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Title:Novel analytical method for investigating compositional driven ion-induced nanopatterning of multicomponent materials
Author(s):Holybee, Brandon Jay
Advisor(s):Allain, Jean Paul
Contributor(s):Zhang, Yang
Department / Program:Nuclear, Plasma, & Rad Engr
Discipline:Nuclear, Plasma, Radiolgc Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):nanopatterning
ion irradiation
Auger electron spectroscopy
Grazing Incidence Small Angle X-ray Scattering (GISAXS)
Gallium antimonide (GaSb)
Abstract:Ion-induced nanopatterning of GaSb produces hexagonally ordered nanopatterns with cone-shaped nanofeatures, where experimental investigations have shown that these nanopatterns form under a wide variety of ion parameters – including ion energy and ion species. Several theoretical works have developed models to specifically describe the GaSb system, developing potential driving mechanisms that lead to pattern formation. Several of these describe compositional mechanisms – particularly segregation and phase separation – as having a dominant role in the ion-induced nanopattern formation, and motivate the investigation of how both the surface composition and topography evolve with ion irradiation leading up to pattern formation. The topography evolution of GaSb is investigated using real-time in-situ Grazing Incidence Small Angle X-ray Scattering (GISAXS) at Brookhaven National Lab. This experiment was setup such that GISAXS scans were taken at much smaller ion fluence intervals, about 1E15cm-2 per scan. These fluence steps allow for a much more detailed investigation of the topography evolution of GaSb from an etch-cleaned surface to the early stages of nanopattern formation. Ne+, Ar+, and Kr+ were all investigated with ion energies of 100eV, 200eV, 500eV, and 1keV. This investigation shows that the ion momentum correlates quite well with the early stage nanopattern onset fluence and average feature spacing when ion-induced patterns were present. The GISAXS experiments were able to determine the threshold fluence for the ion conditions used in the compositional investigation experiments, showing that ion-induced nanopattern formation starts at fluences of 3.1E16cm-2, 3.6E16cm-2, and 8.7E15cm-2 for Ne+, Ar+, and Kr+ at 500eV, respectively. Several theories and models suggest that composition changes at the surface can lead to nanopattern formation during ion irradiation, via mechanisms including preferential sputtering, segregation, and preferential diffusion. This motivates the investigation of the surface composition evolution during ion irradiation – particularly at fluences just before ion-induced nanopatterning begins – in order to extract information on the potential compositionally driven mechanisms involved. In order to achieve this, in-situ Angle-Resolved Auger Electron Spectroscopy (ARAES) is used in conjunction with a mathematical model of the surface composition as a function of depth. This model is based on potential mechanisms involved, including preferential sputtering and segregation, and is formulated in the framework of ARAES analysis, allowing for the ARAES data to be fit directly in a phenomenological approach to investigate the surface composition of GaSb under ion irradiation. In order to avoid contamination at the surface of GaSb, especially from oxide formation, GaSb single crystals were cleaved in-vacuo in order to expose an ideal surface. The cleaved surface is free of contaminants and has a 50-50 composition necessary in determining the relative sensitivity factors required for the ARAES analysis. The extracted composition depth profiles show a dynamic change in the GaSb surface stoichiometry under ion irradiation. In the fluences before ion-induced nanopatterns form, the very surface goes from Ga enriched towards Sb enriched, with a clear sub-surface enrichment of Sb present. This evolution in the composition suggests that composition does indeed play a dominant role in ion-induced nanopatterning of GaSb and lays down the framework for in-situ composition depth profile analysis for future studies.
Issue Date:2016-07-20
Type:Thesis
URI:http://hdl.handle.net/2142/92972
Rights Information:Copyright 2016 Brandon Holybee
Date Available in IDEALS:2016-11-10
Date Deposited:2016-08


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