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Liquid-metal embrittlement (LME) of galvanized (Zn-coated) advanced high-strength steels is a long-known problem in materials science. Here we reveal the initial microstructural processes underneath the Zn-coating that lead to LME-microcrack initiation in the steel substrate. We track the microstructural evolution during the first tens of milliseconds and find pronounced signatures of Fe-Zn intermetallic precipitation in both ferrite grain boundaries and at internal ferrite-oxide phase boundaries. In concert with novel CALPHAD-integrated density-based thermodynamic modelling, we demonstrate that Zn-rich intermetallic phase-nucleation can occur at markedly low processing temperatures due to a segregation transition. We show that a small Znenrichment caused by Zn bulk-diffusion during the initial temperature rise in a joining process is sufficient to induce the segregation transition and subsequent nucleation of Fe-Zn intermetallic grain-boundary phases, which the experiments link to crack initiation sites. These findings direct focus onto LME-controlling microstructural and thermodynamic phenomena at temperatures below the ductility trough and the austenite formation temperature.
Grain boundaries (GBs) are common sites of failure in polycrystalline materials. Recently, a massive Zn segregation transition at Fe GBs was discovered and shown to act as a potent precursor of liquid metal embrittlement (LME) in the Fe-Zn system (Kamachali et al., Scripta Materialia 238 (2024) 115758). In this study, we elaborate on how temperature, GB type and the chemo-structurally coupled phase decomposition at the GB impact this segregation transition. CALPHAD and atomistic simulation data were utilized as inputs to conduct quantitative density-based thermodynamic modeling and phase-field simulations across various GBs, alloy compositions, and temperatures. We reveal that once the segregation transition becomes possible, the GB structural variation stabilizes spinodally formed Zn-rich phases within the GB region, with a higher tendency in disordered GBs. GB phase diagrams were constructed to identify and analyze the range of critical temperatures and alloy compositions associated with the segregation transition. The phase diagrams reveal that the miscibility gap for more disordered GB expands and, although the segregation transition is inevitable and occurs for all GBs, the barrier to triggering it is lower for more disordered GBs. Based on our thermodynamic analyses, potential processing modifications and GB engineering strategies for mitigating segregation-induced LME are thoroughly discussed.
The phase-like behavior of grain boundaries (GBs), recently evidenced in several materials, is opening up new possibilities in the design of alloy microstructures. In this context, GB phase diagrams are contributing to a predictive description of GB segregation and (interfacial) phase changes. The influence of chemo-mechanical solute-GB interactions on the GB phase diagram remains elusive so far. This is particularly important for multi-component alloys where the elastic interactions among solute atoms, of various sizes and bonding energies, can prevail, governing a complex co-segregation phenomenon. Recently, we developed a density-based model for GB thermodynamics that intrinsically accounts for GB elasticity in pure elements. In this work, we incorporate the homogeneous and heterogeneous elastic energies associated with the solutes into the density-based framework. We derive the multi-component homogeneous elastic energy by generalizing the continuum misfitting sphere model and extend it for GBs. The density-based free energy functional directly uses bulk CALPHAD thermodynamic data. The model is applied to binary and ternary Al alloys. We reveal that the elastic energy can profoundly affect the GB solubility and segregation behavior, leading to Cu segregation in otherwise Cu-depleted Al GBs. Consequently, GB segregation transition, i.e., a jump in the GB segregation as a function of alloy composition, is revealed in Al-Cu and Al-Cu-Mg alloy systems with implications for subsequent GB precipitation in these alloys. CALPHAD-informed elasticity-incorporated GB phase diagrams enable addressing a broader range of GB phenomena in engineering multi-component alloys.
Systematic microstructure design requires reliable thermodynamic descriptions of each and all microstructure elements. While such descriptions are well established for most bulk phases, thermodynamic assessment of microstructure defects is challenging because of their individualistic nature. In this paper, a model is devised for assessing grain boundary thermodynamics based on available bulk thermodynamic data. We propose a continuous relative atomic density field and its spatial gradients to describe the grain boundary region with reference to the homogeneous bulk and derive the grain boundary Gibbs free energy functional. The grain boundary segregation isotherm and phase diagram are computed for a regular binary solid solution, and qualitatively benchmarked for the Pt–Au system. The relationships between the grain boundary's atomic density, excess free volume, and misorientation angle are discussed. Combining the current density-based model with available bulk thermodynamic databases enables constructing databases, phase diagrams, and segregation isotherms for grain boundaries, opening possibilities for studying and designing heterogeneous microstructures.
