Functionally graded metal matrix composite of Haynes 282 and SiC fabricated by laser metal deposition
Functionally graded metal matrix composite of Haynes 282 and SiC fabricated by laser metal deposition
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DOI：
10.1016/j.matdes.2019.107877
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发表时间：
2019-10
影响因子：
8.4
通讯作者：
A. Ramakrishnan;G. Dinda
中科院分区：
文献类型：
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作者：
A. Ramakrishnan;G. Dinda
在当前的研究中，利用激光金属沉积（LMD）成功地在单一沉积物中制造了具有不同成分、结构和性能的SiC颗粒增强的Haynes 282（HY282）高温合金的功能梯度金属基复合结构。由于使用高激光能量，我们发现 SiC 与 HY282 大量解离成 Si 和 C，产生多种反应产物，包括富硅过饱和奥氏体 γ 基体、γ′ Ni3(Al,Ti,Si)、M(Ti,Mo)C、M23(Cr,Mo,Si)C6、M6(Mo,Ti)C、M7(Cr, Mo)C3 碳化物和 γ/γ′ 层状碳化物共熔物。由于该过程的快速冷却性质，分级结构由非平衡微观结构、一些有害的第二相以及导致不良性能的严重偏析行为组成。因此，对沉积样品进行热处理循环，以确保微观结构的均匀化。通过扫描电子显微镜、能量色散谱和微压痕技术表征了每层成分变化对显微结构、化学成分和显微硬度的影响。通过计算相图的观点来估计每层分级样品中发现的复杂相，以确定使用计算热力学模拟来预测实验观察到的结构的表现的可行性。
In the current study, functionally graded metal matrix composite structure of Haynes 282 (HY282) superalloy reinforced with SiC particles with varying composition, structure and property in a single deposit is successfully fabricated using laser metal deposition (LMD). Due to the high laser energy used it was found that SiC disassociated profusely into Si and C with HY282 causing several reaction products that included a Si-rich supersaturated austenitic γ matrix, γ′ Ni3(Al,Ti,Si), M(Ti,Mo)C, M23(Cr,Mo,Si)C6, M6(Mo,Ti)C, M7(Cr, Mo)C3 carbides, and γ/γ′ lamellar eutectics. Due to the rapid cooling nature of the process, the graded structure consists of non-equilibrium microstructure, several deleterious secondary phases, and heavy segregation behavior that lead to unwanted properties. Hence a heat-treatment cycle was performed on the as-deposited sample to ensure homogenization of the microstructures. The influence of composition variation in each layer on the microstructure, chemistry, and microhardness were characterized by scanning electron microscopy, energy dispersive spectroscopy, and micro-indentation techniques. The complex phases found in the graded sample in every layer were estimated by calculation of phase diagrams viewpoint to establish the feasibility of using computational thermodynamic simulations to predict the manifestation of the experimentally observed structure.