Abstract
Glassy behavior is manifested by three time-dependent characteristics of a dynamic physical property. Such behaviors have been found in the electrical conductivity transients of various disordered systems, but the mechanisms that yield the glassy behavior are still under intensive debate. The focus of the present work is on the effect of the quantum confinement (QC) and the Coulomb blockade (CB) effects on the experimentally observed glassy-like behavior in semiconductor nanomaterials. Correspondingly, we studied the transient electrical currents in semiconductor systems that contain CdSe or Si nanosize crystallites, as a function of that size and the ambient temperature. In particular, in contrast to the more commonly studied post-excitation behavior in electronic glassy systems, we have also examined the current transients during the excitation. This has enabled us to show that the glassy behavior is a result of the nanosize nature of the studied systems and thus to conclude that the observed characteristics are sensitive to the above effects. Following this and the temperature dependence of the transients, we derived a more detailed macroscopic and microscopic understanding of the corresponding transport mechanisms and their glassy manifestations. We concluded that the observed electrical transients must be explained not only by the commonly suggested principle of the minimization of energy upon the approach to equilibrium, as in the mechanical (say, viscose) glass, but also by the principle of minimal energy dissipation by the electrical current which determines the percolation network of the electrical conductivity. We further suggest that the deep reason for the glassy-like behavior that is observed in the electrical transients of the nanomaterials studied is the close similarity between the localization range of electrons due to the Coulomb blockade and the caging range of the uncharged atomic-size particles in the classical mechanical glass. These considerations are expected to be useful for the understanding and planning of semiconductor nanodevices such as corresponding quantum dot memories and quantum well MOSFETs.
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