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Wednesday, 13 March 2013

Predicting charge transport in polycrystalline graphene

Reporting in Nano Letters, ICREA Prof Stephan Roche and colleagues describe a law to predict charge transport in polycrystalline graphene in function of grain and grain boundary morphology.

A team led by ICN Group Leader Stephan Roche and Professor Jani Kotakosi (University of Helsinki/University of Vienna) has just published an article in Nano Letters in which they report a law for predicting charge transport in polycrystalline graphene, which they formulated based on computer models of large graphene sheets grown by Chemical Vapour Deposition (CVD) (“Scaling Properties of Charge Transport in Polycrystalline Graphene”).

Graphene is a single layer of carbon atoms arranged in a perfect honeycomb pattern of hexagonal carbon rings. It has been touted as a “wonder material” for its unprecedented array of electronic, thermal, mechanical, optical and transport properties. However, the current methods for producing large sheets of graphene (at the 300 mm wafer scale), such as CVD, lead to a type of sample known as polycrystalline graphene, marked by various structural defects that strongly influence the properties of each sample.

In CVD, a graphene sheet is grown on a metallic substrate by simultaneously initiating nucleation of carbon atoms at different regions, and then allowing them to converge. Flawless areas of grown graphene are known as grains; the better the CVD, the larger the grain size (i.e. the greater the area free of defects).  Grain sizes can range from several tens of nanometers to several microns. Grains meet at areas known as boundaries, which are characterised by structural defects—namely, carbon rings having more or less atoms than the standard number of six.

Although scientists are not yet able to produce large graphene samples devoid of defects, they can accurately characterise the samples they have produced, meaning that if given the right predictive tools, they could predict the imperfect behaviour of an imperfect sample.

Prof Roche, Prof Kotakosi and their colleagues created complex computer models of large (up to the micron squared) graphene sheets, incorporating the typical grain sizes and imperfections found in real samples grown by CVD. They then modelled the charge mobility (the speed with which electric charge travels throughout a sample) in function of the grain size and the interfaces between the grains (i.e. the atomic structure of the boundaries).

As predicted, they found that larger grain size correlated to higher charge mobility; basically, that electricity travels faster through graphene with fewer defects. This scaling law held true over a range of typical grain sizes. They also found that the disorder scattering strength (the extent to which the structural defects compromise charge mobility) depends on the atomic structure of the grain boundaries as well as on wave function mismatch between the grains.

According to Prof Roche, “Our methods are not only useful for predicting the electronic behaviour of real graphene samples produced by CVD, they can also be used for determining the inherent limits of charge transport in polycrystalline graphene, which is of prime importance for applications in flexible electronics, touch panels, photovoltaics cells and so forth.”


The team currently plans to improve their predictive model by incorporating more complexity such as high temperature effects, additional sources of disorder, chemical functionalisation, etc.

To access the article “Scaling Properties of Charge Transport in Polycrystalline Graphene”, click here.