journal article·2026-01Open access

Damage tolerance and cyclic stability of 3D-architected Al2O3/polymer composites

Wanyu Li, Keqiang Zhang, Zijian Zhang, Yingjie Feng, Chunlei Wan

Journal of Materiomics· Volume 12· Issue 1

Abstract

The inherent brittleness and unpredictable catastrophic fracture of ceramic materials significantly limit their reliability in engineering applications, necessitating innovative approaches to enhance energy absorption capacity and cyclic load tolerance for structural components. This study presents a novel strategy for fabricating high-strength and cyclically-stable Al 2 O 3 /polymer composites through digital light processing (DLP) 3D printing of triply periodic minimal surface (TPMS) architectures combined with polymer infiltration. Mechanical characterization revealed exceptional quasi-static compressive strength of (201.9 ± 13.2) MPa coupled with remarkable energy absorption capacity reaching (40.1 ± 0.8) MJ/m 3 . The synergistic combination of TPMS structural design and extrinsic polymer toughening mechanisms induced progressive failure patterns characterized by extensive crack deflection and controlled interfacial debonding. Notably, the architected composites demonstrated outstanding cyclic durability, sustaining over 100 cycles at 60% and 70% maximum stress levels while maintaining 73 cycles at 80% stress level. Mechanical analysis attributed this performance enhancement to the polymer matrix's dual role in stress redistribution and energy dissipation accumulation during cyclic loading. This bioinspired structural design paradigm effectively addresses traditional ceramics' brittleness limitations, demonstrating significant potential for engineering applications in extreme environments requiring damage tolerance and load cycling reliability.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Additive Manufacturing and 3D Printing Technologies · Silicone and Siloxane Chemistry · Advanced ceramic materials synthesis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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