Table of contents

Thermal welding is a common joining technique for polymers. In this work we study the effect of various process parameters on the strength and ductility of a symmetric thermally welded joint through molecular dynamics (MD) simulations on carefully prepared and equilibrated macromolecular ensembles. Interdiffusion of mostly chain ends across the interface and formation of entanglements with chains on the other side constitutes the most important mechanism which determines the strength and ductility of the joint. At high temperatures, the entanglement distribution at the interface can become almost indistinguishable from the bulk rather quickly and without motions of the entire chains. The temperature at which the welding is performed and the welding time are the most important process parameters that control the number of entanglements formed across the interface, the interface width, the mechanical properties and mode of failure of the joint. Pressure and quenching rate have marginal effects on the ultimate properties of a thermally welded joint. Our results also indicate that the interface thickness of the welded joint varies linearly with the welding time. The toughness of the welded joint, for chain lengths more than the entanglement length, varies linearly with it. The toughness also scales as the one-fourth power of the time for which the polymers are held at the welding temperature.

In materials science, the relationship between the material internal structure and its associated macroscale properties can be used to guide the design of materials. In this study, we constructed an interpretative machine learning (ML) model to capture the structure-property relationship and predict the solid solubility in binary alloy systems. To do this, we used a dataset containing about 1843 binary alloys and corresponding experiment values of solid solubility. We designed a common function to represent the relationship between individual descriptor and solid solubility, and a deep neural network to integrate the multiple functions. The resulting model can correctly predict the solid solubility value than other ML models. What is more, based on this model, it is feasible to analyze the effect of structures on target property.

Material flow and residual stress distribution during friction surfacing of aluminum alloy AA5083 on aluminum alloy AA5052 substrate have been evaluated employing a three-dimensional model and the finite element software, ABAQUS, as well as experimental investigation. Based on the results, the nature of residual stress in the coating was tensile while getting compressive by straying away from the boundary of the coating. An increment in heat input per unit length of coating has caused a decrease in the maximum tensile residual stress albeit increasing the extent of the region with tensile residual stress. On the advancing side, the velocity vector was larger than the retreating side due to the larger velocity difference between rotating rod and substrate. Moreover, the velocity difference between advancing and retreating sides was much lower in sample with minimum heat input compared to a sample with maximum heat input.

Ab initio data mining approach has been used in order to investigate B₆O system and discover new possible modifications, besides experimentally known R-3m (α-B₆O) structure and theoretically predicted Cmcm (β-B₆O) structure. DFT calculations were performed by two different functionals, LDA and PBE. In this work, we focus on the structure, mechanical, and electronic properties of the experimentally known α-B₆O structure and newly predicted modifications with the B₆O stoichiometry. Moreover, mechanical properties including elastic constants, bulk, shear and elastic moduli, Poisson's ratio, Pugh's criterion, and hardness are given for the investigated modifications of B₆O. In particular, we have investigated the influence of the high pressure on the electronic and mechanical properties. Results of our study provide more insight in the B₆O superhard material and open new possibilities for various device applications.

The study of crystal structure in the process of plastic deformation is essential to analyse the properties of materials and help to understand the deformation mechanism. With the rapid development of computer hardware and algorithms, great efforts have been paid for atomic simulation with computer science. However, most existing methods can only identify known structures in advance and consider unknown structure as unrecognized ones. In this work, we propose a method to identify crystal structure among atomistic simulations of crystalline materials. First, we develop a new characterization to describe each atom's local space information, i.e. local spatial characteristics and utilize mutual information to simplify the characteristics. Then, the multi-layer perceptron neural network is used for the classification on the simplified characteristics. With the proposed method, we can not only identify the crystal structures of the surface of atoms, but also obtain the value of probability of each crystal structure. Our work provides significant insights for finding new mechanisms in structure transformation in material science field.

The mechanical performance of carbides on the grain boundary (GB) of ferritic steels is always concerned. In this paper, four symmetric tilt GBs in body-centered cubic Fe were studied under tensile tests at 0 and 300 K through atomistic simulations. The GBs contained various sized Cr₂₃C₆ precipitates. Stress–strain curves were obtained through the molecular dynamics simulations and the tensile strength varied with GB type. Centro-symmetry parameter, common neighbor and dislocation analyses were performed for defect characterization. GBs with precipitates showed lower tensile strength than pure GBs. As the number and size of carbides increased, the tensile strength decreased. Cavities were easily formed near dislocation loops with a Burgers vector parallel with loading direction during tensile deformation of pure GBs, while ruptures occurred around the precipitate in GBs with carbides. The simulations indicate that Cr₂₃C₆ carbides in Fe are a brittle phase where the dislocations and cracks nucleate.

Carbon fibre reinforced plastics laminates were loaded through to fracture in a three-point bending configuration, to gain understanding of the cohesive interaction between plies and validate mechanical properties and predictive capability of the FE model. The effect of mesh refinement, scaling techniques, failure models and cohesive surfaces were investigated. Fibre orientations investigated were parallel, 45° and perpendicular to the loading. Experimental results showed a larger radius punch promoted failure on the intended bottom side, tensile stresses region, allowing for the Aramis strain camera to record the failure. When the fibre orientation was perpendicular to the punch load, all failure models show similar rate of force increment with respect to displacement. No difference in failure prediction is observed for the different 0° models, except for a 4.18% under prediction by LaRC02 compared to the experiment. With fibre orientations at 45° and 90°, the Maximum Strain and LaRCO2 failure models were more suitable in terms of accuracy and convergence. Incorporating cohesive surfaces between instances improve nonlinearity prediction of 45° and 90° layups. Small span-to-thickness ratio analysis predicts interlaminar shear failure, delamination, versus large span-to-thickness ratio determine normal stresses to dominate failure in laminate. The model was setup in multi-fibre orientation and cross-ply layups for extended application and was shown to successfully predict material response described in literature.

