Macroscopic simulation of hydrogen diffusion across the grain-boundary networks in cold-sprayed Ti6Al4V

Hydrogen embrittlement in metallic parts is a critical safety risk in the systems and processes involving hydrogen. Cold spray is a trending solid-state additive repair technique that may repair hydrogen degraded components in future, and hydrogen is also considered a carrier gas for the cold spray process. There is a lack of hydrogen diffusion prediction methods for cold-sprayed deposits since their irregular microstructures are formed by the supersonic impact of particles. This paper presents the image-based realistic modelling and hydrogen diffusion simulation with a grain-boundary network approach on cold-sprayed Ti6Al4V microstructure with heat treatments at 540 degrees C and 750 degrees C. Grain boundaries with a misorientation angle of less than 15 degrees in EBSD mapping are categorized as special boundaries, or else the boundaries are random. The simulation is conducted by utilizing the accessible MATLAB Im2mesh tool and ABAQUS to obtain repeatable results. The high fraction of special boundaries in cold-sprayed deposits due to particle deformation has shown its potential as a grain boundary engineering method to improve hydrogen resistance. Dense special boundaries trap hydrogen and overcome the "short-circuit diffusion effect" by random boundaries. Heat treatment induces recrystallization and reduces the fraction of special boundaries, and consequently deteriorates the performance of hydrogen mitigation. The simulation results reveal that the accuracy highly depends on the quality of EBSD characterization and the experimentally measured hydrogen properties. The image-based framework demonstrates its capability to simulate 2D diffusion across the complicated GB network of cold-sprayed deposits, as well as using GB maps from literature despite the raw EBSD data is not provided. This paper aims to provide insights into understanding hydrogen diffusion behaviour in grain-boundary networks and develop techniques to predict the hydrogenaffected zone over the service life of components.