Semiconductor Heterostructures and Low-Dimensional Quantum Structures

  • Manijeh Razeghi

In Chapter 3, we have introduced the basic concepts and formalism of quantum mechanics. In Chapter 4, we have determined the energy spectrum, or energy-momentum or E-k relations, for electrons in a crystal which governs their interaction with external forces and fields. Moreover, we saw that the quantum behavior of particles is best observed in small, typically nanometer scale (one billionth of a meter or 10-9 m) dimension structures, as illustrated in the example of a particle in a 1D box.

In nanometer scale structures in a crystal, the motion of an electron can be confined in one or more directions in space. When only one dimension is restricted while the other two remain free, we talk about a quantum well); when two dimensions are restricted, we talk about a quantum wire; and when the motion in all three dimensions is confined, we talk about a quantum dot. In solid state engineering, these are commonly called lowdimensional quantum structures.

In the past few decades, progress in semiconductor crystal growth technology, such as liquid phase epitaxy (LPE), molecular beam epitaxy (MBE), metalorganic chemical vapor deposition (MOCVD), has made it possible to control with atomic scale precision the dimensions of semiconductor structures and thus to realize such low-dimensional quantum structures through the formation of heterojunctions or heterostructures. A semiconductor heterojunction is formed when two different semiconducting materials are brought into direct contact with each other, while heterostructures can be defined as materials that incorporate one or more heterojunctions and can describe more complicated device architectures such as multiple quantum wells, superlattices and other low-dimensional quantum structures.


Quantum Wire Multiple Quantum Band Alignment Quantized Energy Level Momentum Matrix Element 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag US 2009

Authors and Affiliations

  • Manijeh Razeghi
    • 1
  1. 1.Department of Electrical Engineering & Computer ScienceNorthwestern UniversityEvanstonUSA

Personalised recommendations