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Fabrication of Gate-tunable Graphene Devices for Scanning Tunneling Microscopy Studies with Coulomb Impurities
Published on: July 24, 2015
Random resistor network model of minimal conductivity in graphene
Vadim V Cheianov1, Vladimir I Fal'ko, Boris L Altshuler
1Physics Department, Lancaster University, Lancaster, LA1 4YB, United Kingdom.
Physical Review Letters
|November 13, 2007
Summary
Transport in graphene arises from n- and p-type regions. Finite transparency of p-n junctions is crucial for conductivity, analyzed using a random resistor network model.
Area of Science:
- Condensed matter physics
- Materials science
Background:
- Undoped graphene exhibits complex transport due to bipolar charge density fluctuations, forming n- and p-type regions.
- The macroscopic conductivity of graphene is critically dependent on the transparency of the numerous p-n junctions present.
Purpose of the Study:
- To investigate the scaling dependencies of graphene's conductance.
- To analyze the impact of doping and disorder on transport properties.
- To study quantum magnetoresistance and dephasing rates in graphene.
Main Methods:
- Development of a random resistor network model.
- Analysis of percolating current patterns within n- and p-type regions.
- Modeling the finite transparency of p-n junctions.
Main Results:
- The study reveals that transport is governed by percolating current patterns.
- Finite p-n junction transparency is identified as a key factor for conductivity.
- The model allows for the analysis of conductance scaling with doping and disorder.
Conclusions:
- A random resistor network model effectively describes transport phenomena in undoped graphene.
- Understanding p-n junction transparency is essential for controlling graphene conductivity.
- The model provides insights into quantum magnetoresistance and dephasing in disordered graphene.
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