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At least 307 records · Page 17

A Phase-Field Study on Internal to External Oxidation Transition in High-Temperature Structural Alloys

Structural alloys applied at high temperatures rely on an external dense layer of oxide scale for protection. As some reactive alloy components are selectively oxidized internally, understanding how these dispersed metal oxide particles reach the surface to form a protective scale—the so-called internal to external oxidation transition—is crucial for designing these alloys. While the literature is replete with experimental studies on oxidation of alloys, there is a lack of computational studies in this realm due to the complex nature of coupled reaction and diffusion processes in multicomponent multi-phase alloy systems. In this work, we apply a recently developed phase-field model to simulate the oxidation processes under different compositions and nucleation scenarios to gain insights into how a continuous oxide scale can be established. The results show that while alloy composition is critical for internal to external oxidation transition, the oxide nuclei size, shape and distribution also have significant impact on the transition kinetics.

36 MATERIALS SCIENCE↗

Investigation of fracture in porous materials: a phase-field fracture study informed by ReaxFF

Microscopic features (e.g, pore shapes, sizes, and distribution) in porous material substantially affect the overall mechanical properties such as stiffness and strength. In turn, these material properties determine the macroscopic behaviors of fracture in the porous material. In certain cases, macroscopic properties can be derived from the porous skeleton and void ratio (i.e., porosity), but in many other cases, such derivation is a challenging task. This paper presents a numerical investigation of microporosity and micropore shapes effect on the macrofracture behavior in porous amorphous silica. For this study, we extend the recently-proposed combined molecular dynamic (MD) and phase-field (PF) fracture modeling approach by including different pore shapes in the atomistic domain. In the MD simulations, we adopt ReaxFF to evaluate the material properties, where four different micropore cases are considered. Based on the material properties derived from MD simulations, the macrofracture propagation of porous media is studied using hybrid PF simulation. In the characterization of the pore structure, the concept of pore ligament is proposed to relate the pore shape and the critical energy release rate. Two classical fracture problems were used to evaluate the effect of pore shape on the macrofracture behavior. The results of the case study show that although the micropore shapes change the macrofracture behaviors, these effects vary with the geometry and loading conditions of macroscopic boundary value problems. Furthermore, the case study also shows that the influence of micropore structure can be captured at the macroscopic level through the material properties derived from the MD simulations.

42 ENGINEERING↗

Causality-respecting adaptive refinement for PINNs: enabling precise interface evolution in phase field modeling

Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving physical systems described by partial differential equations (PDEs). However, their accuracy in dynamical systems, particularly those involving sharp moving boundaries with complex initial morphologies, remains a challenge. Here, this study introduces an approach combining residual-based adaptive refinement (RBAR) with causality-informed training to enhance the performance of PINNs in solving spatio-temporal PDEs. Our method employs a three-step iterative process: initial causality-based training, RBAR-guided domain refinement, and subsequent causality training on the refined mesh. Applied to the Allen-Cahn equation, a widely-used model in phase field simulations, our approach demonstrates significant improvements in solution accuracy and computational efficiency over traditional PINNs. Notably, we observe an ‘overshoot and relocate’ phenomenon in dynamic cases with complex morphologies, showcasing the method’s adaptive error correction capabilities. This synergistic interaction between RBAR and causality training enables accurate capture of interface evolution, even in challenging scenarios where traditional PINNs fail. Our framework not only resolves the limitations of uniform refinement strategies but also provides a generalizable methodology for solving a broad range of spatio-temporal PDEs. The enhanced performance of the RBAR–causality combined framework demonstrates its strong potential for advancing PINN-based modeling of physical systems characterized by complex, evolving interfaces.

