Personal tools
You are here: Home
Document Actions

Predicting the Electronic Properties of 3D, Million-Atom Semiconductor Nanostructure Architectures


Revolutionary breakthroughs in quantum dots


The past ~10 years have witnessed revolutionary breakthroughs both in synthesis of quantum dots (leading to nearly monodispersed, defect-free nanostructures) and in characterization of such systems, revealing ultra narrow spectroscopic lines of <1meV width, exposing new intriguing effects, such as multiple exciton generation, fine-structure splitting, quantum entanglement, multiexciton recombination and more. These discoveries have led to new technological applications including quantum computing and ultra-high efficiency solar cells. Our work in this project is based on two realizations/observations:

  First, that the dots exhibiting clean and rich spectroscopic and transport characteristics are rather big. Indeed, the phenomenology indicated above is exhibited only by the well-passivated defect-free quantum dots containing at least a few thousand atoms (colloidal) and even a few hundred thousand atoms (self assembled). Understanding the behavior of nanotechnology devices requires the study of even larger, million-atom systems composed of multiple components such as wires+dots+films.

  Second, first-principles many-body computational techniques based on current approaches (Quantum Monte-Carlo, GW, Bethe-Salpeter) are unlikely to be adaptable to such large structures and, at the same time, the effective mass-based techniques are too crude to provide insights on the many-body/atomistic phenomenology revealed by experiment. Thus, we have developed a set of methods that use an atomistic approach (unlike effective-mass based techniques) and utilize single-particle + many body techniques that are readily scalable to ~103-106 atom nanostructures.


DOE-Nano

  • A. Zunger, A. Franceschetti, G. Bester, Materials Science Center, NREL.
  • W.B. Jones, Kwiseon Kim and P. A. Graf, Scientific Computing Center, NREL.
  • L-W. Wang, A. Canning, O. Marques, C. Voemel, Computational Research Division, LBNL.
  • J. Dongarra, J. Langou and S. Tomov, Dept. of Computer Science, University of Tennessee.
« March 2012 »
Su Mo Tu We Th Fr Sa
123
45678910
11121314151617
18192021222324
25262728293031
 

Powered by Plone CMS, the Open Source Content Management System

This site conforms to the following standards: