion of a relatively small numbers of atoms, and may therefore be among the most important defects in graphene. STM measurements show characteristic patterns demonstrating different defects, but are unable to show where the atoms are in each of these defects. For example, bright regions in the images could represent either the locations of atoms or the locations of strong bonds between atoms.

NIST researchers and external collaborators have combined experiment and computation to successfully identify where the atoms are in the observed defects. Modeling efforts showed how finite defects in graphene that preserve threefold carbon bonding can be systematically classified and enumerated, providing an endless variety of candidate defects to investigate. Density functional theory electronic structure computations were used to simulate the expected STM images of candidate defects under experimental conditions. Three of the simulated defects matched those observed in experimental samples: a twofold symmetric defect with a dumbbell shaped bright region in the center that is identified as a divacancy; a larger twofold symmetric defect that is identified as a double divacancy, and a sixfold symmetric “flower” defect that is identified as a patch of 24 carbon atoms rotated by 30 degrees. Remarkably, the “flower” defect was found to relieve stress in graphene under tensile stress, making graphene even stronger than was previously realized.

Major Accomplishments:

The reserachers have authored a pair of papers on topological defects in graphene [E. Cockayne et al., “Grain boundary loops in graphene”, Phys. Rev. B 83, 195425 (2011); E. Cockayne, “Graphing and grafting graphene: classifying finite topological defects”, Phys. Rev. B 85, 125409 (2012)], and their work was recognized on the cover image of the August 13, 2011 issue of Science News magazine.


Lead Organizational Unit:



Phillip First (Georgia Tech)
Gregory Rutter (Intel)
Nathan Guisinger (Argonne)
Jason Crain (U. Edinburgh)
Phone: (301) 975-4347
E-mail: eric.cockayne@nist.gov