arXiv subjects

Michael Zaiser

Publications and source records attributed to Michael Zaiser.

At least 37 records · Page 2Linked to original sources

arXiv2022

Enhanced fault-tolerance in biomimetic hierarchical materials -- a simulation study

Hierarchical microstructures are often invoked to explain the high resilience and fracture toughness of biological materials such as bone and nacre. Biomimetic material models inspired by those structural arrangements face the obvious challenge of capturing their inherent multi-scale complexity, both in experiments and in simulations. To study the influence of hierarchical microstructural patterns in fracture behavior, we propose a large scale three-dimensional hierarchical beam-element simulation framework, where we generalize the constitutive behavior of Timoshenko beam elasticity and Maximum Distortion Energy Theory failure criteria to the complex case of hierarchical networks of approximately 5 million elements. We perform a statistical study of stress-strain relationships and fracture surface mophologies, and conclude that hierarchical systems are capable of arresting crack propagation, an ability that reduces their sensitivity to pre-existing damage and enhances their fault tolerance compared to reference generic fibrous materials.

cond-mat.mtrl-sci↗

arXiv2022

Relating plasticity to dislocation properties by data analysis: scaling vs. machine learning approaches

Plasticity modelling has long been based on phenomenological models based on ad-hoc assuption of constitutive relations, which are then fitted to limited data. Other work is based on the consideration of physical mechanisms which seek to establish a physical foundation of the observed plastic deformation behavior through identification of isolated defect processes ('mechanisms') which are observed either experimentally or in simulations and then serve to formulate so-called physically based models. Neither of these approaches is adequate to capture the complexity of plastic deformation which belongs into the realm of emergent collective phenomena, and to understand the complex interplay of multiple deformation pathways which is at the core of modern high performance structural materials. Data based approaches offer alternative pathways towards plasticity modelling whose strengths and limitations we explore here for a simple example, namely the interplay between rate and dislocation density dependent strengthening mechanisms in fcc metals.

cond-mat.mtrl-sci↗

arXiv2022

A computationally efficient implementation of continuum dislocation dynamics: Formulation and application to ultrafine-grained Mg polycrystals

Continuum dislocation dynamics (CDD) represents the evolution of systems of curved and connected dislocation lines in terms of density-like field variables which include the volume density of loops (or 'curvature density') as an additional field. Since dislocation curvature represents a spatial derivative of the underlying discrete dislocation density tensor, the curvature field evolution equation of necessity contains numerically inconvenient higher-order derivatives of the density fields. We propose a simple approximation to express curvature in terms of density fields, and demonstrate its application to a benchmark problem in deformation of Mg polycrystals.

cond-mat.mtrl-sci↗

arXiv2022

Predicting the failure of two-dimensional silica glasses

Being able to predict the failure of materials based on structural information is a fundamental issue with enormous practical and industrial relevance for the monitoring of devices and components. Thanks to recent advances in deep learning, accurate failure predictions are becoming possible even for strongly disordered solids, but the sheer number of parameters used in the process renders a physical interpretation of the results impossible. Here we address this issue and use machine learning methods to predict the failure of simulated two dimensional silica glasses from their initial undeformed structure. We then exploit Gradient-weighted Class Activation Mapping (Grad-CAM) to build attention maps associated with the predictions, and we demonstrate that these maps are amenable to physical interpretation in terms of topological defects and local potential energies. We show that our predictions can be transferred to samples with different shape or size than those used in training, as well as to experimental images. Our strategy illustrates how artificial neural networks trained with numerical simulation results can provide interpretable predictions of the behavior of experimentally measured structures.

cond-mat.mtrl-sci↗

arXiv2021

Atomistic aspects of load transfer and fracture in CNT-reinforced aluminium

This paper describes atomistic simulations of deformation and fracture of Al reinforced with carbon nanotubes (CNTs). We use density functional theory (DFT) to understand the energetics of Al-graphene interfaces and gain reference data for the parameterization of Al-C empirical potentials. We then investigate the load transfer between CNTs and Al and its effect on composite strengthening. To this end, we perform uniaxial tensile simulations of an Al crystal reinforced with CNTs of various volume fractions. We also study the interaction of the embedded CNTs with a crack. We show that the interaction between CNTs and Al is weak such that, under tensile loading, CNTs can easily slide inside the Al matrix and get pulled out from the cracked surface. This effect is almost independent of CNT length and volume fraction. Little load transfer and consequently no crack bridging are observed during the simulation of pristine CNTs threading the crack surfaces. CNTs that are geometrically fixated inside Al, on the other hand, can increase the fracture stress and enhance plastic dissipation in the matrix. CNTs located in front of a growing crack blunt the crack and induce plastic deformation of the Al matrix. Depending on the CNT orientation, these processes can either increase or decrease the failure stress of the composite.

