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Nano-devices driven by noise: graphene based metamaterials and memristors
S.Savel’ev, Loughborough University UK
Graphene Memristor based memory
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Thanks for invitation
Prof. Alexander Gorban Dr. Ivan Tyukin
Looking forward for future collaboration
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Key collaborators Fabio Marchesoni (Physics Department, Univ. of Camerino, Italy) Peter Hanggi (University of Augsburg, Germany) Franco Nori (RIKEN, Japan; University of Michigan, USA) Feo Kusmartsev (Loughborough University, UK), Stanley Williams and Sasha Bratkovsky (Hewlett-Packard Laboratories,
Californiaity, USA), Sasha Alexandrov (Loughborough University, UK) Alex Zagoskin (Loughborough University, UK) Simon Bending (University of Bath, UK)
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Outline Graphene in space- and time-dependent potentials as metamaterial to comtrol electron transport. Relativistic Brownian motion on a graphene chip. Simulating memristors and future flash memory
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Graphene as metameterials
Such a transmission matrix approach is always used for optical photonic crystals. This allows us to compare transmission of Dirac electrons in periodic electrostatic potentials and electromagnetic waves in photonic crystals.
Phys. Rev. B 79, 075123 (2009).
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Graphene superlattices and Photonic crystals
Transmission coefficient for a) periodic graphene subject to an alternating potential, b) periodic L-R dielectric structure, and c) periodic R-R dielectric structure.
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Laser controlled graphene electronics
Massless Dirac fermions in a laser field as a counterpart of graphene superlattices S.E. Savel’ev and A.S. Alexandrov, Phys. Rev. B 84, 035428 (2011) Current Resonances in Graphene with Time-Dependent Potential Barriers S.E. Savel’ev, W. Häusler, P. Hänggi, Phys. Rev. Lett. 109, 226602 (2012)
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Graphene in a strong laser field as a counterpart of graphene superlattices
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Current resonances in graphene with time dependent potential barriers
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Current resonances in graphene
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Outline Graphene in spatial and temporal electrostatic potentials as metamaterial to comtrol electron transport. Relativistic Brownian motion on a graphene chip. Simulating memristors and future flash memory
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Transverse Ratchets in graphene
Potential along x, drive along y: no motion for classical systems and usually no motion for relativistic systems with no noise
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Geometry of the problem
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Transverse Ratchets in graphene Potential along x, drive along y: no motion for classical systems and no motion for relativistic systems with no noise
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Controlling signal-noise ratio by noise: no potential
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Outline Graphene in spatial and temporal electrostatic potentials as metamaterial to comtrol electron transport. Relativistic Brownian motion on a graphene chip. Simulating memristors and future flash memory
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Outline Graphene in spatial and temporal electrostatic potentials as metamaterial to comtrol electron transport. Relativistic Brownian motion on a graphene chip. Simulating memristors and future flash memory
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Switching of Memristors, HP-collaboration F. Miao, J.J. Yang, J.P. Strachan, D. Stewart, R.S. Williams, C.N. Lau Appl. Phys. Lett. 95, 113503 (2009)
APL 2011, APL 2011, Nanotechnology 2011, Applied Physics A 2011
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Switching of Memristors: simple model
Two fixed point for one minimum potential, slow temperature relaxation
Eur. Phys. J. B (2013) 86: 501
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Switching of Memristors: simple model
Eur. Phys. J. B (2013) 86: 501
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Conclusions • Temporal or spatial periodic potential allow to control band gap
structure in graphene
• Interplay between noise and relativistic dynamics results in new class of stochastic effects
• Diffusive dynamics of oxygen vacancies allow to describe experiments for memristors and predict new regimes of memristor operation