Chapter 84. Towards Optimal Processing of Yttria Stablized Zirconia Thin Films by Stochastic Simulation of Grain Growth

  1. Hua-Tay Lin and
  2. Mrityunjay Singh
  1. J. Lua1,
  2. Z. Xu2,
  3. J. Sankar2,
  4. D. Pai2 and
  5. S. Yamolenko2

Published Online: 26 MAR 2008

DOI: 10.1002/9780470294741.ch84

26th Annual Conference on Composites, Advanced Ceramics, Materials, and Structures: A: Ceramic Engineering and Science Proceedings, Volume 23, Issue 3

26th Annual Conference on Composites, Advanced Ceramics, Materials, and Structures: A: Ceramic Engineering and Science Proceedings, Volume 23, Issue 3

How to Cite

Lua, J., Xu, Z., Sankar, J., Pai, D. and Yamolenko, S. (2008) Towards Optimal Processing of Yttria Stablized Zirconia Thin Films by Stochastic Simulation of Grain Growth, in 26th Annual Conference on Composites, Advanced Ceramics, Materials, and Structures: A: Ceramic Engineering and Science Proceedings, Volume 23, Issue 3 (eds H.-T. Lin and M. Singh), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470294741.ch84

Author Information

  1. 1

    Engineering & Information Technology Group Anteon Corporation 240 Oral School Road Mystic, CT 06355–1208

  2. 2

    NSF Center for Advanced Materials & Smart Structures North Carolina A&T State University Greensboro, NC 27411

Publication History

  1. Published Online: 26 MAR 2008
  2. Published Print: 1 JAN 2002

ISBN Information

Print ISBN: 9780470375785

Online ISBN: 9780470294741

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Keywords:

  • microstructural;
  • combustion;
  • oxygen-ion;
  • electrolyte;
  • slurry

Summary

Yttria fully stabilized zirconia (YSZ) thin films have been used as an electrolyte in solid oxide fuel cells. The microstructural characteristics of the thin films has played an important role in controlling efficiency and reliability of the fuel cell. Experimental studies have shown that both the grain size and the film texture highly depends on various fabrication and processing parameters. To explore an optimal processing technique for maximizing the performance and durability of the fuel cell, a stochastic grain growth model is developed by implementing Thompson's grain evolution law into a probabilistic computational framework. The resulting stochastic grain size evolution model can be used to trace both the microstructure and texture subjected to a given processing condition.