A density-based phase field model is developed where the free energy functional is explicitly linked with molecular dynamics and is referred to as the Molecular Phase Field Method (MoPF). MoPF simulations involve expressing interatomic potentials in terms of density to form a density based free energy functional. Inputs to this functional are taken from atomistics such that the phase field density profile matches the corresponding density profile from atomistic simulations. We analyze our results by comparing the MoPF calculated excess interfacial energies with excess interfacial energies calculated using molecular dynamics associated with several nickel grain boundaries. Additionally, a comparison is made between our results and the interfacial energies of a \Sigma7 boundary across a variety of FCC systems simulated using density functional theory. The MoPF method is able to successfully predict grain boundary free energy trends between grain boundary and material types offering an atomistically informed mesoscale formulation for studying grain boundary physics.
Along with the desire for developing novel multi-principal element alloys, also known as high-entropy alloys, the concern about their safe application is also increasingly growing. This relates to the alloys’ phase stability, in particular, the control required over unexpected phase decompositions resulting from solute segregation at grain boundaries. Yet, the mechanisms of co-segregation and grain boundary phase decomposition in multi-component alloys are rather challenging to explore. In fact, quantitative investigation of grain boundary behaviors is mostly conducted for binary and a few ternary alloys. In this work, we apply the recently introduced CALPHAD-integrated density-based formalism [RSC Advances 10 (2020) 26728-26741] for considering co-segregation phenomena in alloys with an arbitrary number of components —the term ‘co-segregation’ here refers to co-evolution and any mutual interplay among the solute atoms during their interaction with a grain boundary. Quaternary Fe-Co-Mn-Cr alloy system is studied. We present two major advances beyond previous results: First, a co-segregation-induced multi-component grain boundary spinodal decomposition is quantitatively simulated for the first time. We found that in addition to its low cohesive energy and asymmetrical mixing enthalpy due to magnetic ordering, Mn plays a leading role in triggering interfacial phase decomposition by having a relatively large, concentration-dependent atomic mobility. Second, as an alternative to grain boundary phase diagrams proposed for binary and ternary alloys, we introduce the concept of co-segregation maps for grain boundary segregation screening and design in multi-component alloys. Applying the co-segregation maps, the nonlinear Mn and Cr co-segregation are discussed. Depicted on the alloying composition and phase space, the co-segregation maps enable the required insights to guide a safer, more controlled design of high-entropy alloys.
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.
The elastic energy of mixing for multi-component solid solutions is derived by generalizing Eshelby's sphere-in-hole model. By surveying the dependence of the elastic energy on the chemical composition and lattice misfit, we derive a lattice strain coefficient λ*. Studying several high-entropy alloys and superalloys, we propose that most solid solution multi-component alloys are stable when λ*<0.16, generalizing the Hume-Rothery atomic-size rule for binary alloys. We also reveal that the polydispersity index δ, frequently used for describing strain in multi-component alloys, directly represents the elastic energy e with e=qδ², q being an elastic constant. Furthermore, the effects of (i) the number and (ii) the atomic-size distribution of constituting elements on the phase stability of high-entropy alloys were quantified. The present derivations and discussions open for richer considerations of elastic effects in high-entropy alloys, offering immediate support for quantitative assessments of their thermodynamic properties and studying related strengthening mechanisms.
This contribution contains the raw data used to compare experimental results with thermodynamic calculations using the CALPHAD method, which is related to the research article “The AlMo0.5NbTa0.5TiZr refractory high entropy superalloy: experimental findings and comparison with calculations using the CALPHAD method” [1] , and therefore this article can be used as a basis for interpreting the data contained therein. The AlMo0.5NbTa0.5TiZr refractory superalloy was characterized in the cast and annealed condition (1400 °C for 24 h) in order to measure grain size and to identify and measure the size and area fraction of the phases present. The raw data of this article include X-ray diffraction (XRD) measurements, microstructural characterization by scanning and transmission electron microscopy (SEM and TEM), and elemental analysis by energy dispersive X-ray spectroscopy (EDX). XRD includes the determination of phases and the lattice parameters (A2, B2, and hexagonal structure). Microstructural analysis by scanning and transmission electron microscopy includes (1) identification of composition, size, and volume fraction of the present phases and (2) determination of grain size. Based on these experimental data, it is possible to identify similarities and discrepancies with the data calculated using the CALPHAD method for the alloy under study in Ref. [1] , which provides the basis for better and more efficient development of reliable databases.
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.
