Table of contents

Solidification characteristics in the meltpool drive the process-microstructure relationship which helps dictate the material properties of as-built parts in additive manufacturing; therefore, being able to accurately and quickly simulate the size, shape, and solidification characteristics in the melt pool is of great interest to the field. This study investigates various important physical phenomena (dynamic material properties, fluid-flow, radiation and vaporization) which can either be included or neglected in a continuum finite volume model (FVM) and their effect on the solidification conditions. Additionally, since the simplest form of such a model (conduction only) has an analytic solution which is much faster, its viability is also considered. Since the inclusion of some of these physical phenomena will inherently change the net energy input as well as the amount of energy needed to achieve melting of a control volume, each set of included phenomena had an effective absorption efficiency which was calibrated to closely match the dimensions of the melt pool to that of the ground truth data. The ground truth data for this study was defined to be the output of the FVM which included all the physical phenomena (OF). This study then goes on to compare the effects on solidification conditions each of these calibrated models has. It was found that most of the change in solidification conditions comes from the inclusion of latent heat. A posterior correlation factor (PCF) is then introduced to enable an analytic model to predict similar solidification conditions to OF model.

A bimodal precipitation with primary and secondary γ' phase in Ni-17 at.% Al alloys was produced via preaging and continuous cooling. The morphology and composition evolution of γ' phase during cooling process were studied by using phase-field simulation, the bimodal precipitation mechanism was declared. The content of Al in secondary γ' phase is lower than the equilibrium composition because of the slower atom diffusion during continuous cooling. With the increase of cooling rates, the volume fraction and average radius of primary and secondary γ' phase are reduced, the number density of secondary γ' phase increases; in addition, the inter-distance of particle size distribution of primary and secondary γ' phase is widen. A long time of isothermal preaging reduces the precipitation and growth of secondary γ' phase. The hybrider precipitates with bimodal size distribution of γ' phase help optimizing the precipitates morphology of nickel based alloys.

By combining atomistic simulations with a detailed analysis of individual atomic hops, we show that the diffusion of carbon in a binary Fe–C glass exhibits strong (anti-)correlations and is largely determined by the local environment. Higher local carbon concentrations lead to slower atomic mobility. Our results help explain the increasing stability of Fe–C (and, potentially, other similar metal–metalloid glasses) against crystallization with increasing solute concentration.

A new method for the simulation of evolving multi-domains problems has been introduced in previous works and further developed in parallel in the context of isotropic grain growth (GG) with no consideration for the effects of the stored energy (SE) due to dislocations. The methodology consists in a new front-tracking approach where one of the originality is that not only interfaces between grains are discretized but their bulks are also meshed and topological changes of the domains are driven by selective local remeshing operations performed on the finite element (FE) mesh. In this article, further developments and studies of the model will be presented, mainly on the development of a model taking into account grain boundary migration (GBM) by SE. Further developments for the nucleation of new grains will be presented, allowing to model dynamic recrystallization (DRX) and post-dynamic recrystallization (PDRX) phenomena. The accuracy and the performance of the numerical algorithms have been proven to be very promising in Florez et al (2020). Here the results for multiple test cases will be given in order to validate the accuracy of the model taking into account GG and SE. The computational performance will be evaluated for the DRX and PDRX mechanisms and compared to a classical FE framework using a level-set formulation.

Continuum models of dislocation plasticity require constitutive closure assumptions, e.g., by relating details of the dislocation microstructure to energy densities. Currently, there is no systematic way for deriving or extracting such information from reference simulations, such as discrete dislocation dynamics (DDD) or molecular dynamics. Here, a novel data-mining approach is proposed through which energy density data from systems of discrete dislocations can be extracted. Our approach relies on a systematic and controlled coarse-graining process and thereby is consistent with the length scale of interest. For data-mining, a range of different dislocation microstructures that were generated from 2D and 3D DDD simulations, are used. The analyses of the data sets result in energy density formulations as a function of various dislocation density fields. The proposed approach solves the long-standing problem of voxel-size dependent energy calculation during coarse graining of dislocation microstructures. Thus, it is crucial for any continuum dislocation dynamics simulation.

Understanding how intrinsic defects impact magnesium (Mg) crystals mechanics is of prime importance for engineering applications. In this work, the mechanical performance of Mg crystals with cracks at the nanoscale was studied using molecular dynamics method. Influence of the nano-crack type and size on the deformation behavior of Mg crystals was analyzed in details. The obtained results show that the mechanical properties of Mg crystals decrease with the increase of the nano-crack length (perpendicular to the tensile direction). However, the yield stress of Mg crystals is enhanced by increasing the nano-crack width (parallel to the tensile direction) while the nano-crack length remains unchanged. The effect of temperature on Young's modulus of Mg crystals is weak along z-axis, while Young's modulus along y-axis is clearly temperature-dependent. The yield stress of Mg crystals decreases with increasing temperature. The appearance of twins is the main deformation mechanism in Mg crystal along z-axis while the deformation begins with the formation of a prismatic slip along y-axis. The results obtained in this work would provide useful information for further mechanical properties regulation of Mg crystals.

