Abstract
In this work, the influence of thermal pre-processing upon the microstructure and hardness of Al 6061 feedstock powder is considered through the lens of cold spray processing and additive manufacturing. Since solid-state cold spray processes refine and retain microstructural constituents following impact-driven and high-strain rate severe plastic deformation and bonding, thermal pre-processing enables application-driven tuning of the resultant consolidation achieved via microstructural and, therefore, mechanical manipulation of the feedstock prior to use. Microstructural analysis was achieved via X-ray diffraction, scanning electron microscopy, transmission electron microscopy, electron backscatter diffraction, energy dispersive spectroscopy, and differential thermal calorimetry. On the other hand, nanoindentation testing and analysis were relied upon to quantify pre-processing effects and microstructural evolution influences on the resultant hardness as a function of time at 540 °C. In the case of the as-atomized powder, β-Mg2Si-, Al-Fe-, and Mg-Si-type phases were observed along polycrystalline grain boundaries. Furthermore, after a 60 min hold time at 540 °C, Al-Fe-Si-Cr-Mn- and Mg-Si-type intermetallic phases were also observed along grain boundaries. Furthermore, the as-atomized hardness at 250 nm of indentation depth was 1.26 GPa and continuously decreased as a function of hold time until reaching 0.88 GPa after 240 min at 540 °C. Finally, contextualization of the observations with tuning cold spray additive manufacturing part performance via powder pre-processing is presented for through-process and application-minded design.
Funder
United States Army Research Laboratory
Subject
General Materials Science,Metals and Alloys
Reference66 articles.
1. Characterization and Control of Powder Properties for Additive Manufacturing
2. The Effects of LENS Process Parameters on the Behaviour of 17-4 PH Stainless Steel;Mathoho;Proceedings of the TMS 2020 149th Annual Meeting & Exhibition Supplemental Proceedings,2020
3. Classifying Powder Flowability for Cold Spray Additive Manufacturing Using Machine Learning;Valent;Proceedings of the 2nd International Workshop on Big Data Tools, Methods, and Use Cases for Innovative Scientific Discvery, IEEE Bigdata Conference,2020
4. Characteristics of Feedstock Materials;Hussain,2015
5. Standoff distance and bow shock phenomena in the Cold Spray process
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献