cond-mat.mtrl-sci↗

arXiv2021

Pinning of extended dislocations in atomically disordered crystals

In recent years there has been renewed interest in the behavior of dislocations in crystals that exhibit strong atomic scale disorder, as typical of compositionally complex single phase alloys. The behavior of dislocations in such crystals has been often studied in the framework of elastic manifold pinning in disordered systems. Here we discuss modifications of this framework that may need to be adapted when dealing with extended dislocations that split into widely separated partials. We demonstrate that the presence of a stacking fault gives rise to an additional stress scale that needs to be compared with the pinning stress of elastic manifold theory to decide whether the partials are pinned individually or the dislocation is pinned as a whole. For the case of weakly interacting partial dislocations, we demonstrate the existence of multiple metastable states at stresses below the depinning threshold and analyze the stress evolution of the stacking fault width during loading. In addition we investigate how geometrical constraints can modulate the dislocation-solute interaction and enhance the pinning stress. We compare our theoretical arguments with results of atomistic and discrete (partial) dislocation dynamics (D(P)DD) simulations.

cond-mat.mtrl-sci↗

arXiv2021

Pinning of dislocations in disordered alloys: Effects of dislocation orientation

The current interest in compositionally complex alloys including so called high entropy alloys has caused renewed interest in the general problem of solute hardening. It has been suggested that this problem can be addressed by treating the alloy as an effective medium containing a random distribution of dilatation and compression centers representing the volumetric misfit of atoms of different species. The mean square stresses arising from such a random distribution can be calculated analytically, their spatial correlations are strongly anisotropic and exhibit long-range tails with third-order power law decay. Here we discuss implications of the anisotropic and long-range nature of the correlation functions for the pinning of dislocations of arbitrary orientation. While edge dislocations are found to follow the standard pinning paradigm, for dislocations of near screw orientation we demonstrate the co-existence of two types of pinning energy minima.

cond-mat.mtrl-sci↗

arXiv2021

Dislocation-CNT Interactions in Aluminium at the Atomic Level

The interaction between edge dislocations and carbon nanotubes (CNTs) embedded into an Al matrix is investigated. Both pristine and Ni-coated CNTs are considered. It is demonstrated that the embedded CNTs lead to a flow stress contribution equivalent to that of an array of non-shearable inclusions that are by-passed via the Orowan mechanism. The strain hardening mechanism associated with multiple dislocation passes shows, however, characteristic differences from the Orowan picture that indicate that the embedded CNTs behave analogous to embedded voids.

cond-mat.mtrl-sci↗

arXiv2021

Thermodynamic considerations on a class of dislocation-based constitutive models

Dislocations are the main carriers of plastic deformation in crystalline materials. Physically based constitutive equations of crystal plasticity typically incorporate dislocation mechanisms, using a dislocation density based description of dislocation microstructure evolution and plastic flow. Typically, such constitutive models are not formulated in a thermodynamic framework. Nevertheless, fundamental considerations of thermodynamic consistency impose constraints on the admissible range of model parameters and/or on the range of application of such models. In particular, it is mandatory to ensure that the internal energy increase associated with dislocation accumulation is properly accounted for in the local energy balance. We demonstrate on some examples taken from the literature how failure to do so can lead to constitutive equations that violate the first and second laws of thermodynamics either generally or in some particular limit cases, and we discuss how to formulate constraints that recover thermodynamic consistency.

cond-mat.mtrl-sci↗

arXiv2020

Cell structure formation in a two-dimensional density-based dislocation dynamics model

Cellular patterns formed by self-organization of dislocations are a most conspicuous feature of dislocation microstructure evolution during plastic deformation. To elucidate the physical mechanisms underlying dislocation cell structure formation, we use a minimal model for the evolution of dislocation densities under load. By considering only two slip systems in a plane strain setting, we arrive at a model which is easily amenable to analytical stability analysis and numerical simulation. We use this model to establish analytical stability criteria for cell structures to emerge, to investigate the dynamics of the patterning process and establish the mechanism of pattern wavelength selection. This analysis demonstrates an intimate relationship between hardening and cell structure formation, which appears as an almost inevitable corollary to strain hardening itself. Specific mechanisms such as cross slip, by contrast, turn out to be incidental to the formation of cellular patterns.