Allen-Cahn equations↗

Phase-field modeling of thermally-grown oxide and damage evolution in environmental barrier coatings

Silicon carbide-based ceramic matrix composites protected by environmental barrier coatings (EBCs) present a promising materials solution for next-generation gas turbines. Developing more robust and efficient EBCs is therefore of significant technological importance. During the service in high-temperature oxidative environments, there is a thermally grown oxide (TGO) layer, spontaneously formed in the EBC system. TGO is recognized as a critical factor for the degradation and failure of EBCs, yet the detailed mechanisms of TGO growth and its effect on EBC failure remain unclear. In this study we develop a comprehensive chemo-mechano-phase-field model to simulate growth of the TGO in EBCs, factoring in creep and deformation, and especially the cracking behaviors. The volume expansion due to TGO growth and the resulting large inelastic deformation are addressed by using our recently developed, so-called incremental realization of inelastic deformation (IRID) algorithm, in combination with an adapted Hu-Chen spectral solver for elasticity. Simulations of TGO growth are performed considering different growth modes of TGOs determined mainly by the ratio of oxidant permeability in the topcoat to that in the TGO itself. Large-scale three-dimensional (3D) simulations are performed to model the formation of interconnecting vertical/channel cracks (often called ‘mud cracks’). The simulated crack morphology are in excellent agreement with the experimental observations from the literature. The simulations also provide insights into the cracking of EBCs and its dependence on the structure and constituent properties of the coating system. Furthermore, these results demonstrate the developed damage model can be a useful tool for design of more durable EBCs.

Cracking↗

A numerical-homogenization based phase-field fracture modeling of linear elastic heterogeneous porous media

Most porous media, such as geomaterials and biomaterials are highly heterogeneous in nature, and they contain large variations of microscopic pore structures, such as pore sizes, pore distribution, and pore shapes. The oscillation of microscopic structures is a substantial challenge in theoretical characterization and is usually ignored in continuous modeling. However, mechanical behavior of porous media such as deformation and failure, are essentially impacted by the microscopic heterogeneity which needs to be considered in modeling a porous media. Here, this research proposes a numerical modeling framework with a capability to investigate the effect of microscopic heterogeneity on the macroscopic fracture behavior in porous media by using a numerical homogenization technique, combined with the phase-field fracture modeling method. This numerical modeling strategy computes a homogenized elasticity tensor based on microscopic heterogeneous pore structures heterogenous porous domain by solving boundary value problems at microscopic domain. The strain energy and subsequent propagation of macroscopic fractures will be updated using homogenized stiffness information. Using this numerical scheme, the microscopic pore structure’s impact on the fracture behavior through the homogenized elastic tensor will be taken into account. This multiscale technique is benchmarked against classical problems. Finally, the results highlight the importance of the underlying pore structure and reveal that both fracture strength and propagation path can be influenced by the microscopic heterogeneity.

36 MATERIALS SCIENCE↗

Linearly first- and second-order, unconditionally energy stable schemes for the phase field crystal model

In this paper, we develop a series of linear, unconditionally energy stable numerical schemes for solving the classical phase field crystal model. The temporal discretizations are based on the first order Euler method, the second order backward differentiation formulas (BDF2) and the second order Crank–Nicolson method, respectively. The schemes lead to linear elliptic equations to be solved at each time step, and the induced linear systems are symmetric positive definite. We prove that all three schemes are unconditionally energy stable rigorously. Various classical numerical experiments in 2D and 3D are performed to validate the accuracy and efficiency of the proposed schemes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Towards inverse microstructure-centered materials design using generative phase-field modeling and deep variational autoencoders

The field of Integrated Computational Materials Engineering (ICME) combines a broad range of methods to study materials’ responses over a spectrum of length scales. A relatively unexplored aspect of microstructure-sensitive materials design is uncertainty propagation and quantification (UP/UQ) of materials’ microstructure, as well as establishing process-structure–property (PSP) relationships for inverse material design. In this study, an efficient UP technique built on the idea of changing probability measures and a deep generative unsupervised representative machine learning method for microstructure-based design of thermal conductivity of materials is proposed. Probability measures are used to represent microstructure space, and Wasserstein metrics are used to test the efficiency of the UP method. By using deep Variational AutoEncoder (VAE), we identify the correlations between the material/process parameters and the thermal conductivity of heterogeneous dual-phase microstructures. Through high-throughput screening, UP, and the deep-generative VAE method, PSP relationships that are too complex can be revealed by exploiting the materials’ design space with an emphasis on microstructures. As a last point, we demonstrate generative machine learning serves as a useful tool for inverse microstructure-centered materials design, and we demonstrate this by examining the inverse design of thermal conductivity in nano-structured materials. Here, the results reveal the effects of morphology, volume fraction, characteristic length scale, and the individual thermal diffusivity of phases on the thermal conductivity of dual-phase alloys. Our findings emphasize the advantages of high-throughput phase-field modeling and generative deep learning for linking PSP and inverse microstructure-centered materials design.

