Preparation and mechanical properties of graphene-reinforced alumina-matrix composites

Regulating interface interaction in alumina/graphene composites with nano alumina coating transition layers

The structure and properties of graphene/alumina composites are affected by the interface interaction. To demonstrate the influence of interface interaction on the structure of composite materials, a composite without graphene/matrix alumina interface was designed and prepared. We introduced a nano transition layer into the composite by pre-fabricating nano alumina coating on the surface of graphene, thus regulating the influence of interface interaction on the structure of the composite. According to the analysis of laser micro Raman spectroscopy, the structure of graphene was not seriously damaged during the modification process, and graphene was subjected to tensile or compressive stress along the 2D plane. The fracture behavior of the modified graphene/alumina composites is similar to that of pure alumina, but significantly different from that of pure graphene/alumina composites. The elastic modulus and hardness of composite material G/A/A are higher, while its microstructure has better density and uniformity. In situ HRSEM observation showed that there was a transition layer of alumina in the modified graphene/alumina composite. The transition layer blocks or buffers the interfacial stress interaction, therefore, the composite material exhibits a fracture behavior similar to that of pure alumina at this time. This work demonstrates that interface interactions have a significant impact on the structure and fracture behavior of graphene/alumina composites.

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.

Sustainable Microfabrication Enhancement of Graphene Nanoplatelet-Reinforced Biomedical Alumina Ceramic Matrix Nanocomposites

Studies about adding graphene reinforcement to improve the microfabrication performance of alumina (Al₂O₃) ceramic materials are still too rare and incomplete to satisfy sustainable manufacturing requirements. Therefore, this study aims to develop a detailed understanding of the effect of graphene reinforcement to enhance the laser micromachining performance of Al₂O₃-based nanocomposites. To achieve this, high-density Al₂O₃ nanocomposite specimens were fabricated with 0 wt.%, 0.5 wt.%, 1 wt.%, 1.5 wt.%, and 2.5 wt.% graphene nanoplatelets (GNPs) using a high-frequency induction heating process. The specimens were subjected to laser micromachining. Afterward, the effects of the GNP contents on the ablation depth/width, surface morphology, surface roughness, and material removal rate were studied. The results indicate that the micro-fabrication performance of the nanocomposites was significantly affected by the GNP content. All nanocomposites exhibited improvement in the ablation depth and material removal rate compared to the base Al₂O₃ (0 wt.% GNP). For instance, at a higher scanning speed, the ablation depth was increased by a factor of 10 times for the GNP-reinforced specimens compared to the base Al₂O₃ nanocomposites. In addition, the MRRs were increased by 2134%, 2391%, 2915%, and 2427% for the 0.5 wt.%, 1 wt.%, 1.5 wt.%, and 2.5 wt.% GNP/Al₂O₃ nanocomposites, respectively, compared to the base Al₂O₃ specimens. Likewise, the surface roughness and surface morphology were considerably improved for all GNP/Al₂O₃ nanocomposite specimens compared to the base Al₂O₃. This is because the GNP reinforcement reduced the ablation threshold and increased the material removal efficiency by increasing the optical absorbance and thermal conductivity and reducing the grain size of the Al₂O₃ nanocomposites. Among the GNP/Al₂O₃ nanocomposites, the 0.5 wt.% and 1 wt.% GNP specimens showed superior performance with minimum defects in most laser micromachining conditions. Overall, the results show that the GNP-reinforced Al₂O₃ nanocomposites can be machined with high quality and a high production rate using a basic fiber laser system (20 Watts) with very low power consumption. This study shows huge potential for adding graphene to alumina ceramic-based materials to improve their machinability.