Synthesis of High-Performance Multi-Component Metallic Materials by Laser Additive Manufacturing via Integrated Modeling and Systematic Experiments

Shunyu Liu, Purdue University

Abstract

This research aims at investigating the direct in-situ synthesis of high-performance multi-component alloys such as high entropy alloys, bulk metallic glasses, and metal matrix composites using the directed energy deposition (DED) process, and modeling the entire solidification and microstructure evolution of these alloys via a novel three-dimensional cellular automata-phase field (3D CA-PF) model. These alloys are currently the focus of significant attention in the materials and engineering communities due to their superior material properties. In the 3D CA-PF model, the growth kinetics including the growth velocity and solute partition at the local solid/liquid interface is calculated by the multi-phase and multi-component PF component, and the 3D CA component uses the growth kinetics as inputs to calculate the dendrite morphology variation and composition redistribution for the entire domain, which could save the computational cost more than five orders of magnitude compared to the PF modeling that can only be applied to small domains due to its heavy computational requirements. Coupled with the temporal and spatial temperature history predicted by the experimentally validated DED model, this computation-efficient 3D CA-PF model can predict the microstructure evolution within the entire macro-scale depositions, which is known to be nonuniform due to the particular nature of additive manufacturing (AM) processes. To achieve the final goal of direct in-situ synthesis of five-component CoCrFeCuNi high entropy alloys (HEA), and modeling of the solidification and microstructure evolution during the DED process, the proposed research is carried out in progressive stages with the increasing complexity of alloy systems. First, a simple binary material system of Ti-TiC composite was studied. The thermodynamically-consistent binary PF model is used to simulate the formation mechanism of detrimental resolidified dendritic TiCx. To capture the polycrystalline solidification, a grain index is introduced to link different crystallographic orientations for each grain. This PF model simulates the microstructure evolution of TiCx in different zones in the molten pool by combining the temperature history predicted by the DED model. The simulated results provide the solution of limiting the free carbon content in the melt, according to which, the formation of TiCxdendrites is successfully avoided by experimentally controlling the melting degree of premixed TiC particulates. Second, the solidification, grain structure evolution, and phase transformation in the DED-built ternary Ti6Al4V alloy under the influences of thermal history are systematically simulated using the established simulation framework and a phase prediction model. The thermal history in a three-track deposition is simulated by the DED model. With such thermal information, the 3D CA model simulates the grain structure evolution on the macro-scale. The thermodynamically-consistent PF model predicts the local grain structure and concentration distributions of solutes Al and V on the micro-scale. The meso-scale CA-PF model captures the sub-grain microstructure evolution and concentration distributions of solutes within the entire molten pool. The dendritic morphology is captured within the large β grains. When the temperature drops below the β-transus temperature, the solid-state phase transformation of β→α/ is studied by the phase prediction model. Based on the predicted volume fractions of and α, the microhardness is also successfully assessed using rules of mixtures.

Degree

Ph.D.

Advisors

Shin, Purdue University.

Subject Area

Engineering|High Temperature Physics|Industrial engineering|Materials science|Optics|Physics|Thermodynamics

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