Elevated temperature microstructural stability in cast AlCuMnZr alloys through solute segregation
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Solute segregation is a crucial means of stabilizing nanostructured alloys, and at very small grain sizes, this requires consideration of triple junctions (TJs), which attain a meaningful volume fraction and thus become relevant for bulk material behavior. Here, in this study, the solute segregation spectra for grain boundary (GB) and TJ sites are calculated for a large number of dilute Al-based binary systems with available interatomic potentials. A defect-identifying algorithm is applied to quantify the average GB thickness and classify the intergranular site spectra into GB and junction subspectra. The algorithm is also applied to a hybrid electronic-level database for GB segregation of various solutes in Al, yielding polycrystalline TJ solute segregation spectra from first principles. The results suggest that TJ segregation is alloy or interatomic potential dependent and can exhibit either boundary or junction preference. With these spectra as inputs, the spectral GB segregation model gives quantitative predictions of segregation as a function of grain size, temperature, and total solute concentration, suitable for alloy screening and design.
Solute segregation in materials with grain boundaries (GBs) has emerged as a popular method to thermodynamically stabilize nanocrystalline structures. However, the impact of varied GB crystallographic character on solute segregation has never been thoroughly examined. Here, this work examines Co solute segregation in a dataset of 7272 Al bicrystal GBs that span the 5D space of GB crystallographic character. Considerable attention is paid to verification of the calculations in the diverse and large set of GBs. In addition, the results of this work are favorably validated against similar bicrystal and polycrystal simulations. As with other work, we show that Co atoms exhibit strong segregation to sites in Al GBs and that segregation correlates strongly with GB energy and GB excess volume. Segregation varies smoothly in the 5D crystallographic space but has a complex landscape without an obvious functional form.
The atomic structure and chemistry at metal/oxide interfaces play a crucial role in determining their properties. However, studying semi-coherent metal/oxide interfaces that include misfit dislocations through density functional theory (DFT) is often computationally expensive due to the large number of atoms involved, ranging from hundreds to thousands. In this study, we explore solute segregation behavior at the Fe/Y 2 O 3 interface—an important model interface for cladding applications in nuclear fission reactors—by combining DFT calculations with a machine learning (ML) approach. ML models are trained using DFT-calculated segregation energies (𝐸 𝑆𝑒𝑔 ) to identify the key chemical and geometric factors influencing solute segregation at metal/oxide interfaces, revealing the competition between these features in determining 𝐸 𝑆𝑒𝑔 . Moreover, the segregation behavior at a specific Fe/Y 2 O 3 interface is predicted with high accuracy using ML models trained on data from this interface. Furthermore, it is found that the ML models could also predict solute segregation at a different Fe/Y 2 O 3 interface with a new orientation relationship (OR), at a computational cost of less than 1/45 of that required for similar DFT calculations.
θ'-Al 2 Cu precipitates in Al-Cu alloys have various distorted octagon shapes, which can be explained by the competition between {100} and {110} type semi-coherent interfaces with the Al matrix. While most prior studies on the semi-coherent Al/θ' interfaces have focused on the {100} orientation, little is known about the {110} interface. We have investigated the energetics of pristine and solute-segregated {110} semi-coherent Al/θ' interfaces with advanced characterization and first-principles studies. We report interfacial, strain, and solute segregation energetics of the {110} Al/θ' semi-coherent interface for 39 elements and compared them with previously reported values of the {100} interface. We discuss the atomic features and atomic local structures to identify similarities and differences between the two types of Al/θ' semi-coherent interfaces. Here, the isotropy in pristine Al/θ' semi-coherent interfacial energy and the anisotropy resulting from solute segregation provide insight into the formation of different types of θ' precipitate “faces” reported in the literature.
The effect of solid-liquid interface shape on lateral solute segregation during steady-state unidirectional solidification of a binary mixture is calculated under the assumption of no convection in the liquid. A finite element technique is employed to compute the concentration field in the liquid and the lateral segregation in the solid with a curved boundary between the liquid and solid phases. The computational model is constructed assuming knowledge of the solid-liquid interface shape; no attempt is made to relate this shape to the thermal field. The influence of interface curvature on the lateral compositional variation is investigated over a range of system parameters including diffusivity, growth speed, distribution coefficient, and geometric factors of the system. In the limiting case of a slightly nonplanar interface, numerical results from the finite element technique are in good agreement with the analytical solutions of Coriell and Sekerka obtained by using linear theory. For the general case of highly non-planar interface shapes, the linear theory fails and the concentration field in the liquid as well as the lateral solute segregation in the solid can be calculated by using the finite element method.
