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Journal of Materials Science

, Volume 46, Issue 1, pp 243–253 | Cite as

The effect of high temperature heat treatment on the structure and properties of anodic aluminum oxide

  • M. Kylan McQuaigJr.
  • Alejandro Toro
  • William Van Geertruyden
  • Wojciech Z. Misiolek
Article

Abstract

Nanoporous anodic aluminum oxide (AAO) membranes can be fabricated with highly controllable thickness and porosity, making them ideal for filtration applications. Use of these membranes is currently limited largely due to their size and overall fragility. The objective of this research was to improve mechanical properties of AAO membranes through use of high temperature heat treatment to induce phase transformations in the material. A repeatable two-step anodization process was developed for consistent sample fabrication and heat treatments were performed at 900 °C and 1200 °C in air. The pore morphology and phase composition of the as-anodized and heat-treated membranes were then observed using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Microhardness testing was utilized to evaluate the mechanical behavior of the membranes before and after heat treatment. As-anodized AAO membranes were determined to be amorphous, and membranes heat-treated to 900 °C and 1200 °C were transformed to crystalline phases while retaining their original porous structure. Heat treatment to 900 °C resulted in formation of the γ-alumina transition phase in the skeleton regions of the membrane and nanocrystalline regions of α-alumina throughout the structure, while heat treatment to 1200 °C completely transformed the material to the stable α-alumina structure. The microhardness testing showed an increase in hardness from 2.5 ± 0.4 GPa to 4.7 ± 1.0 GPa in the transformation from amorphous to α-alumina.

Keywords

Differential Scanning Calorimetry Anodic Aluminum Oxide Anodic Aluminum Oxide Membrane High Temperature Heat Treatment Commercial Membrane 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

Funding for the research was provided by the National Institute of Health (grant NIAID_1R21AI081638-01A2). The authors wish to thank The Loewy Family Foundation for the support through the Loewy Graduate Fellowship (M.K. McQuaig, Jr.), Loewy Visiting Professorship (A. Toro) and Loewy Professorship (W.Z. Misiolek). The authors also thank Adrián Gómez from the National University of Colombia for his valuable help with DSC and TGA measurements.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • M. Kylan McQuaigJr.
    • 1
  • Alejandro Toro
    • 3
  • William Van Geertruyden
    • 2
  • Wojciech Z. Misiolek
    • 1
  1. 1.Institute for Metal Forming, Lehigh UniversityBethlehemUSA
  2. 2.EMV Technologies, LLCBethlehemUSA
  3. 3.Tribology and Surfaces Group, National University of ColombiaMedellinColombia

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