Functionally graded metal matrix composite of Haynes 282 and SiC fabricated by laser metal deposition

Highlights: • Direct laser metal deposition of functionally graded metal matrix composite structures was successfully fabricated • HY282−SiC gradient deposit in every layer consisted of varying stoichiometry revealing novel microstructures • Increasing SiC particles in HY282 in successive layers resulted in pinning effect leading to grain refinement of γ-matrix • There is a distinct gradation in microstructure and mechanical properties of as-deposited and heat-treated specimens • Heat-treatment conceded microstructural homogeneity, and increased hardness compared to non-equilibrium microstructure. -- Abstract: In the current study, functionally graded metal matrix composite structure of Haynes 282 (HY282) superalloy reinforced with SiC particles with varying composition, structure and property in a single deposit is successfully fabricated using laser metal deposition (LMD). Due to the high laser energy used it was found that SiC disassociated profusely into Si and C with HY282 causing several reaction products that included a Si-rich supersaturated austenitic γ matrix, γ′ Ni3(Al,Ti,Si), M(Ti,Mo)C, M23(Cr,Mo,Si)C6, M6(Mo,Ti)C, M7(Cr, Mo)C3 carbides, and γ/γ′ lamellar eutectics. Due to the rapid cooling nature of the process, the graded structure consists of non-equilibrium microstructure, several deleterious secondary phases, and heavy segregation behavior that lead to unwanted properties. Hence a heat-treatment cycle was performed on the as-deposited sample to ensure homogenization of the microstructures. The influence of composition variation in each layer on the microstructure, chemistry, and microhardness were characterized by scanning electron microscopy, energy dispersive spectroscopy, and micro-indentation techniques. The complex phases found in the graded sample in every layer were estimated by calculation of phase diagrams viewpoint to establish the feasibility of using computational thermodynamic simulations to predict the manifestation of the experimentally observed structure.