Particular combinations of solute atoms segregated to the interface of the Al and θ ' - Al 2 Cu in Al-Cu alloys can help stabilize θ ' precipitates at high temperatures. Stabilization of such precipitates is determined by a combination of thermodynamics (including driving forces for coarsening and transformation and solute segregation tendencies) and kinetic effects (including solute diffusion and interfacial mobility in the presence of interfacial solute segregation). For some alloys such as recent Al-Cu-based alloys, multiple solutes segregate in significant quantities to interfaces, and solute-solute interactions at the interface are important, with multiple types of solutes competing for similar interfacial sites. To treat this situation, we develop and apply a statistical mechanics approach to calculate the temperature-dependent equilibrium solute atoms distribution near the coherent and semicoherent interfaces between the Al matrix and the θ ' - Al 2 Cu precipitates. The developed approach is applied to the investigation of Si, Mn, and Zr segregation at the interface, as particular combinations of these elements affect the thermal stability of the θ ' precipitates. We demonstrate that because Si and Mn atoms segregate on the same semicoherent interface, the presence of Si reduces the concentration of Mn solutes at the interface. Si atoms preferably occupy the first layer of the interface and compete with Mn atoms for one type of particular sites in the layer. Mn atoms preferably occupy the second layer of the semicoherent interface, and the Mn-Mn interaction plays an important role in their distribution. Zr atoms mostly segregate on one of the two nonequivalent sites of the second layer of the coherent interface. Due to symmetry properties of the coherent interface, the calculations show that the segregation Zr of atoms to this interface will likely lead to the formation of L 1 2 ordered Al 3 Zr layer.
Solute segregation to individual grain boundaries is used by design to produce strong and stable nanocrystalline metallic alloys. Grain-boundary segregation, however, is known to cause adverse embrittlement effects from a strain-localization failure mechanism that imposes significant material limitations for structural applications. Here, using atomistic simulations, it is discovered that heterogeneous Ni segregation in nanocrystalline Ni-mixed Ag alloys dramatically shuts down localized shear bands during plastic deformation, while simultaneously increasing the tensile strength. Nanocrystalline Cu-mixed Ag metals are predicted to exhibit standard homogeneous Cu segregation and a tensile strength that saturates above a solute concentration of 8 at.% due to glass-like shear localization induced by grain boundaries. By contrast, it is found that heterogeneous Ni segregation in nanocrystalline Ag-Ni alloys forms solute-rich clusters along interfaces leading to strain delocalization at high strain and continuous strengthening at high solute concentrations up to 15 at.%. As a result, this study reveals the importance of heterogeneous versus homogeneous segregation behaviors on strain localization and points to a fundamentally new strategy to design failure-resistant nanostructured materials through grain boundary segregation engineering.
Investigation of semi-coherent metal/oxide interfaces with misfit dislocations using density functional theory (DFT) is computationally intensive to the point of being prohibitive, as it involves several hundreds to many thousands of atoms. In this study, we examined the solute segregation behavior at the Fe/Y 2 O 3 interface—a model interface for cladding applications in nuclear fission reactors—using a combination of DFT calculations and machine learning (ML) approaches. Both coherent and semi-coherent interfaces were considered. ML models were trained on DFT-calculated segregation energies to identify the key chemical, geometric and strain energy related features that govern solute segregation behavior at coherent Fe/Y 2 O 3 interfaces. Furthermore, it was found that ML models when trained on DFT calculated segregation energy of elements at a coherent interface, comprising of about a hundred-atom supercell, can predict the segregation energy of elements at a semi-coherent Fe/Y 2 O 3 interface (with multiple hundreds of atoms) at a fraction of computational cost (1/35th), with an accuracy comparable to DFT calculations.
An Ag–Ni semi-empirical potential was developed to simulate the segregation of Ni solutes at Ag grain boundaries (GBs). The potential combines a new Ag potential fitted to correctly reproduce the stable and unstable stacking fault energies in this metal and the existing Ni potential from Mendelev et al (2012 Phil. Mag. 92 4454–69). The Ag–Ni cross potential functions were fitted to ab initio data on the liquid structure of the Ag 80 Ni 20 alloy to properly incorporate the Ag–Ni interaction at small atomic separations, and to the Ni segregation energies at different sites within a high-energy Σ9 (221) symmetric tilt GB. By deploying this potential with hybrid Monte Carlo/molecular dynamics simulations, it was found that heterogeneous segregation and clustering of Ni atoms at GBs and twin boundary defects occur at low Ni concentrations, 1 and 2 at%. This behavior is profoundly different from the homogeneous interfacial dispersion generally observed for the Cu segregation in Ag. A GB transformation to amorphous intergranular films was found to prevail at higher Ni concentrations (10 at%). In conclusion, the developed potential opens new opportunities for studying the selective segregation behavior of Ni solutes in interface-hardened Ag metals and its effect on plasticity.
