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Mikko J. Alava

Publications and source records attributed to Mikko J. Alava.

At least 37 records · Page 2Linked to original sources

Probing the transition from dislocation jamming to pinning by machine learning

Collective motion of dislocations is governed by the obstacles they encounter. In pure crystals, dislocations form complex structures as they become jammed by their anisotropic shear stress fields. On the other hand, introducing disorder to the crystal causes dislocations to pin to these impeding elements and, thus, leads to a competition between dislocation-dislocation and dislocation-disorder interactions. Previous studies have shown that, depending on the dominating interaction, the mechanical response and the way the crystal yields change. Here we employ three-dimensional discrete dislocation dynamics simulations with varying density of fully coherent precipitates to study this phase transition $-$ from jamming to pinning $-$ using unsupervised machine learning. By constructing descriptors characterizing the evolving dislocation configurations during constant loading, a confusion algorithm is shown to be able to distinguish the systems into two separate phases. These phases agree well with the observed changes in the relaxation rate during the loading. Our results also give insights on the structure of the dislocation networks in the two phases.

cond-mat.mtrl-sci↗

Plastic yielding and deformation bursts in the presence of disorder from coherent precipitates

Alloying metals with other elements is often done to improve the material strength or hardness. A key microscopic mechanism is precipitation hardening, where precipitates impede dislocation motion, but the role of such obstacles in determining the nature of collective dislocation dynamics remains to be understood. Here, three-dimensional discrete dislocation dynamics simulations of FCC single crystals are performed with fully coherent spherical precipitates from zero precipitate density upto $ρ_p = 10^{21}\,\text{m}^{-3}$ and at various dislocation-precipitate interaction strengths. When the dislocation-precipitate interactions do not play a major role the yielding is qualitatively as for pure crystals, i.e., dominated by "dislocation jamming", resulting in glassy dislocation dynamics exhibiting critical features at any stress value. We demonstrate that increasing the precipitate density and/or the dislocation-precipitate interaction strength creates a true yield or dislocation assembly depinning transition, with a critical yield stress. This is clearly visible in the statistics of dislocation avalanches observed when quasistatically ramping up the external stress, and is also manifested in the response of the system to constant applied stresses. The scaling of the yielding with precipitates is discussed in terms of the Bacon-Kocks-Scattergood relation.

cond-mat.mtrl-sci↗

Machine learning plastic deformation of crystals

Plastic deformation of micron-scale crystalline solids exhibits stress-strain curves with significant sample-to-sample variations. It is a pertinent question if this variability is purely random or to some extent predictable. Here we show, by employing machine learning techniques such as regression neural networks and support vector machines that deformation predictability evolves with strain and crystal size. Using data from discrete dislocations dynamics simulations, the machine learning models are trained to infer the mapping from features of the pre-existing dislocation configuration to the stress-strain curves. The predictability vs strain relation is non-monotonic and exhibits a system size effect: larger systems are more predictable. Stochastic deformation avalanches give rise to fundamental limits of deformation predictability for intermediate strains. However, the large-strain deformation dynamics of the samples can be predicted surprisingly well.

cond-mat.dis-nn↗

Nanoscale Liquid Crystal Lubrication Controlled by Surface Structure and Film Composition

Liquid crystals have emerged as potential candidates for next-generation lubricants due to their tendency to exhibit long-range ordering. Here, we construct a full atomistic model of 4-cyano-4-hexylbiphenyl (6CB) nematic liquid crystal lubricants mixed with hexane and confined by mica surfaces. We explore the effect of the surface structure of mica, as well as lubricant composition and thickness, on the nanoscale friction in the system. Our results demonstrate the key role of the structure of the mica surfaces, specifically the positions of potassium ($\mathrm{K}^+$) ions, in determining the nature of sliding friction with monolayer lubricants, including the presence or absence of stick-slip dynamics. With the commensurate setup of confining surfaces, when the grooves created between the periodic $\mathrm{K}^+$ ions are parallel to the sliding direction we observe a lower friction force as compared to the perpendicular situation. Random positions of ions exhibit even smaller friction forces with respect to the previous two cases. For thicker lubrication layers the surface structure becomes less important and we observe a good agreement with the experimental data on bulk viscosity of 6CB and the additive hexane. In case of thicker lubrication layers, friction may still be controlled by tuning the relative concentrations of 6CB and hexane in the mixture.

cond-mat.soft↗

Mimicking complex dislocation dynamics by interaction networks

Two-dimensional discrete dislocation models exhibit complex dynamics in relaxation and under external loading. This is manifested both in the time-dependent velocities of individual dislocations and in the ensemble response, the strain rate. Here we study how well this complexity may be reproduced using so-called Interaction Networks, an Artificial Intelligence method for learning the dynamics of complex interacting systems. We test how to learn such networks using creep data, and show results on reproducing individual and collective dislocation velocities. The quality of reproducing the interaction kernel is discussed.

