Nanoindentation analyses of (CoCr)100-x Ni x medium-entropy alloys with different Ni contents and crystal orientations were carried out by molecular dynamics simulations. Analyses show that the force-displacement curves during elastic deformation are in good accordance with the Hertz contact theory and the elastic modulus is closely related to the Ni contents and crystal orientations. The elastic-plastic transition point appears later in (CoCr)67Ni33 than in other alloys. The plastic deformation was studied by exploring the instantaneous microstructure, which was found to be dominated by homogeneous nucleation of Shockley partial dislocations and the accumulation of stacking faults, and different levels of dislocation density were produced in the alloys with different Ni contents and crystal orientations. By analyzing the evolution of dislocation density and hardness, a linear relationship between the square root of dislocation density and hardness can be revealed, which agrees well with the classical Taylor hardening model, and the empirical constant is found closely related to crystal orientations.

In this study, a novel multiscale material model is proposed to simulate the elasto-plastic damage-healing behavior of an epoxy matrix in a composite material. This framework combines the non-linear mean field homogenization methodologies with the continuum damage-healing mechanics to achieve the healing process in a coupled manner along with the damage. The model is able to predict the time dependent healing effect combined with damage propagation. In the proposed multiscale model, the healing depends on the current damage of the matrix, the available time that the healing can evolve and the rate of healing. A parametric study with respect to the rate of healing and a time dependency analysis were performed to examine the sensitivity of the model. In addition, a microscale method to calculate the healing initiation and healing efficiency is proposed using a representative volume element of an epoxy matrix with healing microcapsules. The microscale simulation showed that with 7.5% volume fraction of microcapsules 40% of the structural integrity can be recovered.

Significant variations in the tensile strength of unidirectional (UD) fiber-reinforced composites are frequently observed due to randomness in the fiber arrays. Herein, we propose a novel method for predicting tensile strength capable of quantifying uncertainty based on a new recurrence relation for fiber fracture propagation and a determination algorithm for the fracture sequence for random fiber arrays (RFAs). We performed finite element simulations, calculating the stress concentration factor (SCF) for UD composites with various RFAs. Then, we trained an artificial neural network with the obtained SCF data and used it to predict the SCF for composites with an arbitrary RFA. The tensile strength of UD composites was predicted over a range of values, demonstrating that accuracy was superior to conventional prediction methods.

In plane magnetization reversal of permalloy thin truncated conical double-disk as a function of the σ=r/R is investigated using micromagnetic simulations with fixed base radius (R) of 100 nm. When external magnetic field is applied along the longer axis of the double-disk, the remanent states change gradually from vortex state to S state and then to buckled magnetization state with reduction of σ. When σ ≈ 1 and the conical nanodisk resembles to a regular cylindrical nanodisk, incoherent magnetization reversal is dominant whereas tapering of conical disk reduces extent of incoherence in magnetization reversal. As tapering of nanodisk goes extreme so that σ ≈ 0.1, the magnetization reversal is governed only by coherent rotation. Correspondingly, coercive field reduces monotonically as σ increases. On the other hand, when a field is applied in plane but perpendicular to the long axis, almost zero coercivity is discovered. These variations are explained using a analytical calculation of demagnetization factors which quantifies shape anisotropy as well as the consideration of incoherence in magnetization reversal.

This study presents a non-equilibrium molecular dynamics simulation of the shock compression of a [1 1ˉ 0]-oriented CoCrFeMnNi high-entropy alloy (HEA) at 77 K. The effects of different impact velocities on the mechanical properties were investigated in detail, as well as the changes in atomic microstructure and the formation of defects and dislocations under impact loading. In addition, the role of voids in the CoCrFeMnNi HEA was investigated. The results showed that with an increase in impact velocity, the average values of the atomic velocity, temperature, and stress increase. The phenomenon of double-wave separation of the elastic and plastic waves was apparent, and when the loading velocity increased, the propagation velocities of the elastic and plastic waves also increased incrementally. The change in the atomic microstructure and generation of dislocation defects further revealed the effect of different impact velocities on the CoCrFeMnNi HEA. The degree of change in the phase structure was positively correlated with the magnitude of the impact velocity; however, the number of dislocations and defects first increased to a maximum and then decreased with the increase in impact velocity. In addition, the void structure had almost no effect on the phase change of the HEA when subjected to impact loading, whereas the effect on dislocation defects was more pronounced.