Maraging steels are Fe-Ni precipitation-strengthened steels that can be heat treated for achieving high strength with an accompanying loss in ductility, a trend common to most metals. Here, we show that the segregation of Ni during laser powder bed fusion, commonly considered a nuisance that is dealt with via solutionizing heat treatments, can be leveraged via direct aging to achieve higher strength and ductility simultaneously, compared to a solutionized and aged condition. The high dislocation density in combination with solute segregation in the as-fabricated material promotes the precipitation of Mo-rich intermetallic phases that are responsible for the high strength, and the Ni segregated regions facilitate austenite reversion during direct aging. The reverted austenite enhances the elongation via transformation-induced plasticity. While overcoming the strength–ductility conundrum, direct aging can significantly reduce the energy and emissions associated with multistep heat treatments, especially in the global tool and die industry, while laser powder bed fusion (LPBF) can enable tools with integrated cooling channels for increased downstream production efficiency.
Radiation-induced segregation (RIS) has been frequently reported in structural materials such as austenitic, ferritic, and ferritic-martensitic stainless steels (SS) that have been widely used in light water reactors (LWRs). RIS has been linked to secondary degradation effects in SS including irradiation-induced stress corrosion cracking (IASCC). Earlier studies on thermal segregation in Fe-based alloys found that metalloids elements such as P, S, Si, Ge, Sn, etc., embrittle the materials when enrichment was observed at grain boundaries (GBs). RIS of Fe-Cr-Ni-based austenitic steels has been modeled in the U.S. 2015 fiscal year (FY2015), which identified the pre-enrichment due to thermal segregation can have an important role on the subsequent RIS. The goal of this work is to develop thermal segregation models for alloying elements in steels for future integration with RIS modeling.
Grain boundary segregation is of increasing importance for stabilizing nanocrystalline alloys, and while segregation is typically modeled as a scale-independent phenomenon, at the finest nanocrystalline grain sizes there are several sources of grain size dependence. Here we provide quantitative detail on two grain size dependencies not previously elaborated, both of which arise from the spectrality of intergranular segregation sites. The first of these arises because a change in grain size affects which portions of the segregation spectrum are occupied by the solutes, with no change in the shape or nature of the spectrum itself. The second of these arises from the presence of higher-order grain junctions, which have unique segregation behaviors and an increasing relative presence at finer grain sizes. This paper uses molecular statics to quantify these size dependencies in detail for the case of an Al(Mg) binary alloy. Together, these two effects combined have a significant effect on the effective McLean segregation energy of more than 6 kJ/mol (from approximately -18.5 kJ/mol at 5 nm to -12.5 kJ/mol at more than 40 nm), with the majority of grain size dependence arising from the spectrality of segregation sites.
In nanocrystalline alloys, the anisotropy in grain boundary segregation and its impact on dynamic solute drag plays a key role in the thermal stability of these systems during processing treatments or under service conditions.
In this work we apply continuum models to analyze phase change, heat transfer, fluid flow, solute transport, and segregation in order to understand prior neutron imaging observations of the vertical gradient freeze growth of Eu-doped BaBrCl. The models provide a rigorous framework in which to understand the mechanisms that are responsible for the complicated evolution of interface shape and dopant distribution in the growth experiment. We explain how a transition in the solid/liquid interface shape from concave to convex is driven by changes in radial heat transfer caused by furnace design. We also provide a mechanistic explanation of how dynamic growth conditions and changes of the flow structure in the melt result in complicated segregation patterns in this system. A growth pause caused by controller lock-up is shown to result in a band of solute depletion in accordance with classical theory. However, changing flow patterns during growth result in a non-monotonic axial distribution of solute that cannot be explained by simple application of classical segregation models. We assert that the approach presented here, namely the use of rigorous models in conjunction advanced diagnostics, such as neutron imaging, provides an exciting path forward for process optimization and control, accelerating the incremental advances that have, in the past, typically relied on empiricism, experience, and intuition.
Recent reports suggest that interstitial solute additions to body-centered cubic (bcc) high-entropy alloys (HEAs) may enhance their mechanical properties. However, details of interactions between interstitial atoms and dislocations in these HEAs remain incompletely understood. Using first-principles calculations, we examine the energetics of C, N, and O interstitial solutes in elemental bcc metals and NbTaTiHfZr, focusing on their segregation in screw dislocation cores. We examine two types of core sites and show that the low-energy configuration and associated segregation energy depend on the transition metal group. In NbTaTiHfZr, we find that chemical complexity substantially suppresses interstitial segregation in dislocation cores, as fluctuations in bulk solute energies induce energetically favorable sites that disfavor segregation to core sites. Local chemical order further enhances this effect by promoting solute clustering away from dislocation cores. These findings reveal fundamental differences between the behavior of interstitial atoms in elemental metals and HEAs, with implications for high-temperature plasticity and dynamic strain aging.
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