In Situ Al-TiC Composites Fabricated by Self-propagating High-Temperature Reaction: Insights on Reaction Pathways and Their Microstructural Signatures
In Situ Al-TiC Composites Fabricated by Self-propagating High-Temperature Reaction: Insights on Reaction Pathways and Their Microstructural Signatures
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DOI：
10.1007/s11661-020-05786-1
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发表时间：
2020-05
期刊：
影响因子：
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通讯作者：
C. Reese;A. Gladstein;J. M. Fedors;V. De Andrade;B. Mishra;A. Shahani;A. Taub
中科院分区：
文献类型：
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作者：
C. Reese;A. Gladstein;J. M. Fedors;V. De Andrade;B. Mishra;A. Shahani;A. Taub
在这项研究中，我们分析了原位经由铝热剂辅助（例如，CuO）自蔓延高温合成（SHS）生产的Al/TiC金属基纳米复合材料的形成机制和加工-微观结构关系。 Al/TiC 复合材料是通过使用多种加工条件（例如前驱体粉末量、本体熔体温度、前驱体粉末尺寸、颗粒包装方法）在铝熔体中使 Al-Ti-C-CuO 颗粒反应而制成的。使用 2D (SEM) 和 3D (TXM) 显微镜技术对铸态复合材料进行可视化，以研究纳米尺度的 TiC 颗粒和二次沉淀物（例如 Al3Ti）特性。 SHS 生产的样品揭示了复杂的微观结构，由单个和簇状的 TiC 颗粒、细长的 Al3Ti 金属间化合物以及被 TiC 包围的富碳区域组成。基于热力学分析和我们的微观结构观察，我们提出了三种主要的 TiC 形成途径，每一种都会产生独特的微观结构特征。最后，我们利用全范围成像数据的多元统计（典型相关性）来推断对 TiC 颗粒特性和最终复合材料微观结构影响最大的主要加工变量（即 CuO 和 C 的量）。我们还讨论了主要加工变量如何与所提出的形成途径相关，以及它们如何为通过铝热剂辅助 SHS 生产的未来复合材料的合理设计提供信息。
In this study, we have analyzed the formation mechanisms and processing-microstructure relationships for Al/TiC metal matrix nanocomposites producedin situ viathermite-assisted (e.g., CuO) self-propagating high-temperature synthesis (SHS). Al/TiC composites were created by reacting Al-Ti-C-CuO pellets in an Al melt using a wide variety of processing conditions (e.g., precursor powder amounts, bulk melt temperature, precursor powder size, pellet packing method). As-cast composites were visualized using both 2D (SEM) and 3D (TXM) microscopy techniques, to study TiC particle and secondary precipitate (e.g., Al3Ti) characteristics at the nanoscale. SHS-produced samples reveal complex microstructures consisting of individual and clustered TiC particles, elongated Al3Ti intermetallics, and C-rich regions surrounded by TiC. Based on a thermodynamic analysis and our microstructural observations, we propose three dominant TiC formation pathways, each resulting in a distinct microstructural signature. Finally, we utilize multivariate statistics (canonical correlations) on the full breadth of imaging data to infer the dominant processing variables (i.e., amount of CuO and C) that most strongly influence TiC particle characteristics and the final composite microstructure. We also discuss how the dominant processing variables relate to the proposed formation pathways and how they may inform the rational design of future composites producedviathermite-assisted SHS.