Due to the limitations of experimental testing in material size and time scale, this work presents a mechano-electrochemical bidirectional coupling finite element method (FEM) simulation model on account of mechanistic and corrosion kinetics understanding in Al alloy-316L SS galvanic couple. The galvanic corrosion behavior and anodic dissolution deformation of the couple in 3.5 wt.% NaCl solution were analyzed. The effect of external load on galvanic corrosion initiation and propagation was investigated based on Gutman’s theory. The FEM model reveals that the galvanic corrosion is connected with the mechanical damage and the stress concentration coefficient, and highlights the crucial role of corrosion defect in the mechanical behavior of Al alloy. The results show that the external force aggravates the galvanic corrosion at the defects, deteriorating the protection of corrosion products. The thickness of the Al (OH)3 deposition layer reflects the electrochemical reactivity at different positions on the anode surface. The mechanical damage occurs initially at the corrosion defect and then extends to the middle of the anode. The stress concentration coefficient at the center of the anode gradually exceeds the position of the corrosion defect, resulting in mechanical failure at this position.

Auxetic materials or structures possess a negative Poisson’s ratio in contrast to conventional materials, and they shrink or expand transversely under uniaxial compression or tension, respectively. These unique deformation features leads to enhance the mechanical properties compared with the conventional materials. Auxetic tubular structures are of significant interest in the literature because of their superior mechanical qualities, applicability and extensive application. Various auxetic tubular structures with different geometries have been proposed and examined before including conventional peanut-shaped tubular structures. However, application of the peanut-shaped structures is limited due to their low stiffness. In this study, it is aimed to enhance the stiffness of the peanut-shaped tubular auxetic by either adding stiffener to the conventional structure or rotating the unit cell of the structure by a certain angle. Also, the effect of the above-mentioned modifications on the Poisson’s ratio of the structure is investigated. A total of 12 different peanut-shaped auxetics are modelled and the elastic behaviour of these structures under uniaxial compression is compared numerically using finite element simulation. As a result of this analysis, it is observed that both the Poisson’s ratio and stiffness values obtained from the models utilising stiffener were higher than the values obtained from their conventional counterparts. Besides, it is seen that the stiffness values increased while the Poisson’s ratios decreased with the rotation of the unit cell in all of the peanut-shaped tubular auxetics.

The ability to accurately predict the time evolution of precipitate size distributions is fundamental to optimising heat treatments and mechanical properties of engineering alloys. Mean-field models of the particle growth rates assume that diffusion fields between neighbouring particles are weakly coupled reducing the problem to a single particle embedded in an effective medium. This regime of behaviour is expected to be satisfied for low volume fraction alloys. However, these assumptions are not fulfilled in many applications of interest where strong interactions between precipitates holds. Correction factors are often introduced to account for the accelerated rate of diffusion caused by the overlapping of diffusion fields between neighbouring precipitates. This paper applies the Wang–Glicksman–Rajan–Voorhees (WGRV) discrete point-source/sink model to compare descriptions of competitive growth. This includes assessing correction factors to the mean-field particle growth rate derived by Ardell, Marqusee and Ross, and Svoboda and Fischer in addition to Di Nunzio’s pairwise interaction model. The WGRV model is used as a benchmark to compare different approximations of competitive growth that apply similar assumptions. This is followed by the application of the models to simulate precipitation kinetics during long term aging kinetics observed in the nickel-based superalloys IN738LC and RR1000. It is shown that the competitive growth correction factors are accurate for volume fractions of 20% and under-predict the acceleration of precipitate kinetics predicted at 40%. The WGRV model is able to capture the coarsening kinetics observed in both IN738LC and RR1000 with reasonable accuracy. The WGRV model determines particle growth rates as a function of the immediate neighbourhood and provides an improved prediction of the coarsening behaviour of tertiary particles in RR1000 in comparison to the mean-field approximation, however over-estimates the growth rate of the tertiary particles compared to experimental data.

