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Several recent studies have revealed that the phase decomposition in medium- and high-entropy alloys is triggered by solute segregation at grain boundaries. The chemically complex nature of these alloys already clues that such segregation in materials should be something more than the interaction between solutes and grain boundary, but also affected by the solute-solute interactions during the segregation. In fact, experiments indicate the significance of such solute-solute interaction. Yet, the mechanisms of co-segregation in multi-component alloys are rather challenging to explore and rarely studied quantitatively. Recently, a CALPHAD-integrated density-based phase-field model has been proposed for studying grain boundary phenomena. Several applications of this model have shown its expansive capacity for investigating grain boundary segregation and phase behavior. In this talk, the applications of this model to studying co-segregation phenomena and grain boundary phase diagrams in multi-component alloys are presented ––the term ‘co-segregation’ here refers to co-evolution and any mutual interplay among the solutes and grain boundary during the segregation. In particular, the iron-based ternary and quaternary alloys are discussed. I show how a grain boundary may have its own miscibility gap and how this immiscibility can influence the co-segregation behavior. As an alternative to grain boundary phase diagrams, rather suited for binary and ternary alloys, a new concept of co-segregation maps for screening and segregation design in multi-component alloys is presented. Applying the co-segregation maps, the nonlinear Mn and Cr co-segregation in Fe-Co-Mn-Cr is discussed.
Experimentally informed multiscale creep modelling of additive manufactured Ni-based superalloys
(2023)
Excellent creep resistance at elevated temperatures, i.e. T / T_m> 0.5, due to γ-γ’ microstructure is one of the main properties of nickel-based superalloys. Due to its great importance for industrial applications, a remarkable amount of research has been devoted to understanding the underlying deformation mechanism in a wide spectrum of temperature and loading conditions. Additive manufactured (AM) nickel-based superalloys while being governed by similar γ-γ’ microstructure, exhibit AM-process specific microstructural characteristics, such as columnar grains, strong crystallographic texture (typically <001> fiber texture parallel to build direction) and compositional inhomogeneity, which in turn leads to anisotropic creep response in both stationary and tertiary phases.
Despite the deep insights achieved recently on the correlation between process parameters and the resulting microstructure, the anisotropic creep behavior and corresponding deformation mechanism of these materials are insufficiently understood so far. One reason for this is the lack of capable material models that can link the microstructure to the mechanical behavior. To overcome this challenge, a multiscale microstructure-based approach has been applied by coupling crystal plasticity (CP) and polycrystal model which enables the inclusion of different deformation mechanisms and microstructural characteristics such as crystallographic texture and grain morphology. The method has been applied to experimental data for AM-manufactured INCONEL-738LC (IN738). The effect of different slip systems, texture, and morphology on creep anisotropy at 850°C has been investigated. Results suggest a strong correlation between superlattice extrinsic stacking fault (SESF) and microtwinning and observed creep anisotropy.
Grain boundary (GB) chemical and structural variations can significantly influence materials performance. The former is generally ascribed to the structural gradient between the grain and GB. While GB segregation may be accompanied by chemical and structural variations, clear insights about the GB’s thermodynamic phase behaviour upon coupling between its chemistry and structure is lacking. Using the CALPHAD integrated density-based phase field model, we study the co-evolution of GB’s structure and segregation in Fe-Mn alloys. We found that the GB segregation transition is amplified if its structure can respond to chemical variation. Additionally, the coupling between GB structural and segregation evolution was found to enable co-existence of the spinodally formed low- and high-Mn phases within the GB. In the light of atomistic simulations, we expand on investigating the correlation between the parameters that characterise the GB density map with GB properties.
Recent advances in Deep Learning (DL) have significantly impacted the field of materials modelling. DL tools have been recently considered as promising tools to address the complex relationships among processing, microstructure and property of materials. The thermal stability of polycrystalline materials is a highly interesting and complex problem that could be addressed using DL techniques. The Multi-Phase-Field (MPF) method has emerged as a powerful tool for addressing grain growth phenomena from multiple perspectives. Unlike sharp-interface based methods, the MPF approach bypasses the need for detailed information on individual grains. In this work, we use DL to address issues related to MPF simulations of grain growth including numerical efficiency, computing speed, and resource consumption. This presents specific challenges for high-performance computing (HPC) due to the large datasets and complex computations required by both MPF and DL methods. We study various 3D microstructure settings with the goal of accelerating the simulation process while exploring different physical effects. In particular, the impact of grain boundary and triple junction energies on grain growth are to be investigated. The results will be presented in terms of the evolving size and shape distribution of the grains.