A model for the emission of point defects by point defect sinks is proposed for object kinetic Monte Carlo simulations. Local equilibrium of point defects in the vicinity of sinks is ensured by construction, even if elastic interactions are taken into account for the diffusion of point defects. The emission of vacancies by dislocation segments is treated in detail and validated numerically. The model is then used to simulate the annealing of a vacancy Frank loop in a system containing surfaces. Results are in overall good agreement with analytical formulas, which are based on the approximation of instantaneous equilibration of the vacancy field during the loop evolution process. For small loops the shrinkage is so rapid that this quasi-static approximation is no more valid.

Nitric oxide (NO) is often used for the passivation of SiC/SiO₂ metal oxide semiconductor (MOS) devices. Although it is established experimentally, using XPS, EELS, and SIMS measurements, that the 4H-SiC/SiO₂ interface is extensively nitridated, the mechanisms of NO incorporation and diffusion in amorphous (a)-SiO₂ films are still poorly understood. We used density functional theory (DFT) to simulate the incorporation and diffusion of NO through a-SiO₂ and correlate local steric environment in amorphous network to interstitial NO (NO_i) incorporation energy and migration barriers. Shapes and volumes of structural cages in amorphous structures are characterised using a methodology based on the Voronoi S-network. Using an efficient sampling technique we identify the energy minima and transition states for neutral and negatively charged NO_i molecules. Neutral NO_i interacts with the amorphous network only weakly with the smallest incorporation energies in bigger cages. On the other hand ${\mathrm{N}\mathrm{O}}_{i}^{-1}$ binds at the network sites with wide O–Si–O bond angles, which also serve as the intrinsic precursor sites for electron trapping.

In numerous polycrystalline materials, grain size is controlled by second phase particles (SPPs) that hinder the grain boundaries (GBs) by pinning mechanisms. The Smith–Zener pinning (SZP) model describes the physical interaction between SPPs and GBs. Both of them can evolve when applying a heat treatment to the material. As industrial forging processes involve hot deformation steps near the solvus temperature, it is thus of prime importance to characterize the evolution of the SPPs due to their impact on the final microstructure, notably on the grain size. The level set (LS) method is classically used to describe the influence of SPPs on grain growth (GG) by considering the simulated particles as inert and represented by static holes in the used finite element (FE) mesh. A new formalism to model GG mechanism under the influence of the SZP phenomenon, able to take into account evolving particles is proposed. It involves the representation of SPPs by a LS function and a particular numerical treatment around the grain interfaces encountering SPP, making possible the modelling of SPPs evolution without altering the undergoing pinning pressure. Validation and comparison of the new method regarding previous FE-LS formulation in 2D and 3D simulations and an application on GG under the influence of dissolving particles are described.

Ni-base superalloys show an intricate network of dislocations around γ' precipitates during high-temperature low-to-intermediate stress creep. With an aim to understand the formation of this interfacial dislocation network on the surfaces of unsheared, cuboidal γ' precipitates, we perform three-dimensional discrete dislocation dynamics simulations at constant stress in a model system containing superellipsoidal inclusions. The exponents of the superellipsoid are adjusted to fit the cuboidal shape of γ'. We use a fault-energy-based back-force model to describe interactions between dislocations and structurally inhomogeneous inclusions. The model incorporates climb of edge dislocation segments on non-glissile planes through a modified dislocation mobility law for face-centred cubic crystals. Athermal repulsive intersection cross-slip is considered for the screw segments. We systematically show the evolution of dislocation network as a function of applied stress, inter-particle spacing, and ratio of glide-to-climb mobility. We scale the simulation box and the inclusions by the same factor in order to keep the volume fraction of inclusions constant in all cases. Although the dislocation density increases with the increase in applied stress as well as inter-particle spacing, the onset of steady-state in all cases is marked by a constant mobile-to-immobile dislocation density (ρ^m/ρ^im) ratio. For the range of stresses and inter-particle spacings considered in this study, the steady-state ρ^m/ρ^im remains nearly the same. Our simulations indicate a power-law behaviour where the stress exponent n ≈ 4 suggests dislocation climb to be the rate-controlling mechanism. The simulated morphological features of the dislocation network formed on the surfaces of the inclusions at steady-state (e.g., hexagonal nets due to dislocation reactions) are similar to those observed experimentally in single-crystalline superalloys crept at high temperatures and low stresses. Moreover, we obtain a relationship between length scale associated with dislocation density and applied stress.

