Chen, Z., Li, W., Ola, O., Feng, L., Zhang, X., Zhang, Y.-W., & Yao, X. (2025). Hierarchical nanoporous-based design strategy towards ductile ceramics with excellent strain hardening capability. International Journal of Plasticity, 194, 104487. https://doi.org/10.1016/j.ijplas.2025.104487
Abstract:
Overcoming the inherent brittleness of ceramics is a longstanding, unsolved challenge in materials science and engineering. Here, we demonstrate a new effective strategy to achieve a brittle-ductile transition in ceramics by introducing a hierarchical spinodal structure. Combining phase field method and molecular dynamics (MD) method, we first constructed nanoporous SiC samples with 1-level and hierarchical 2-level structures separately using a phase field method whose rationality is well validated, featuring spinodal topologies. Then, the mechanical response of the nanoporous ceramics under compression is investigated by all-atom MD simulations to discover the underlying nanoscale deformation mechanisms. The results revealed that the 1-level nanoporous SiC samples exhibited conventional brittleness due to stress-concentration-induced cracking; in stark contrast, the hierarchical 2-level samples displayed a ductile, strain-hardening, metal-like behavior, which is attributed to the presence of dispersed nuclei of defects like stacking faults, which effectively dispersed stress and prevented stress-concentration-induced failure. The strength of the hierarchical nanoporous ceramics follows Shi's law rather than classical Gibson-Ashby law. Our study not only elucidates the two distinct deformation mechanisms but also introduces a highly effective hierarchical nanoporous strategy for the design of ductile ceramics with excellent strain hardening capability, addressing the enduring challenge of brittleness in ceramics.
License type:
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Funding Info:
This research / project is supported by the A*STAR - Manufacturing, Trade, and Connectivity Programmatic Fund
Grant Reference no. : M22L2b0111
This research / project is supported by the National Research Foundation - AI Singapore Grand Challenge in AI for Materials Discovery
Grant Reference no. : AISG2-GC-2023-010