cond-mat.mtrl-sci↗

arXiv2020

Prediction of creep failure time using machine learning

A subcritical load on a disordered material can induce creep damage. The creep rate in this case exhibits three temporal regimes viz. an initial decelerating regime followed by a steady-state regime and a stage of accelerating creep that ultimately leads to catastrophic breakdown. Due to the statistical regularities in the creep rate, the time evolution of creep rate has often been used to predict residual lifetime until catastrophic breakdown. However, in disordered samples, these efforts met with limited success. Nevertheless, it is clear that as the failure is approached, the damage become increasingly spatially correlated, and the spatio-temporal patterns of acoustic emission, which serve as a proxy for damage accumulation activity, are likely to mirror such correlations. However, due to the high dimensionality of the data and the complex nature of the correlations it is not straightforward to identify the said correlations and thereby the precursory signals of failure. Here we use supervised machine learning to estimate the remaining time to failure of samples of disordered materials. The machine learning algorithm uses as input the temporal signal provided by a mesoscale elastoplastic model for the evolution of creep damage in disordered solids. Machine learning algorithms are well-suited for assessing the proximity to failure from the time series of the acoustic emissions of sheared samples. We show that materials are relatively more predictable for higher disorder while are relatively less predictable for larger system sizes. We find that machine learning predictions, in the vast majority of cases, perform substantially better than other prediction approaches proposed in the literature.

cond-mat.soft↗

arXiv2020

Multilayer Structures of Graphene and Pt Nanoparticles -- a Multiscale Computational Study

We report results of a multiscale simulation study of multilayer structures consisting of graphene sheets with embedded Pt nanoparticles. Density functional theory is used to understand the energetics of Pt-graphene interfaces and provide reference data for the parameterization of a Pt-graphene interaction potential. Molecular dynamics simulations then provide the conformation and energetics of graphene sheets with embedded Pt nanoparticles of varying density, form and size. These results are interpreted using a continuum mechanical model of sheet deformation, and serve to parameterize a meso-scale Monte Carlo model to investigate the question under which conditions the free volume around the Pt nanoparticles forms a percolating cluster, such that the structures can be used in catalytic applications. We conclude with a discussion of potential applications of such multilayer structures.

physics.app-ph↗

arXiv2020

Strain rate dependency of dislocation plasticity

Dislocation slip is a general deformation mode and governs the strength of metals. Via discrete dislocation dynamics and molecular dynamics simulations, we investigate the strain rate and dislocation density dependence of the strength of bulk copper single crystals using 192 simulations spanning over 10 orders of magnitude in strain rate and 9 orders of magnitude in dislocation density. Based on these large set of simulations and theoretical analysis, a new analytical relationship between material strength, dislocation density, strain rate and dislocation mobility is proposed, which is in excellent agreement with the current simulations as well as with experimental data. The results show that the material strength is a non-monotonic function of dislocation density and displays two universal regimes (first decreasing, then increasing) as the dislocation density increases. The first regime is a result of strain rate hardening, while the second regime is dominated by the classical Taylor forest hardening. Accordingly, the strength displays universally, as a function of strain rate, a rate-independent regime at low strain rates (governed by forest hardening) followed by a rate hardening regime at high strain rates (governed by strain rate hardening). All the results can be captured by a single scaling function. Finally, the fluctuations of dislocation flow are analyzed in terms of the strain rate dependent distribution of dislocation segment velocities. It is found that the fluctuations are governed by another universal scaling function and diverge in the rate independent limit, indicating a critical behavior. The current analysis provides a comprehensive understanding on how collective dislocation motions are governed by the competition between the internal elastic interactions of dislocations, and the stress required to drive dislocation fluxes at a given externally imposed strain rate.

cond-mat.mtrl-sci↗

arXiv2020

Constitutive modeling of the tension-compression behavior of gradient structured materials

Gradient structured (GS) metals processed by severe plastic deformation techniques can be designed to achieve simultaneously high strength and high ductility. Significant kinematic hardening is key to their excellent strain hardening capacity which results in a favorable strength-ductility combination. Unfortunately, no constitutive model has been established to simulate and analyze the characteristic kinematic hardening behavior of GS metal to understand the relationship between their microstructure and macroscopic response. In this work, we developed a deformation-mechanismbased strain gradient plasticity model considering the plasticity heterogeneities from the grain to the sample scale. A back stress model, which accounts for the dependency of dislocation pile-ups on grain size, is established to describe the cyclic deformation properties of GS materials. The established model unified the geometrically necessary dislocations accommodating internal plasticity heterogeneities, the resulting back stress and reversible dislocations during reverse loading into a strain gradient plasticity framework, without introducing excessive numbers of independent material parameters. A finite element implementation of the model quantitatively predicts the uniaxial tensile and tensile-compressive responses of a GS copper bar as well as of a reference sample with homogeneous grain size. It is found that GS copper exhibits enhanced kinematic hardening which results mainly from fine grains in the GS layer and contributes to the considerable ductility of the GS material. The model allows to investigate the mechanical response and optimize the properties of materials with various types of spatially heterogeneous grain microstructures.

