JOURNAL ARTICLE

Fracture resistance of pottery laminates with intentionally introduced defects.

  • Published In: International Journal of Applied Ceramic Technology, 2025, v. 22, n. 2. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Sawada, Takeyuki; Maki, Yuto; Ikari, Shunsuke; Yamamoto, Keisuke; Kawai, Shuji; Nakao, Wataru 3 of 3

Abstract

Laminated ceramics containing layers of pottery materials with high and low Young's moduli were developed to mimic the nacre structure of abalone shells with high resistances against dynamic fractures. The layers with the low Young's modulus moderated crack deflection and impact, thereby exhibiting a high fracture resistance. The ceramic pores were formed by the CO2 gas generated through the oxidation of SiC during firing. The dynamic fracture resistance was enhanced by elastic wave scattering owing to the difference between the Young's moduli of the dense and porous layers. The effect of lamination on the dynamic fracture resistance was observed because the elastic waves were scattered owing to the difference in the elastic modulus between the porous and dense layers, and their propagation to the back sample surface was suppressed. The fracture energy of the 5‐layer laminate was determined to be about four times larger than that of the dense monolayer, which indicates that the introduction of intentional defects is effective in improving the dynamic fracture resistance of the pottery ceramics. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Applied Ceramic Technology. 2025/03, Vol. 22, Issue 2, p1
  • Document Type:Article
  • Subject Area:Visual Arts
  • Publication Date:2025
  • ISSN:1546-542X
  • DOI:10.1111/ijac.14945
  • Accession Number:183976973
  • Copyright Statement:Copyright of International Journal of Applied Ceramic Technology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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