physics.comp-ph↗

Excitation spectra in crystal plasticity

Plastically deforming crystals exhibit scale-free fluctuations that are similar to those observed in driven disordered elastic systems close to depinning, but the nature of the yielding critical point is still debated. Here, we study the marginal stability of ensembles of dislocations and compute their excitation spectrum in two and three dimensions. Our results show the presence of a singularity in the distribution of {\it excitation stresses}, i.e., the stress needed to make a localized region unstable, that is remarkably similar to the one measured in amorphous plasticity and spin glasses. These results allow us to understand recent observations of extended criticality in bursty crystal plasticity and explain how they originate from the presence of a pseudogap in the excitation spectrum.

cond-mat.stat-mech↗

Mechanics of disordered auxetic metamaterials

Auxetic materials are of great engineering interest not only because of their fascinating negative Poisson's ratio, but also due to their increased toughness and indentation resistance. These materials are typically synthesized polyester foams with a very heterogeneous structure, but the role of disorder in auxetic behavior is not fully understood. Here, we provide a systematic theoretical and experimental investigation in to the effect of disorder on the mechanical properties of a paradigmatic auxetic lattice with a re-entrant hexagonal geometry. We show that disorder has a marginal effect on the Poisson's ratio unless the lattice topology is altered, and in all cases examined the disorder preserves the auxetic characteristics. Depending on the direction of loading applied to these disordered auxetic lattices, either brittle or ductile failure is observed. It is found that brittle failure is associated with a disorder-dependent tensile strength, whereas in ductile failure disorder does not affect strength. Our work thus provides general guidelines to optimize elasticity and strength of disordered auxetic metamaterials.

cond-mat.mtrl-sci↗

Friction controls submerged granular flows

We investigate the coupling between interstitial medium and granular particles by studying the hopper flow of dry and submerged system experimentally and numerically. In accordance with earlier studies, we find, that the dry hopper empties at a constant rate. However, in the submerged system we observe the surging of the flow rate. We model both systems using the discrete element method, which we couple with computational fluid dynamics in the case of a submerged hopper. We are able to match the simulations and the experiments with good accuracy. To do that, we fit the particle-particle contact friction for each system separately, finding that submerging the hopper changes the particle-particle contact friction from $μ_{vacuum}=0.15$ to $μ_{sub}=0.13$, while all the other simulation parameters remain the same. Furthermore, our experiments find a particle size dependence to the flow rate, which is comprehended based on arguments on the terminal velocity and drag. These results jointly allow us to conclude that at the large particle limit, the interstitial medium does not matter, in contrast to small particles. The particle size limit, where this occurs depends on the viscosity of the interstitial fluid.

cond-mat.soft↗

Start-up inertia as an origin for heterogeneous flow

For quite some time non-monotonic flow curve was thought to be a requirement for shear banded flows in complex fluids. Thus, in simple yield stress fluids shear banding was considered to be absent. Recent spatially resolved rheological experiments have found simple yield stress fluids to exhibit shear banded flow profiles. One proposed mechanism for the initiation of such transient shear banding process has been a small stress heterogeneity rising from the experimental device geometry. Here, using Computational Fluid Dynamics methods, we show that transient shear banding can be initialized even under homogeneous stress conditions by the fluid start-up inertia, and that such mechanism indeed is present in realistic experimental conditions.

cond-mat.soft↗

Inter-event correlations from avalanches hiding below the detection threshold

Numerous systems ranging from deformation of materials to earthquakes exhibit bursty dynamics, which consist of a sequence of events with a broad event size distribution. Very often these events are observed to be temporally correlated or clustered, evidenced by power-law distributed waiting times separating two consecutive activity bursts. We show how such inter-event correlations arise simply because of a finite detection threshold, created by the limited sensitivity of the measurement apparatus, or used to subtract background activity or noise from the activity signal. Data from crack propagation experiments and numerical simulations of a non-equilibrium crack line model demonstrate how thresholding leads to correlated bursts of activity by separating the avalanche events into sub-avalanches. The resulting temporal sub-avalanche correlations are well-described by our general scaling description of thresholding-induced correlations in crackling noise.

cond-mat.stat-mech↗

Bursts of activity in collective cell migration

Dense monolayers of living cells display intriguing relaxation dynamics, reminiscent of soft and glassy materials close to the jamming transition, and migrate collectively when space is available, as in wound healing or in cancer invasion. Here we show that collective cell migration occurs in bursts that are similar to those recorded in the propagation of cracks, fluid fronts in porous media and ferromagnetic domain walls. In analogy with these systems, the distribution of activity bursts displays scaling laws that are universal in different cell types and for cells moving on different substrates. The main features of the invasion dynamics are quantitatively captured by a model of interacting active particles moving in a disordered landscape. Our results illustrate that collective motion of living cells is analogous to the corresponding dynamics in driven, but inanimate, systems.

physics.bio-ph↗

Deformation and fracture of echinoderm collagen networks

Collagen networks provide the main structural component of most tissues and represent an important ingredient for bio-mimetic materials for bio-medical applications. Here we study the mechanical properties of stiff collagen networks derived from three different echinoderms and show that they exhibit non-linear stiffening followed by brittle fracture. The disordered nature of the network leads to strong sample-to-sample fluctuations in elasticity and fracture strength. We perform numerical simulations of a three dimensional model for the deformation of a cross-linked elastic fibril network which is able to reproduce the macroscopic features of the experimental results and provide insights into the internal mechanics of stiff collagen networks. Our numerical model provides an avenue for the design of collagen membranes with tunable mechanical properties.