The mechanical behavior of composite interface can be influenced by multiple factors, including the morphological roughness, the structure of coating interphase, and the temperature. Here, high-throughput molecular dynamics (MD) simulations are carried out to investigate the entangled effects of these factors on the shear stiffness G , the friction coefficient μ , the debonding strain ϵd and stress τd , of SiCf/SiC interface. We find that G is maximized by small roughness and high temperature for the optimal chemical bonding effect; μ and ϵd are maximized by large roughness and low temperature, taking advantage of the mechanical interlocking effect while avoiding cusp softening; τd demonstrates two local maxima which result from the competition between chemical bonding and mechanical interlocking. Provided the MD simulation results, a variational autoencoder (VAE) model is proposed to design the microstructure of SiCf/SiC interface for desired shear properties. According to the validations, the VAE-predicted interfacial configuration demonstrates highly similar shear properties to the reference one, justifying its potential for the microstructure design of composite interface. The results of this work can be employed to facilitate the development of SiCf/SiC composite by taking advantage of the synergistic effects of multiple designable factors.

We introduce a phase field crystal (PFC) model for particles with n-fold rotational symmetry in two dimensions. Our approach is based on a free energy functional that depends on the reduced one-particle density, the strength of the orientation, and the direction of the orientation, where all these order parameters depend on the position. The functional is constructed such that for particles with axial symmetry (i.e. n = 2) the PFC model for liquid crystals as introduced by Löwen (2010 J. Phys.: Condens. Matter 22 364105) is recovered. We discuss the stability of the functional and explore phases that occur for 1 ⩽ n ⩽ 6. In addition to isotropic, nematic, stripe, and triangular order, we also observe cluster crystals with square, rhombic, honeycomb, and even quasicrystalline symmetry. The n-fold symmetry of the particles corresponds to the one that can be realized for colloids with symmetrically arranged patches. We explain how both, repulsive as well as attractive patches, are described in our model.

The interactions between the atmospheric gases and the halide perovskite materials are receiving attention in these years before the extensive industrial deployment of halide perovskite materials. In this manuscript, we combine first-principles calculation and machine learning techniques to evaluate the interactions between the atmospheric gas molecules and a two-dimensional Ruddlesden–Popper halide perovskite Cs2PbBr4 surface based on the adsorption energies and automatically design advanced molecular descriptors for the target output. The impacts of density functionals are considered while an accurate machine learning model (r = 0.954 and R 2 = 0.951) is obtained based on the XGBRF ensemble algorithm. Importantly, the symbolic regression automatically finds an effective hybrid descriptor that exhibits high correlation with the target output that is comparable with the machine learning model; the symbolic regression-derived descriptor is mathematically simple and chemistry-aware, which complements the debatable ‘black-box’ machine learning model. Both feature importance ranking and symbolic regression indicate the importance of the functional-dependent energy levels of the perovskite systems and the amide/hydroxyl functional groups of the molecules. The present study highlights the viability of combining density functional theory and machine learning techniques to model the low-dimensional perovskite structures under the atmospheric conditions.

In this work, to understand crack propagation in Al/Ti nanolayered composites, a series of molecular dynamic simulations were performed with crack in different layers of the nanolayered composites and subjected to mode I loading. Nanolayered composite with a crack in Al layer, and monolithic Al show ductile fracture behavior that occurs by nucleation of Shockley partial dislocation at the crack tip. On the other hand, the fracture behavior in nanolayered composites with a crack in Ti shows crack bowing which is similar to the brittle fracture, and subsequent crack trapping at the interface. However, monolithic Ti shows typical cleavage fracture followed by activation of basal and pyramidal ⟨c+a⟩ slip that blunts the crack leading to ductile fracture. When the crack is in the Ti layer, the other Ti layers in a nanolayered composite deform by prismatic and pyramidal ⟨c+a⟩ slip. However, the Ti layer deforms only via slip on prismatic planes when the crack is in the Al layer. Critical strain energy release rate G c based continuum analysis predicts the fracture mode in monolithic Ti correctly, but it fails to predict the fracture mode in monolithic Al and nanolayered composites with crack in the Al layer. It is found that the G c determined based on external loading is marginally higher when the crack is in the Al layer as compared against the case when the crack is in the Ti layer. The G c value for the basal and pyramidal slip in Ti is higher than the G c value for cleavage. This poses an interesting phenomenon since the G c in monolithic Al is found to be much lower than that of monolithic Ti. The reason is attributed to the constrained plasticity in the presence of an Al/Ti interface.