Simulating the frictional properties of complex interfaces is computational resource consuming. In this paper, we propose a density functional theory (DFT) calculation combined machine learning (ML) strategy to investigate the sliding potential energy corrugation between geometrical corrugated graphene (Gr) sheets. By the aid of few DFT calculations and geometrical descriptors Σr⁻ⁿ (n = 1, 2, 6, 12), the trained ML models can accurately predict the sliding potential evolutions of Gr/Pt and Gr/Re systems. To be specific, based on DFT calculations of sliding along [110] direction, the trained linear regression (LIN) models can properly give out the potential energy evolution along the [100] direction with deviation less than 5%. By the dataset of given distances (9.3 Å, 9.65 Å and 10 Å) between two Re monolayers in Gr/Re systems, LIN and Bayesian ridge regression (BR) models can quantitatively predict the potential energy evolution of unknown distances (9.2 Å, 9.4 Å, 9.5 Å and 9.6 Å). The predicted magnitudes of potential energy corrugations by BR model divert less than 3 meV Å⁻² from DFT calculations. The prediction results for extrapolated distances (9.0 Å and 9.1 Å) deviate notably, but the extension of training dataset effectively improves the predictive ability of ML models, especially for the LIN model. Thus, the supposed strategy could become an effective method to investigate the frictional characteristics of complex interfaces.

Small organic multiamine and multihydroxyl molecules have great potential for enhancing overall properties of poly(vinyl alcohol) (PVA) through the cross-linking effect of hydrogen bonds. However, experimentally there remains a remarkable lack of insightful understanding of the cross-linking effect on a molecular level. In the work, we report molecular dynamics simulations to reveal the cross-linking effect of hydrogen bonds of tetraaminopyrimidine (4N-2456) molecules on the structure, chain dynamics and mechanical properties of the PVA matrix. It was found that the addition of 4N-2456 leads to a nonlinear decrease of the free volume of PVA. A critical concentration of 4N-2456, about 5 wt%, was identified, resulting in the formation of 4N-2456 clusters. At this concentration, the PVA chains show the relatively slow mobility, the higher glass transition temperature and elastic modulus. Further increasing the 4N-2456 concentration enhances aggregation, and conversely weakens the interactions of hydrogen bonds between the PVA chains. Our work offers an understanding of how the 4N-2456 molecules influence the PVA chain dynamics and mechanical properties of the PVA matrix on molecular level.

In this study, we simulate the radiation-induced phase transition in the binary alloy employing the modified Cahn–Hilliard (CH) equation that accounts for the process of radiation-enhanced diffusion, ballistic mixing, and compositional fluctuations. The influence of displacement rate on the dynamics of the average radius, number density, nucleation rate, and volume fraction of the second phase is discussed. Also, the mechanism of precipitate vanishing under irradiation condition is revealed.

Phase decomposition in binary Fe_1−xCu_x is studied using Monte Carlo simulations. Initially, density functional theory calculations are utilized to determine reference energies of various Fe–Cu compounds that serve as input for a temperature and composition-dependent cluster expansion. On this basis, the thermodynamic properties of the bcc Fe–Cu system are predicted and used to simulate the equilibrium constitution of bcc Cu-rich precipitates in an Fe-rich solid solution at various temperatures and supersaturations. Complementarily, computationally efficient pair potentials are developed in the local chemical environment approach that are calibrated on the first principles-cluster expansion results. These are then utilized in large-scale simulations for analysis of the multi-particle precipitate evolution. It is concluded that both approaches provide comparable information in terms of the precipitate radius as well as interface constitution. Whereas the cluster expansion ('full-information') path is especially useful in predicting energies of various ground state configurations for small systems, the local chemical environment approach ('fast-computation') path is particularly useful in evaluation of cluster formation kinetics and evolution statistics.

Micromechanical analysis of a representative volume element (RVE) is commonly performed to estimate the material's effective/homogenized properties in a multiscale analysis of deformation of materials. Typically numerical analysis techniques such as the finite element (FE) method are used for such an analysis. A highly refined FE mesh is required to capture microstructure features accurately for the analysis of RVE. However, this increases the number of degrees of freedom and affects computational time adversely. In this contribution a total finite element tearing and interconnection (TFETI) domain decomposition method based approach is presented for a computationally efficient micromechanical analysis. Two critical aspects of the micromechanical analysis, namely, a) computationally efficient solution of the boundary value problem and b) ease of computation of effective properties, are addressed in this work. This work focuses on the displacement driven micromechanical analysis where the boundary conditions are available in terms of displacements over the entire boundary. Two types of displacement boundary conditions, viz uniform or proportional displacements and periodic displacements corresponding to the state of uniaxial extension and simple shear are considered. The performance of the adapted TFETI with commonly used preconditioners, namely Dirichlet and lumped, for such displacement driven analysis is investigated. An efficient algorithm that exploits the structure of the TFETI method is proposed to calculate the effective properties. The proposed method's efficacy is demonstrated by analyzing some representative model problems of composite materials. It is observed that the method's performance depends on various problem parameters such as volume fraction, the shape of inclusion, the distance between the inclusions, and the contrast between the material properties of matrix and inclusion. The performance also depends on the numerical method parameters, such as the number of subdomains, shape of subdomains, and preconditioners. Therefore, a systematic study is carried out to study the influence of these parameters on the method's performance.