Characterization of Zirconia Specimens Fabricated by Ceramic On-Demand Extrusion
Abstract
The Ceramic On-Demand Extrusion (CODE) process is a novel additive manufacturing method for fabricating dense (~99% of theoretical density) ceramic components from aqueous, high solids loading pastes ( > 50 vol%). In this study, 3 mol% Y2O3 stabilized zirconia (3YSZ) specimens were fabricated using the CODE process. The specimens were then dried in a humidity-controlled environmental chamber and afterwards sintered under atmospheric conditions. Mechanical properties of the sintered specimens were examined using ASTM standard test techniques, including density, Young's modulus, flexural strength, Weibull modulus, fracture toughness, and Vickers hardness. The microstructure was analyzed and grain size measured using scanning electron microscopy. The results were compared with those from Direct Inkjet Printing, Selective Laser Sintering, Lithography-based Ceramic Manufacturing (LCM), and other extrusion-based processes, and indicated that zirconia specimens produced by CODE exhibit superior mechanical properties among the additive manufacturing processes. Several sample components were produced to demonstrate CODE's capability for fabricating geometrically complex ceramic components. The surface roughness of these components was also examined.
Recommended Citation
W. Li et al., "Characterization of Zirconia Specimens Fabricated by Ceramic On-Demand Extrusion," Ceramics International, vol. 44, no. 11, pp. 12245 - 12252, Elsevier Ltd, Aug 2018.
The definitive version is available at https://doi.org/10.1016/j.ceramint.2018.04.008
Department(s)
Materials Science and Engineering
Research Center/Lab(s)
Intelligent Systems Center
Keywords and Phrases
Additive Manufacturing; Mechanical Property; Surface Roughness; ZrO2
International Standard Serial Number (ISSN)
0272-8842
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2018 Elsevier Ltd, All rights reserved.
Publication Date
01 Aug 2018
Comments
The authors gratefully acknowledge the financial support of this research by the National Energy Technology Laboratory of the Department of Energy under the contract No. DE-FE0012272 , and by the Intelligent Systems Center at the Missouri University of Science and Technology.