A cellular automaton (CA)-finite element (FE) model was implemented for multi-scale modelling of micro-segregation, mesoscopic grain structure and macroscopic segregation during direct chill (DC) casting of industrial billets or slabs. The macroscopic transport of mass, momentum, energy and solutes was solved on an FE grid, while the mesoscopic grain structure governed by nucleation, growth kinetics and grain evolution was calculated on a CA grid. The solidification path was determined using a modified micro-segregation model for multi-component aluminium alloys. An Euler representation was used for pre-processing and post-processing, and a Lagrangian representation was used for expanding the calculation domain and for resolving the CAFE model. By simulating a DC casting experiment of the 2024 aluminium alloy, a typical grain structure was reproduced, and the composition map showed a reasonable deviation. This model was applied to an industrial-scale DC cast slab of an Al-3.5Cu-1.5 Mg (wt. %) alloy, and three simulations with different nucleation undercoolings were performed for a grain-unrefined slab, a grain-refined slab and an equilibrium solidified slab, respectively. The slabs tended to solidify at equilibrium with the decreasing nucleation undercooling. The earlier release of latent heat yielded a smaller liquid undercooling region ahead of the solidification front, and a finer grain structure. A typical grain structure with coarse equiaxial grains at the centre and fine columnar grains near the bottom surface as well as sidewall was observed for the grain-unrefined slab. By contrast, the grain structure of the grain-refined slab was fully equiaxial. Furthermore, the grain structure, temperature field, melt flow and macro-segregation were quantitatively investigated.

We discuss an active phase field crystal (PFC) model that describes a mixture of active and passive particles. First, a microscopic derivation from dynamical density functional theory is presented that includes a systematic treatment of the relevant orientational degrees of freedom. Of particular interest is the construction of the nonlinear and coupling terms. This allows for interesting insights into the microscopic justification of phenomenological constructions used in PFC models for active particles and mixtures, the approximations required for obtaining them, and possible generalizations. Second, the derived model is investigated using linear stability analysis and nonlinear methods. It is found that the model allows for a rich nonlinear behavior with states ranging from steady periodic and localized states to various time-periodic states. The latter include standing, traveling, and modulated waves corresponding to spatially periodic and localized traveling, wiggling, and alternating peak patterns and their combinations.

Designing composite materials according to the need of applications is fundamentally a challenging and time-consuming task. A deep neural network-based computational framework is developed in this work to solve the forward (predictive) and the inverse (generative) composite design problem. The predictor model is based on the popular convolution neural network architecture and trained with the help of finite element simulations. Conventionally, a large amount of training data is required for accurate prediction from neural network models. A data augmentation strategy is proposed in this study which significantly saves computational resources in the training phase. It shown that the data augmentation approach is general and can be used in any setting involving periodic microstructures. We next use, the property predictor model as a feedback mechanism in the neural network-based generator model. The proposed predictive-generative model is used to obtain the composite microstructure for various requirements such as maximization of elastic properties, specified elastic constants, etc. The efficacy of the proposed predictive-generative model is demonstrated by solving certain class of problems. It is envisaged that the developed model coupled with data augmentation strategy will significantly reduce the cost and time associated with the composite material designing process for varying application requirements.

