Thermopower of multilayer graphene

TL;DR

This paper systematically calculates the thermopower in multilayer graphene systems, considering effects like screening, impurity scattering, and different models, revealing how bias and layer number influence thermoelectric properties.

Contribution

It provides a comprehensive analysis of thermopower in multilayer graphene, incorporating self-consistent screening and impurity effects, and compares different theoretical models.

Findings

Biased bilayer graphene exhibits the highest thermopower.

Energy gaps appear in biased and high-density unbiased trilayer and quad-layer graphene.

Impurity scattering is essential to replicate experimental results in monolayer graphene.

Abstract

We systematically calculate thermopower of biased and unbiased multilayer grphene systems. The effect of screening to a bias field perpendicular to the graphene planes is taken into account self-consistently under the Hartree approximation. The model including nearest neighbor hopping and the more complete Slonczewski-Weiss-McClure (SWMcC) model are both considered for a comparison. The effect of impurity scattering is studied for monolayer and unbiased bilayer graphene and is treated in terms of the self-consistent Born approximation. For a monolayer graphene, only when the effect of impurity scattering is taken into account, could all the qualitative aspects of the experimental results be correctly reproduced. A small energy gap opens for the biased trilayer graphene. When the carrier density is high enough, a gap is also found for unbiased trilayer and quad-layer graphene. The biased bilayer graphene shows the largest thermopower among all the systems studied.