36 MATERIALS SCIENCE↗

Cohesive phase-field chemo-mechanical simulations of inter- and trans- granular fractures in polycrystalline NMC cathodes via image-based 3D reconstruction

The optimal design and durable utilization of lithium-ion batteries necessitates an objective modeling approach to understand fracture and failure mechanisms. This paper presents a comprehensive chemo-mechanical modeling study focused on elucidating fracture-induced damage and degradation phenomena in the polycrystalline Li $\mathcal{x}$ Ni 0.5 Mn 0.3 Co 0.2 O 2 (NMC532) cathode. An innovative approach that utilizes image-based reconstructed 3D geometry as finite element (FE) mesh input is employed to enhance the precision in capturing the convoluted architecture and morphological features. For accurately representing the intricate crack configurations within the polycrystalline system, we adopted the cohesive phase-field fracture (CPF) model. Through the integration of advanced image-based geometry reconstruction technique and the promising CPF modeling approach, lithium (de)intercalation induced crack evolution (e.g., nucleation, propagation, branching and diverse modes including inter-/trans-(intra-) granular patterns) and the resulting chemical degradation can be precisely captured, which is also compared and validated with numerical predictions using a continuum damage model. In particular, this model predicts fracture induced degradation under varying fracture properties of grain boundaries and charging rates; the conclusion that NMC particles comprised of larger grains are predicted to have less degradation than those with smaller grains can also be drawn. This comprehensive analysis provides valuable insights into the fracture and degradation within polycrystalline NMC cathodes.

25 ENERGY STORAGE↗

Coupled phase field damage and crystal plasticity analysis of intragranular fracture: The role of crystallographic orientation and voids

Damage evolution in engineering metal alloys at the grain scale exhibits significant microstructural heterogeneity and anisotropy. These heterogeneities create local hotspots for stress and strain localization, leading to void nucleation. Crystal orientation influences the active slip systems around voids, affecting lattice rotation and potentially forming discontinuities. At low triaxiality, voids may change shape due to lower stress, rotation, elongation, and coalescence. At high triaxiality, the correlation between crystal orientation and void growth rate becomes stronger, resembling the behavior observed in isolated single crystals. Therefore, understanding the effects of crystal orientation, heterogeneous strain, and defect evolution is crucial for single crystal fracture characterization. Here, in this work, a coupled phase-field damage (PFD) and crystal plasticity (CP) model is implemented within a finite element framework to analyze crystal deformation and failure. The CP method employs a dislocation density-based constitutive model, while intragranular failure is modeled using an anisotropic PFD method. The PFD model considers both the stored energy due to elastic stretching and the energy release due to defect formation and crack formation. A single crystal Al2219 with an intracrystalline spherical void is chosen to analyze fracture. The study finds that fracture propagation is strongly correlated with crystal orientations. This coupled CP-PFD model provides accurate failure prediction in crystalline materials by incorporating the effects of crystal orientations and existing voids. This study demonstrates how the local microstructure and defects influence plastic deformation and failure mechanisms in metal alloys.

