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Quantum Field Theoretical Approach to the Electrical Conductivity of Graphene

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Internet of Things, Smart Spaces, and Next Generation Networks and Systems (ruSMART 2016, NEW2AN 2016)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 9870))

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Abstract

The longitudinal and transverse electrical conductivities of graphene are calculated at both zero and nonzero temperature starting from the first principles of thermal quantum field theory using the polarization tensor in (2+1)-dimensional space-time. An expression for the universal conductivity of graphene found previously using different phenomenological approaches is confirmed. Both exact and approximate asymptotic expressions for the real and imaginary parts of the conductivity of graphene are derived and compared with the results of numerical computations. The obtained results can be used in numerous applications of graphene, such as in optical detectors, transparent electrodes and nanocommunications.

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Authors and Affiliations

  1. Central Astronomical Observatory at Pulkovo of the Russian Academy of Sciences, St. Petersburg, 196140, Russia

    Galina L. Klimchitskaya & Vladimir M. Mostepanenko

  2. Institute of Physics, Nanotechnology and Telecommunications, Peter the Great Saint Petersburg Polytechnic University, St. Petersburg, 195251, Russia

    Galina L. Klimchitskaya, Vladimir M. Mostepanenko & Viktor M. Petrov

Authors
  1. Galina L. Klimchitskaya
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  2. Vladimir M. Mostepanenko
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  3. Viktor M. Petrov
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Corresponding author

Correspondence to Viktor M. Petrov .

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Editors and Affiliations

  1. Tampere University of Technology , Tampere, Finland

    Olga Galinina

  2. FRUCT Oy , Helsinki, Finland

    Sergey Balandin

  3. Tampere University of Technology , Tampere, Finland

    Yevgeni Koucheryavy

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Klimchitskaya, G.L., Mostepanenko, V.M., Petrov, V.M. (2016). Quantum Field Theoretical Approach to the Electrical Conductivity of Graphene. In: Galinina, O., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. ruSMART NEW2AN 2016 2016. Lecture Notes in Computer Science(), vol 9870. Springer, Cham. https://doi.org/10.1007/978-3-319-46301-8_61

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  • DOI: https://doi.org/10.1007/978-3-319-46301-8_61

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46300-1

  • Online ISBN: 978-3-319-46301-8

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