(604e) Control of Oxygen Self-Diffusion In Metal Oxides for Nanoelectronics | AIChE

(604e) Control of Oxygen Self-Diffusion In Metal Oxides for Nanoelectronics

Authors 

Gorai, P. - Presenter, University of Illinois
Pangan-Okimoto, K. - Presenter, University of Illinois
Hollister, A. - Presenter, University of Illinois


Oxygen defects play a central role in various physical phenomena in semiconductor metal oxides that are technologically relevant. Metal oxide properties like gas sensing, photoluminescence, bipolar switching and photocatalysis are strongly influenced by the concentration and diffusion of native oxygen defects. Previous work done in our group in silicon (Si) and titanium dioxide (TiO2) identified the semiconductor surface as an efficient pathway for the generation and annihilation of point defects in the underlying bulk. Such surface pathways should play an especially important role in nanoelectronic and nanophotonic devices where the surface to volume ratio is high. It is expected that such surface effects should apply to other semiconductors as well. In an attempt to generalize the surface effects, the present work extends these findings for Si and TiO2 to zinc oxide (ZnO), wherein we have identified unique surface pathways for generation of oxygen point defects. Oxygen diffusion rates were measured by exposing natural-abundance single-crystal ZnO <0001> to isotopically labeled oxygen gas.  The resulting profiles were measured by secondary ion mass spectrometry (SIMS) and modeled with mass transport equations for the reaction and diffusion of mobile and stagnant oxygen point defect species. The effective oxygen diffusivity is determined by fitting this model to experimental SIMS profiles. In addition, the detailed reaction-diffusion network of point defects in ZnO is modeled with continuum equations to simulate the self-diffusion of oxygen, explicitly incorporating the oxygen adsorption on to the <0001> surface, defect generation near the surface and the subsequent diffusion of the defect through the bulk. Such a model will help us understand mechanistically the effect of each of these elementary steps on the oxygen self-diffusion in ZnO besides extracting important kinetic parameters.

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