Aluminum alloy↗

Hyperelastic phase-field fracture mechanics modeling of the toughening induced by Bouligand structures in natural materials

Bouligand structures are widely observed in natural materials; elasmoid fish scales and the exoskeleton of arthropods, such as lobsters, crabs, mantis shrimp and insects, are prime examples. In fish scales, such as those of the Arapaima gigas, the tough inner core beneath the harder surface of the scale displays a Bouligand structure comprising a layered arrangement of collagen fibrils with an orthogonal or twisted staircase (or plywood) architecture. A much rarer variation of this structure, the double-twisted Bouligand structure, has been discovered in the primitive elasmoid scales of the coelacanth fish; this architecture is quite distinct from “modern” elasmoid fish scales yet provides extraordinary resistance to deformation and fracture. Here we examine the toughening mechanisms created by the double-twisted Bouligand structure in comparison to those generated by the more common single Bouligand structures. Specifically, we have developed an orientation-dependent, hyperelastic, phase-field fracture mechanics method to computationally examine the relative fracture toughness of elasmoid fish scales comprising single vs. double-twisted Bouligand structures of fibrils. The model demonstrates the critical role played by the extra inter-bundle fibrils found in coelacanth fish scales in enhancing the toughness of Bouligand-type structures. Synthesis and fracture tests of 3-D printed Bouligand-type materials are presented to support the modeling and complement our understanding of the fracture mechanisms in Bouligand-type structures.

3-D printing↗

Analysis of a new multispecies tumor growth model coupling 3D phase-fields with a 1D vascular network

In this study, we present and analyze a mathematical model for tumor growth incorporating ECM erosion, interstitial flow, and the effect of vascular flow and nutrient transport. The model is of phase-field or diffused-interface type in which multiple phases of cell species and other constituents are separated by smooth evolving interfaces. The model involves a mesoscale version of Darcy’s law to capture the flow mechanism in the tissue matrix. Modeling flow and transport processes in the vasculature supplying the healthy and cancerous tissue, one-dimensional (1D) equations are considered. Since the models governing the transport and flow processes are defined together with cell species models on a three-dimensional (3D) domain, we obtain a 3D–1D coupled model.

3D–1D coupled blood flow models↗

Dendritic Growth Under Natural and Forced Convection in Al-Cu Alloys: From Equiaxed to Columnar Dendrites and from 2D to 3D Phase-Field Simulations

The interaction between convection and solute transport during solidification has significant influence on the dendritic evolution. By employing the phase-field lattice-Boltzmann approach together with the parallel and adaptive-mesh-refinement algorithm, the dendritic evolution under convection is simulated in both 2D and 3D cases. The flow-induced redistribution of the solute alters both tip velocity and the development of dendritic arms. The effect of both convection and undercooling is quantified and compared using the length ratio of the dendritic arms. The effect of convection behavior (i.e., natural and forced) and domain dimension (i.e., 2D and 3D) on dendritic growth is discussed. Results show that the convection effect is mainly dominated by the convection mode, and the melt flow in 2D can produce biased results comparing with those in 3D.

36 MATERIALS SCIENCE↗

Phase-field modeling of stored-energy-driven grain growth with intra-granular variation in dislocation density

Abstract We present a phase-field (PF) model to simulate the microstructure evolution occurring in polycrystalline materials with a variation in the intra-granular dislocation density. The model accounts for two mechanisms that lead to the grain boundary migration: the driving force due to capillarity and that due to the stored energy arising from a spatially varying dislocation density. In addition to the order parameters that distinguish regions occupied by different grains, we introduce dislocation density fields that describe spatial variation of the dislocation density. We assume that the dislocation density decays as a function of the distance the grain boundary has migrated. To demonstrate and parameterize the model, we simulate microstructure evolution in two dimensions, for which the initial microstructure is based on real-time experimental data. Additionally, we applied the model to study the effect of a cyclic heat treatment (CHT) on the microstructure evolution. Specifically, we simulated stored-energy-driven grain growth during three thermal cycles, as well as grain growth without stored energy that serves as a baseline for comparison. We showed that the microstructure evolution proceeded much faster when the stored energy was considered. A non-self-similar evolution was observed in this case, while a nearly self-similar evolution was found when the microstructure evolution is driven solely by capillarity. These results suggest a possible mechanism for the initiation of abnormal grain growth during CHT. Finally, we demonstrate an integrated experimental-computational workflow that utilizes the experimental measurements to inform the PF model and its parameterization, which provides a foundation for the development of future simulation tools capable of quantitative prediction of microstructure evolution during non-isothermal heat treatment.

