Direct Nanoscale Imaging of Evolving Electric Field Domains in Quantum Structures
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Dhar-2014-Direct nanoscale imaging.pdf
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Author(s)
Dhar, Rudra Sankar
Razavipour, Seyed Ghasem
Dupont, E.
Xu, Chao
Laframboise, Sylvain R.
Wasilewski, Zbig
Hu, Qing
Ban, Dayan
Date Issued
November 2014
Journal
Scientific Reports
Publisher
Nature Publishing Group
Citation
Dhar, Rudra Sankar, Seyed Ghasem Razavipour, Emmanuel Dupont, Chao Xu, Sylvain Laframboise, Zbig Wasilewski, Qing Hu, and Dayan Ban. “Direct Nanoscale Imaging of Evolving Electric Field Domains in Quantum Structures.” Sci. Rep. 4 (November 28, 2014): 7183.
Version
Final published version
Abstract
The external performance of quantum optoelectronic devices is governed by the spatial profiles of electrons and potentials within the active regions of these devices. For example, in quantum cascade lasers (QCLs), the electric field domain (EFD) hypothesis posits that the potential distribution might be simultaneously spatially nonuniform and temporally unstable. Unfortunately, there exists no prior means of probing the inner potential profile directly. Here we report the nanoscale measured electric potential distribution inside operating QCLs by using scanning voltage microscopy at a cryogenic temperature. We prove that, per the EFD hypothesis, the multi-quantum-well active region is indeed divided into multiple sections having distinctly different electric fields. The electric field across these serially-stacked quantum cascade modules does not continuously increase in proportion to gradual increases in the applied device bias, but rather hops between discrete values that are related to tunneling resonances. We also report the evolution of EFDs, finding that an incremental change in device bias leads to a hopping-style shift in the EFD boundary – the higher electric field domain expands at least one module each step at the expense of the lower field domain within the active region.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Research Laboratory of Electronics
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DOI of Published Version
https://doi.org/10.1038/srep07183