physics.bio-ph↗

Glassy features of crystal plasticity

Crystal plasticity occurs by deformation bursts due to the avalanche-like motion of dislocations. Here we perform extensive numerical simulations of a three-dimensional dislocation dynamics model under quasistatic stress-controlled loading. Our results show that avalanches are power-law distributed, and display peculiar stress and sample size dependence: The average avalanche size grows exponentially with the applied stress, and the amount of slip increases with the system size. These results suggest that intermittent deformation processes in crystalline materials exhibit an extended critical-like phase in analogy to glassy systems, instead of originating from a non-equilibrium phase transition critical point.

cond-mat.stat-mech↗

Multi-scale modeling of dislocation-precipitate interactions in Fe: from molecular dynamics to discrete dislocations

The stress-driven motion of dislocations in crystalline solids, and thus the ensuing plastic deformation process, is greatly influenced by the presence or absence of various point-like defects such as precipitates or solute atoms. These defects act as obstacles for dislocation motion and hence affect the mechanical properties of the material. Here we combine molecular dynamics studies with three-dimensional discrete dislocation dynamics simulations in order to model the interaction between different kinds of precipitates and a $\frac{1}{2}\langle 1 1 1\rangle$ $\{1 1 0\}$ edge dislocation in BCC iron. We have implemented immobile spherical precipitates into the ParaDis discrete dislocation dynamics code, with the dislocations interacting with the precipitates via a Gaussian potential, generating a normal force acting on the dislocation segments. The parameters used in the discrete dislocation dynamics simulations for the precipitate potential, the dislocation mobility, shear modulus and dislocation core energy are obtained from molecular dynamics simulations. We compare the critical stresses needed to unpin the dislocation from the precipitate in molecular dynamics and discrete dislocation dynamics simulations in order to fit the two methods together, and discuss the variety of the relevant pinning/depinning mechanisms.

cond-mat.mtrl-sci↗

Avalanches in wood compression

Wood is a multi-scale material exhibiting a complex viscoplastic response. We study avalanches in small wood samples in compression. "Woodquakes" measured by acoustic emission are surprisingly similar to earthquakes and crackling noise in rocks and laboratory tests on brittle materials. Both the distributions of event energies and of waiting (silent) times follow power-laws. The stress- strain response exhibits clear signatures of localization of deformation to "weak spots" or softwood layers, as identified using Digital Image Correlation. Even though material structure-dependent localization takes place, the avalanche behavior remains scale-free.

cond-mat.stat-mech↗

Quenched pinning and collective dislocation dynamics

Several experiments show that crystalline solids deform in a bursty and intermittent fashion. Power-law distributed strain bursts in compression experiments of micron-sized samples, and acoustic emission energies from larger-scale specimens, are the key signatures of the underlying critical-like collective dislocation dynamics - a phenomenon that has also been seen in discrete dislocation dynamics (DDD) simulations. Here we show, by performing large-scale two-dimensional DDD simulations, that the character of the dislocation avalanche dynamics changes upon addition of sufficiently strong randomly distributed quenched pinning centres, present e.g. in many alloys as immobile solute atoms. For intermediate pinning strength, our results adhere to the scaling picture of depinning transitions, in contrast to pure systems where dislocation jamming dominates the avalanche dynamics. Still stronger disorder quenches the critical behaviour entirely.

cond-mat.mtrl-sci↗

Osmotic stress affects functional properties of human melanoma cell lines

Understanding the role of microenvironment in cancer growth and metastasis is a key issue for cancer research. Here, we study the effect of osmotic pressure on the functional properties of primary and metastatic melanoma cell lines. In particular, we experimentally quantify individual cell motility and transmigration capability. We then perform a circular scratch assay to study how a cancer cell front invades an empty space. Our results show that primary melanoma cells are sensitive to a low osmotic pressure, while metastatic cells are less. To better understand the experimental results, we introduce and study a continuous model for the dynamics of a cell layer and a stochastic discrete model for cell proliferation and diffusion. The two models capture essential features of the experimental results and allow to make predictions for a wide range of experimentally measurable parameters.

physics.bio-ph↗

Stick-Slip Control in Nanoscale Boundary Lubrication by Surface Wettability

We study the effect of atomic scale surface-lubricant interactions on nanoscale boundary-lubricated friction, by considering two example surfaces - hydrophilic mica and hydrophobic graphene - confining thin layers of water in molecular dynamics simulations. We observe stick-slip dynamics for thin water films confined by mica sheets, involving periodic breaking-reforming transitions of atomic scale capillary water bridges formed around the potassium ions of mica. However, only smooth sliding without stick-slip events is observed for water confined by graphene, as well as for thicker water layers confined by mica. Thus, our results illustrate how atomic scale details affect the wettability of the confining surfaces, and consequently control the presence or absence of stick-slip dynamics in nanoscale friction.

cond-mat.mtrl-sci↗