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Simulation-assisted parameter optimization and tribological behavior of graphene reinforced IN718 matrix composite prepared by SLM

材料科学 复合数 摩擦学 石墨烯 复合材料 基质(化学分析) 纳米技术
作者
Yang Chu,Haichuan Shi,Peilei Zhang,Zhishui Yu,Hua Yan,Qinghua Lu,Shijie Song,Kaichang Yu
出处
期刊:Intermetallics [Elsevier BV]
卷期号:170: 108307-108307 被引量:4
标识
DOI:10.1016/j.intermet.2024.108307
摘要

To enhance the wear resistance of nickel-based superalloys and broaden their applications, we investigated the microstructural organization and wear properties of IN718 composites reinforced with graphene nanoparticles fabricated through selective laser melting. The optimal parameters for printing were obtained by combining experiments and simulations, and their wear patterns were subsequently explored at different sliding speeds (250–350 r/min) and loads (4N–8N). Based on the composite TEM images combined with experiments, it was found that the homogeneous dispersion of graphene nanoparticles in the 3D-printed GNPs/IN718 composites acted as dislocation reinforcement and load reinforcement. The average microhardness of the GNPs/IN718 composites increased by 24.2 % compared to the IN718 alloy. In the friction test, GNPs acts as a lubricating phase, resulting in a significant increase in the friction wear performance of the composite. The average coefficient of friction decreased by 33.8 % and the wear rate decreased by 51.3 %. The wear state of the composites change from abrasive wear to delamination wear and a combination of delamination wear and oxidative wear as the speed and load are increased, respectively. This paper provides potential guidance for further improving the wear performance of additively manufactured nickel-based superalloys.
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