cond-mat.mtrl-sci↗

arXiv2019

Avalanche dynamics in hierarchical fiber bundles

Heterogeneous materials are often organized in a hierarchical manner, where a basic unit is repeated over multiple scales.The structure then acquires a self-similar pattern. Examples of such structure are found in various biological and synthetic materials. The hierarchical structure can have significant consequences for the failure strength and the mechanical response of such systems. Here we consider a fiber bundle model with hierarchical structure and study the effect of the self-similar arrangement on the avalanche dynamics exhibited by the model during the approach to failure. We show that the failure strength of the model generally decreases in a hierarchical structure, as opposed to the situation where no such hierarchy exists. However, we also report a special arrangement of the hierarchy for which the failure threshold could be substantially above that of a non hierarchical reference structure.

cond-mat.stat-mech↗

arXiv2019

Statistical dynamics of early creep stages in disordered materials

When materials are loaded below their short-term strength over extended periods, a slow time-dependent process known as creep deformation takes place. During creep deformation, the structural properties of a material evolve as a function of time. By means of a generic coarse-grained mesoscopic elastoplastic model which envisages deformation as a sequence of stochastically activated discrete events, we study the creep deformation of disordered materials. We find that the structural evolution of the material during creep modifies not only the average material properties but also changes the statistics of those properties. We analyze the emergence of correlations in the strain localization and deformation activity patterns, the variation of the event rate and the evolution of the inter-event time distribution. We find that the event rate follows the Omori law of aftershocks, which is the discrete counterpart of Andrade's transient creep law, and that the exponent of these laws only depends on the microstructural heterogeneity. Finally, we find during the initial stages of transient creep a transition from Poisson distributed inter-event times towards a non-trivial power law distribution.

cond-mat.soft↗

arXiv2019

Grain boundary effect on nanoindentation: A multiscale discrete dislocation dynamics model

Nanoindentation is a convenient method to investigate the mechanical properties of materials on small scales by utilizing low loads and small indentation depths. However, the effect of grain boundaries (GB) on the nanoindentation response remains unclear and needs to be studied by investigating in detail the interactions between dislocations and GBs during nanoindentation. In the present work, we employ a three-dimensional multiscale modeling framework, which couples three-dimensional discrete dislocation dynamics (DDD) with the Finite Element method (FEM) to investigate GB effects on the nanoindentation behavior of an aluminum bicrystal. The interaction between dislocations and GB is physically modeled in terms of a penetrable GB, where piled-up dislocations can penetrate through the GB and dislocation debris at GBs can emit full dislocations into grains. In the simulation, we confirmed two experimentally observed phenomena, namely, pop-in events and the dependence of indentation hardness on the distance from GB. Two pop-in events were observed, of which the initial pop-in event is correlated with the activation and multiplication of dislocations, while the GB pop-in event results from dislocation transmission through the GB. By changing the distance between the indenter and GB, the simulation shows that the indentation hardness increases with decreasing GB-indenter distance. A quantitative model has been formulated which relates the dependency of indentation hardness on indentation depth and on GB-indenter distance to the back stress created by piled-up geometrically necessary dislocations in the plastic zone and to the additional constraint imposed by the GB on the plastic zone size.

cond-mat.mtrl-sci↗

arXiv2018

Microplasticity and yielding in crystals with heterogeneous dislocation distribution

In this study, we use discrete dislocation dynamics (DDD) simulation to investigate the effect of heterogeneous dislocation density on the transition between quasi-elastic deformation and plastic flow in face-centered cubic single crystals. By analyzing the stress-strain curves of samples with an initial, axial dislocation density gradient, we arrive at the following conclusions: (i) in the regime of quasi-elastic deformation before the onset of plastic flow, the effective elastic modulus of the simulated samples falls significantly below the value for a dislocation-free crystal. This modulus reduction increases with decreasing dislocation density gradient: crystals with homogeneous dislocation distribution are thus weakest in the quasi-elastic regime; (ii) the transition towards plastic flow occurs first in regions of reduced dislocation density. Therefore, the overall yield stress decreases with increasing dislocation density gradient; (iii) crystals with dislocation density gradient exhibit a more pronounced hardening stage during which stress is re-distributed onto stronger regions with higher dislocation density until the sample flows at a constant flow stress that is approximately independent on dislocation density gradient. We interpret these findings in terms of a continuum dislocation dynamics inspired model of dislocation density evolution that accounts for inversive dislocation motions. The transition between quasi-elastic and plastic deformation is interpreted as a transition from inversive to non-inversive dislocation motion, and the initial differences in elastic modulus are related to a density dependent polarizability of the dislocation system. The subsequent plastic flow behavior is analyzed in terms of a modified version of Mughrabi's composite model.

cond-mat.mtrl-sci↗