Observation of unconventional edge states in 'photonic graphene'

Yonatan Plotnik, Mikael C. Rechtsman, Daohong Song, Matthias Heinrich, Julia M. Zeuner, Stefan Nolte, Yaakov Lumer, Natalia Malkova, Jingjun Xu, Alexander Szameit, Zhigang Chen, Mordechai Segev

Research output: Contribution to journalArticlepeer-review

198 Scopus citations

Abstract

Graphene, a two-dimensional honeycomb lattice of carbon atoms, has been attracting much interest in recent years. Electrons therein behave as massless relativistic particles, giving rise to strikingly unconventional phenomena. Graphene edge states are essential for understanding the electronic properties of this material. However, the coarse or impure nature of the graphene edges hampers the ability to directly probe the edge states. Perhaps the best example is given by the edge states on the bearded edge that have never been observed - because such an edge is unstable in graphene. Here, we use the optical equivalent of graphene - a photonic honeycomb lattice - to study the edge states and their properties. We directly image the edge states on both the zigzag and bearded edges of this photonic graphene, measure their dispersion properties, and most importantly, find a new type of edge state: one residing on the bearded edge that has never been predicted or observed. This edge state lies near the Van Hove singularity in the edge band structure and can be classified as a Tamm-like state lacking any surface defect. The mechanism underlying its formation may counterintuitively appear in other crystalline systems.

Original languageEnglish (US)
Pages (from-to)57-62
Number of pages6
JournalNature Materials
Volume13
Issue number1
DOIs
StatePublished - Jan 2014

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Materials Science(all)
  • Condensed Matter Physics
  • Mechanics of Materials
  • Mechanical Engineering

Fingerprint Dive into the research topics of 'Observation of unconventional edge states in 'photonic graphene''. Together they form a unique fingerprint.

Cite this