Growth and Spectroscopy of Semiconductor Quantum Rings

  • Wen LeiEmail author
  • Axel Lorke
Part of the NanoScience and Technology book series (NANO)


Quantum rings are unique nanostructures as they are topologically not simply connected and therefore different from most other low-dimensional systems such as quantum dots, quantum wires or quantum wells. This topology gives rise to an intriguing energy structure, in particular, when a magnetic field is applied such that a flux can penetrate through the ring’s interior. Flux quantization will lead to a ground state, which has a non-vanishing angular momentum, and the intraband transitions are affected by the corresponding change in dipole-allowed transitions. Quantum rings, which are of the order of 10 nm in size are of particular interest, because they make it possible to study these systems in the true quantum limit.

In this chapter, we will review the growth techniques, which lead to the self-organized formation of quantum rings of a few tens of nanometers in diameter. The mechanisms will be discussed, which ‘invert’ the geometry of InAs islands, grown in the Stranski-Krastanov mode on GaAs, when they are partially capped with GaAs. When the thus formed nanorings are embedded in a suitable heterostructure, they can be electrically tuned and carriers can be injected with single-electron/single-hole precision. We will discuss, how the number of carriers and the strength of the applied field influence the single-particle and many-particle ground states, which can be probed by capacitance-voltage measurements. Also, far-infrared absorption spectra will be presented, which show the influence of flux quantization on the intraband transitions. These spectroscopic techniques, together with photoluminescence data obtained on single rings as well as on ring ensembles, make it possible to obtain an in-depth view into the detailed energetic structure of nanoscopic rings.


Interband Transition Metal Organic Chemical Vapor Deposition Wetting Layer Back Contact Quantum Ring 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by the Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung and the Australian Research Council.


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© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.School of Electrical, Electronic and Computer EngineeringThe University of Western AustraliaCrawleyAustralia
  2. 2.Faculty of Physics and CENIDEUniversität Duisburg-EssenDuisburgGermany

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