Cold Spraying of Mixed Metal Powders: A Modelling Framework for Predicting Deposition Efficiency and Coating Composition

IF 3.2 3区 材料科学 Q2 MATERIALS SCIENCE, COATINGS & FILMS
Che Zhang, Tesfaye Molla, Christian Brandl, Jarrod Watts, Rick McCully, Caixian Tang, Graham Schaffer
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引用次数: 0

Abstract

Cold spraying (CS) of composite coatings produced from mixed metal powders can exhibit enhanced functional properties over coatings made from pure metals. However, controlling the deposition efficiency and the resulting microstructure during CS is challenging due to interactions between different materials. In this study, we developed a modelling framework to predict the deposition efficiency (DE) of mixed metal powders and the resultant coating composition. This is achieved by predicting the critical and impact velocities as a function of particle size, which allows determination of the DEs of both matched (A/A or B/B) and mismatched (A/B or B/A) particle/substrate combinations. These DEs are then used to determine the overall DE of the composite coating and its composition by using a layer-wise deposition model. The modelling framework is validated by performing several CS experiments using Cu and Al particles together with SEM image analyses of the coating microstructures. We find that in-flight interaction of particles of different masses has a significant effect on the impact velocity and hence DE of composite coatings. By effectively predicting DE and coating composition, the proposed model serves as a valuable tool for optimizing cold spray parameters, reducing trial-and-error costs and time, and accelerating the development of novel composite coatings with enhanced properties.

冷喷涂混合金属粉末:预测沉积效率和涂层成分的建模框架
由混合金属粉末制成的复合涂层的冷喷涂(CS)比由纯金属制成的涂层具有更高的功能性能。然而,由于不同材料之间的相互作用,在CS过程中控制沉积效率和产生的微观结构是具有挑战性的。在这项研究中,我们开发了一个模型框架来预测混合金属粉末的沉积效率(DE)和由此产生的涂层成分。这是通过预测临界速度和冲击速度作为粒径的函数来实现的,这可以确定匹配(a / a或B/B)和不匹配(a /B或B/ a)颗粒/基质组合的de。然后使用这些DE来确定复合涂层的总体DE及其组成,使用分层沉积模型。利用Cu和Al颗粒进行了多次CS实验,并对涂层微观结构进行了SEM图像分析,验证了模型框架的有效性。我们发现不同质量颗粒在飞行中的相互作用对复合涂层的冲击速度和DE有显著影响。通过有效地预测DE和涂层成分,该模型可作为优化冷喷涂参数、减少试错成本和时间、加速新型复合涂层性能增强的有价值的工具。
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来源期刊
Journal of Thermal Spray Technology
Journal of Thermal Spray Technology 工程技术-材料科学:膜
CiteScore
5.20
自引率
25.80%
发文量
198
审稿时长
2.6 months
期刊介绍: From the scientific to the practical, stay on top of advances in this fast-growing coating technology with ASM International''s Journal of Thermal Spray Technology. Critically reviewed scientific papers and engineering articles combine the best of new research with the latest applications and problem solving. A service of the ASM Thermal Spray Society (TSS), the Journal of Thermal Spray Technology covers all fundamental and practical aspects of thermal spray science, including processes, feedstock manufacture, and testing and characterization. The journal contains worldwide coverage of the latest research, products, equipment and process developments, and includes technical note case studies from real-time applications and in-depth topical reviews.
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