We present a numerical model to predict oxide scale growth on tungsten surfaces under exposure to oxygen at high temperatures. The model captures the formation of four thermodynamically-compatible oxide sublayers, WO2, WO2.72, WO2.9, and WO3, on top of the metal substrate. Oxide layer growth is simulated by tracking the oxide/oxide and oxide/metal interfaces using a sharp-interface Stefan model coupled to diffusion kinetics. The model is parameterized using selected experimental measurements and electronic structure calculations of the diffusivities of all the oxide subphases involved. We simulate oxide growth at temperatures of 600∘C and above, extracting the power law growth exponents in each case, which we find to deviate from classical parabolic growth in several cases. We conduct a comparison of the model predictions with an extensive experimental data set, with reasonable agreement at most temperatures. While many gaps in our understanding still exist, this work is a first attempt at embedding the thermodynamic and kinetic complexity of tungsten oxide growth into a comprehensive mesoscale kinetic model that attempts to capture the essential features of tungsten oxidation to fill existing knowledge gaps and guide and enhance future tungsten oxidation models.

We present a phase-field crystal model for solidification that accounts for thermal transport and a temperature-dependent lattice parameter. Elasticity effects are characterized through the continuous elastic field computed from the microscopic density field. We showcase the model capabilities via selected numerical investigations which focus on the prototypical growth of two-dimensional crystals from the melt, resulting in faceted shapes and dendrites. This work sets the grounds for a comprehensive mesoscale model of solidification including thermal expansion.

The development of carbon fiber reinforced plastic (CFRP) has revolutionized the light-weight protection materials industry. In the field of aviation, understanding the damage characteristics of CFRP under high-speed impacts is vital to design aero turbofan engines with lightweight fan cases. This study uses a refined solid model of CFRP laminates created by TexGen. ABAQUS/Explicit and VUMAT user subroutine were used to simulate the failure process of CFRP laminates caused by ballistic impact experiments. The study performs a detailed analysis of data recorded during the experiment conducted where Ti-6Al-4V alloy flakes impacted CFRP laminates at velocities ranging from 156.9 m s−1 to 297 m s−1 using a light gas gun. Image recordings through high-speed cameras and 3D-DIC help identify macroscopic damage characteristics like morphology and strain of CFRP laminates. Reliability of numerical simulations was verified via dynamic strain time history curves, scanning electron microscope microstructure images and damage element morphology. Deformation processes such as matrix cracking, fiber pull-out, and delamination play a crucial role in absorbing most of the initial kinetic energy of Ti-6Al-4V alloy flake, and therefore protect the laminate. Given our findings combined with the deformation characteristics and energy absorption mechanism of ballistic impacts, a reliable numerical simulation method for the damage characteristics of Ti-6Al-4V alloy flake penetrating CFRP laminates is presented that provides a basis for designing composite case containment systems.

The combination of classical and ab initio molecular dynamics simulations for computing structural and thermodynamic properties of metallic liquids is illustrated on the example of ruthenium and ruthenium-based alloys. The classical simulations used embedded atom model (EAM) potentials parametrized with the force matching method. The ab initio reference data were obtained using two electronic structure codes implementing the density functional theory plane wave/pseudopotential method. Several methodological aspects in the determination of structural and thermodynamic properties in the liquid phase are examined, first for pure ruthenium. The efficiency of this combined method is finally illustrated on the structure and the pressure of ternary alloys of platinum group metals of interest in the treatment of nuclear wastes.

Elastic interactions between point defects and sinks, such as dislocations and cavities, affect the diffusion of point defects and are responsible for some of the features observed in microstructures under irradiation. It is therefore necessary to include elastic interactions in kinetic simulations for a quantitative prediction of material properties. In this work a method is presented to accurately and efficiently evaluate the strain field in object kinetic Monte Carlo simulations. It can handle any strain field which is biharmonic, such as the one generated by a dislocation segment or a cavity in isotropic elasticity. A speed-up of several orders of magnitude is obtained compared to the direct summation over strain sources, so that simulations over experimental time scales can be performed within reasonable computation times. The case of a thin foil containing a high density of loops under irradiation is investigated. Loop growth rates are found to depend on the loop radius, as shown experimentally, but more complex effects due to the surrounding microstructure are also highlighted.