Materials Science↗

Controlled Solidification of Liquids Within the SFC Primary Phase Field of the “Fe{sub 2}O{sub 3}”-CaO-SiO{sub 2} System in Air

To provide fundamental information on the phases and microstructures formed during sintering, a liquid with a bulk composition within the silico ferrite of calcium (SFC) primary phase field in the ternary “Fe{sub 2}O{sub 3}”-CaO-SiO{sub 2} system in air was solidified at a controlled rate. Samples of a bulk composition with a CaO/SiO{sub 2} ratio of 4.00 and 69.24 wt pct Fe{sub 2}O{sub 3}, were cooled from 1623 K (1350 °C) at 2 K/s, with samples quenched at temperatures between 1513 K (1240 °C) to 1453 K (1180 °C). The silico ferrite of calcium and aluminium I (SFCA-I) and Ca{sub 7.2}Fe{sub 0.8}{sup 2+}Fe{sub 30}{sup 3+}O{sub 53} phases were observed to form an intergrowth (‘SFC-I’) rather than the anticipated SFC phase. Solidification was found to occur in three stages, Liquid + ‘SFC-I’, Liquid + ‘SFC-I’ + C{sub 2}S + CF{sub 2}, and C{sub 2}S + CF{sub 2} + CF, where C{sub 2}S denotes dicalcium silicate, CF denotes calcium ferrite and CF{sub 2} denotes calcium diferrite. The phases formed and the solidification sequence differ from those predicted under equilibrium and Scheil–Gulliver Cooling. Although not directly applicable to industrial operations, this research clearly shows that the formation of both the SFCA and SFCA-I phase in iron ore sinters is controlled by kinetic processes rather than equilibrium conditions.

36 MATERIALS SCIENCE↗

Investigation on Microsegregation of IN718 Alloy During Additive Manufacturing via Integrated Phase-Field and Finite-Element Modeling

In this work, we apply a multi-scale model combining finite-element method (FEM) and phase-field model (PFM) to simulate the evolution of solidification microstructures at different locations within a molten pool of an additively manufactured IN718 alloy. Specifically, the FEM is used to calculate the shape of molten pool and the relative thermal gradient G at the macroscale. Then, the calculated thermal information is input into PFM for microstructure simulation. Finally, the morphology of solidification structures and formation of Laves phase at different sites are studied and compared. We found that the solidification site with a large angle between the temperature gradient and the preferred crystalline orientation could build up a high niobium (Nb) concentration in the liquid during solidification but has less possibility of forming continuous long chain morphology of Laves phase particles. This finding provides an understanding of the microstructure evolution inside the molten pool of IN718 alloy during solidification. Further, the finding indicates that the site with a large misorientation angle will have a good hot cracking resistance after solidification.

36 MATERIALS SCIENCE↗

Strain effects on domain structures in ferroelectric thin films from phase‐field simulations

Abstract Strain and applied external electric fields are known to influence domain evolution and associated ferroelectric responses in ferroelectric thin films. Here, phase‐field simulations are used to predict equilibrium domain structures and polarization‐field ( P ‐ E ) hysteresis loops of lead zirconate titanate (PZT) thin films under a series of mismatch strains, ranging from strongly tensile to strongly compressive. In particular, the evolution of domains and the P ‐ E curves under different applied strains reveal the mesoscale mechanism, the appearance of in‐plane polarization during domain switching, that is responsible for a relatively small coercive field and remnant polarization. A Landau energy distribution is analyzed to better understand the domain evolution under various strain conditions. The results provide guidance for choice of mismatched strains to yield the desired P ‐ E hysteresis loops and the domain structures.

Lin, Fang‐Yin↗