The exceptionally high mobility of carriers in graphene is one of its defining characteristics, especially in view of potential applications. Therefore it is of both practical and fundamental importance to understand the mechanisms responsible for li
miting the values of mobility. The aim of the paper is to study theoretically one such mechanism, i.e. scattering on ripples. The transport properties of rippled graphene are studied using using single-band tight-binding model. Both the bond-length variation, corresponding to the vector potential in the effective mass picture, and fluctuating scalar potential are included in the formalism. The samples are modeled as self-similar surfaces characterized by the roughness exponent with values ranging from typical for graphene on SiO$_{2}$ to seen in suspended samples. The range of calculated resistivities and mobilities overlaps with experiment. The results presented here support the notion of rippling as one of the factors limiting the mobility.
We present the formalism and demonstrate the use of the overlapping muffin-tin approximation (OMTA). This fits a full potential to a superposition of spherically symmetric short-ranged potential wells plus a constant. For one-electron potentials of t
his form, the standard multiple-scattering methods can solve Schr{o}dingers equation correctly to 1st order in the potential overlap. Choosing an augmented-plane-wave method as the source of the full potential, we illustrate the procedure for diamond-structured Si. First, we compare the potential in the Si-centered OMTA with the full potential, and then compare the corresponding OMTA $N$-th order muffin-tin orbital and full-potential LAPW band structures. We find that the two latter agree qualitatively for a wide range of overlaps and that the valence bands have an rms deviation of 20 meV/electron for 30% radial overlap. Smaller overlaps give worse potentials and larger overlaps give larger 2nd-order errors of the multiple-scattering method. To further remove the mean error of the bands for small overlaps is simple.