We have investigated the aluminum-silicate melt used as a simple case for many-component network-forming liquids. Based on the calculation of T–O subnets, T–O bonds (T is Si or Al) and commuting linkages, a systematic analysis is carried out to clarifying specific features of microstructure and dynamics. The simulation reveals a strong correlation between the mean square displacements and number of T–O bonds which remain unbroken during the simulation time. The model contains T–O subnets which behave like large molecules. We also find that most mobile and immobile atoms tend to gather in large clusters, the number of which slightly changes during the simulation time. In contrast, the atoms randomly taken from the system form numerous small clusters. The simulation result clearly demonstrates the micro-segregation and strong heterogeneity in dynamics and structure. In particular, the breaking and forming of T–O bonds (the replacing of T–O bonds by new ones) happen non-uniformly through the network structure. The atoms do not move in random directions, but they prefer to displace together by groups.

An extension of the dislocation dynamics method to polycrystalline materials is presented with emphasis on handling interactions between dislocations and grain boundaries. The key new features of the method include: (1) a grain boundary detection algorithm, (2) new dislocation emission criteria based on power dissipation and area growth, (3) mobility of dislocations at grain boundaries, and (4) extension of topological operations e.g. mesh adaption, collision, and dissociation to handle dislocations interacting with grain boundaries. Verification and validation examples are executed to compare our calculations with existing analytic methods, molecular dynamics simulations, and experimental observations.

A flow stress model which considers the processing conditions for a given alloy composition as well as the microchemistry of the alloy allows for integrated optimization of alloy composition, thermal treatments and forming operations to achieve the desired properties in the most efficient processing route. In the past, a statistical flow stress model for cell forming metals, 3IVM+ (3 Internal Variable Model), has been used for through process modeling of sheet production. However, this model was restricted to a given alloy in the state in which it was calibrated. In this work, the existing 3IVM+ model is augmented with an analytical solute strengthening model which uses input from ab initio simulations. Furthermore, a new particle strengthening model for non-shearable precipitates has been introduced which takes Orowan looping at low temperatures and dislocation climb at high temperatures into account. Hence, the present modeling approach considers the strengthening contributions from solutes, precipitates and forest dislocations. Three case studies on the alloys AA 1110, AA 3003 and AA 8014 are presented to assess the performance of the model in simulating the yield stress and flow stress of Al alloys over a wide range of temperatures and strain rates.

We have calculated the migration barriers for surface diffusion on tungsten. Our results form a self-sufficient parameterisation for kinetic Monte Carlo simulations of arbitrarily rough atomic tungsten surfaces, as well as nanostructures such as nanotips and nanoclusters. The parameterisation includes first- and second-nearest neighbour atom jump processes, as well as a third-nearest neighbour exchange process. The migration energy barriers of all processes are calculated with the nudged elastic band method. The same attempt frequency for all processes is found sufficient and the value is fitted to molecular dynamics simulations. The model is validated by correctly simulating with kinetic Monte Carlo the energetically favourable W nanocluster shapes, in good agreement with molecular dynamics simulations.

Pure magnesium (Mg) is an attractive metal for structural applications due to its low density, but also has low ductility and low fracture toughness. Dilute alloying of Mg with rare earth elements in small amounts improves the ductility, but the effects of alloying on fracture are not well-established. Here, the intrinsic fracture of a model Mg-3at%Y solid solution alloy is studied using a combination of anisotropic linear elastic fracture mechanics and atomistic simulations applied to a comprehensive set of crack configurations under mode I loading. The competition between brittle cleavage and ductile dislocation emission at the crack tip in Mg is improved slightly by alloying, because local fluctuations of the random solutes enable dislocation emission rather than cleavage fracture for a number of configurations where the differences in critical load for cleavage and emission are small. However, basal-plane cleavage remains strongly preferred, as in pure Mg. The alloys do show higher fracture toughness for all configurations due to local solute-induced deformation phenomena at the crack tip. Thus, alloying with Y is expected to improve the fracture toughness of Mg, but the persistence of basal cleavage prevents the alloy from becoming intrinsically ductile for all orientations.

Plastic deformation of most crystalline materials is due to the motion of lattice dislocations. Therefore, the simulation of the interaction and dynamics of these defects has become state-of-the-art method to study work hardening, size effects, creep and many other mechanical properties of metallic specimens. Lot of efforts have been made to make the simulations realistic by including specific dislocation mechanisms and the effect of free surfaces. However, less attention has been devoted to the numerical scheme that is used to solve the equations of motion. In this paper we propose a scheme that speeds up simulations by several orders of magnitude. The scheme is implicit because this type is the most efficient one for solving stiff equations that arise due to the long-range nature of dislocation interactions. The numerical results show that the method is not only faster than other approaches at the same numerical precision, but it can also be efficiently applied even without dislocation annihilation. The suggested method significantly increases the achievable volume and/or duration of discrete dislocation dynamics simulations and can be generalized for complex 2D and 3D simulations as well.

A numerical method is developed to efficiently calculate the stress (and displacement) field in finite 2D rectangular media. The solution is expanded on a function basis with elements that satisfy the Navier–Cauchy equation. The obtained solution approximates the boundary conditions with their finite Fourier series. The method is capable to handle Dirichlet, Neumann and mixed boundary value problems as well and it was found to converge exponentially fast to the analytical solution with respect to the size of the basis. Possible application in discrete dislocation dynamics simulations is discussed and compared to the widely used finite element methods: it was found that the new method is superior in terms of computational complexity.