10 years of research on toughness enhancement of structural ceramics by graphene

Enhancing the Properties of Yttria-Stabilized Zirconia Composites with Zeolitic Imidazolate Framework-Derived Nanocarbons

Ceramic matrix composites (CMCs) reinforced with nanocarbon have attracted significant interest due to their potential to enhance mechanical, thermal, and electrical properties. Although the investigation of carbon-based materials such as graphene and carbon nanotubes as additives for advanced ceramics has been widespread, the utilization of metal-organic framework (MOF)-derived nanocarbons in CMCs remains largely unexplored. We extended our previous proof-of-concept investigations by demonstrating the effectiveness of a different type of MOF-derived carbon as a reinforcing phase in an alternative ceramic matrix. We employed spark plasma sintering (SPS) to consolidate yttria-stabilized zirconia (YSZ) and zeolitic imidazolate framework (ZIF-67) powder blends at 1300 °C and a uniaxial pressure of 50 MPa. YSZ serves as the ceramic matrix, whereas ZIF-67 serves as the nanocarbon source. The composite exhibits a highly significant improvement in fracture toughness with an increase of up to 13% compared to that of the YSZ monolith. The formation of ZIF-derived nanocarbon interlayers is responsible for the observed enhancement in ductility, which can be attributed to their ability to facilitate energy dissipation during crack propagation and inhibit grain growth. Furthermore, the room-temperature electrical conductivity of the sintered samples demonstrates a substantial improvement, primarily due to the in situ formation of nanocarbon-based fillers, reaching an impressive 27 S/m with 10 wt % ZIF-67 content. Based on the results, it can be inferred that the incorporation of in situ MOF-derived nanocarbons into CMCs leads to a substantial improvement in both the mechanical and electrical properties.

An Armour Structure to Suppress the Brittle Failure of Ceramic Coatings

The brittle failure of ceramic coatings limits their application in many fields. To address this issue, a novel armoured ceramic coating was developed to suppress brittle failure. First, an interconnected frame microstructure was micromachined onto the surface of a mild steel substrate using a nanosecond laser. Subsequently, a polymer-derived ceramic slurry was sprayed and sintered to obtain an armoured ceramic coating. The laser-micromachined burr-like microstructure of the substrate facilitated adhesion between the coating and the substrate. The results of the mechanical properties test showed that the armoured coating could withstand more than 20 cycles of water-cooled thermal shock at 600 °C, and the peeling area of the armoured coating was approximately three times less than that of the unarmoured coating under a normal load of 1471 N. The laboratory and field corrosion test results indicated that at high temperatures, the corrosion resistance of the armoured coating was comparable with that of the unarmoured coating and was approximately 10 times higher than that of the uncoated sample. The proposed method will aid in suppressing the brittle failure of ceramic coatings and broaden their scope of application in different fields.

Integrated Intelligent Method Based on Fuzzy Logic for Optimizing Laser Microfabrication Processing of GnPs-Improved Alumina Nanocomposites

Studies on using multifunctional graphene nanostructures to enhance the microfabrication processing of monolithic alumina are still rare and too limited to meet the requirements of green manufacturing criteria. Therefore, this study aims to increase the ablation depth and material removal rate and minimize the roughness of the fabricated microchannel of alumina-based nanocomposites. To achieve this, high-density alumina nanocomposites with different graphene nanoplatelet (GnP) contents (0.5 wt.%, 1 wt.%, 1.5 wt.%, and 2.5 wt.%) were fabricated. Afterward, statistical analysis based on the full factorial design was performed to study the influence of the graphene reinforcement ratio, scanning speed, and frequency on material removal rate (MRR), surface roughness, and ablation depth during low-power laser micromachining. After that, an integrated intelligent multi-objective optimization approach based on the adaptive neuro-fuzzy inference system (ANIFS) and multi-objective particle swarm optimization approach was developed to monitor and find the optimal GnP ratio and microlaser parameters. The results reveal that the GnP reinforcement ratio significantly affects the laser micromachining performance of Al₂O₃ nanocomposites. This study also revealed that the developed ANFIS models could obtain an accurate estimation model for monitoring the surface roughness, MRR, and ablation depth with fewer errors than 52.07%, 100.15%, and 76% for surface roughness, MRR, and ablation depth, respectively, in comparison with the mathematical models. The integrated intelligent optimization approach indicated that a GnP reinforcement ratio of 2.16, scanning speed of 342 mm/s, and frequency of 20 kHz led to the fabrication of microchannels with high quality and accuracy of Al₂O₃ nanocomposites. In contrast, the unreinforced alumina could not be machined using the same optimized parameters with low-power laser technology. Henceforth, an integrated intelligence method is a powerful tool for monitoring and optimizing the micromachining processes of ceramic nanocomposites, as demonstrated by the obtained results.