The low working temperature of cold spray technology offers a unique possibility to deposit a wide variety of composite materials by mixing two or more constituent powders. However, while it is possible to precisely control the chemical composition of the mixture before spraying, the compositional yield in the deposit remains uncertain. This is mainly due the variation of deposition kinetics between the constituent phases leading to a compositional deviation with respect to the feedstock. The mismatch in thermo-mechanical properties of the materials included in the feedstock can also lead to the variation of deposit composition along its thickness. Here, we paired a probabilistic approach with finite element simulations to estimate the deposition efficiency of the mixed powder and assess the actual composition of the cold spray multi-material deposit. The developed model accounts for the interaction of the powders with the substrate and estimates the deposition probability based on the actual deformation of particles of each individual phase during deposition. The model is validated by comparison with experimental data in the case of zinc‑aluminum mixture, that is known as a promising option for corrosion-resistant coatings thanks to its excellent cathodic protection. The results confirm the adeptness of the proposed model in predicting the deposition efficiency as well as deposit composition variation along the thickness with a high accuracy in the case of multi-material deposits.

Estimating deposition efficiency and chemical composition variation along thickness for cold spraying of composite feedstocks

Ardeshiri Lordejani A.;Guagliano M.;Bagherifard S.
2022-01-01

Abstract

The low working temperature of cold spray technology offers a unique possibility to deposit a wide variety of composite materials by mixing two or more constituent powders. However, while it is possible to precisely control the chemical composition of the mixture before spraying, the compositional yield in the deposit remains uncertain. This is mainly due the variation of deposition kinetics between the constituent phases leading to a compositional deviation with respect to the feedstock. The mismatch in thermo-mechanical properties of the materials included in the feedstock can also lead to the variation of deposit composition along its thickness. Here, we paired a probabilistic approach with finite element simulations to estimate the deposition efficiency of the mixed powder and assess the actual composition of the cold spray multi-material deposit. The developed model accounts for the interaction of the powders with the substrate and estimates the deposition probability based on the actual deformation of particles of each individual phase during deposition. The model is validated by comparison with experimental data in the case of zinc‑aluminum mixture, that is known as a promising option for corrosion-resistant coatings thanks to its excellent cathodic protection. The results confirm the adeptness of the proposed model in predicting the deposition efficiency as well as deposit composition variation along the thickness with a high accuracy in the case of multi-material deposits.
2022
Deposition efficiency
Finite element modelling
Multi-material feedstock
Supersonic spray
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1232076
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