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Funding Information: M.A., L.J., J.K., T.M. and A.P. acknowledge support from FinnCERES flagship (151830423) and Business Finland (211835). L.V. acknowledges funding from the Vilho, Yrjö, and Kalle Väisälä Foundation via personal grants. Publisher Copyright: © 2023, The Author(s). Abstract: Foam-formed cellulose biocomposites are a promising technology for developing lightweight and sustainable packaging materials. In this work, we produce and characterize biocomposite foams based on methylcellulose (MC), cellulose fibers (CF), and lignin (LN). The results indicate that adding organosolv lignin to a foam prepared using MC and CF moderately increases Young’s modulus, protects the foam from the growth of Escherichia coli bacteria, and improves the hydrophobicity of the foam surface. This article concludes that organosolv lignin enhances many properties of cellulose biocomposite foams that are required in applications such as insulation, packaging, and cushioning. The optimization of the foam composition offers research directions toward the upscaling of the material solution to the industrial scale. Graphical abstract: [Figure not available: see fulltext.].

Funding Information: M.J.A. and T.M. acknowledge support from the European Union Horizon 2020 research and innovation programme under Grant Agreement No. 857470 and from European Regional Development Fund via Foundation for Polish Science International Research Agenda PLUS programme Grant No. MAB PLUS/2018/8. M.J.A. acknowledges support from the Academy of Finland (Center of Excellence program, 278367 and 317464). J.K. acknowledges funding from Academy of Finland (308235) and Business Finland (211715). I.V.L. acknowledges funding from Academy of Finland (341440 and 346603). The authors acknowledge the computational resources provided by the Aalto University School of Science “Science-IT” project and the provision of facilities and technical support by Aalto University at OtaNano–Nanomicroscopy Center (Aalto-NMC). | openaire: EC/H2020/857470/EU//NOMATEN Fatigue failure of crystalline materials is a difficult problem in science and engineering, and recent results have shown that fatigue crack growth can occur in intermittent jumps that have fat-tailed distributions. As fatigue crack propagation is known to leave markings - called striations - on the fracture surface, the distances between these should also have fat-tailed distributions if the crack propagation is intermittent. Here, we combine macroscale crack tip tracking in fatigue crack growth measurements of aluminum 5005 samples with postmortem scanning electron microscopy imaging of the striation lines. We introduce two different methods for extracting the striation line spacing from the images. What we find is a similar distribution of striation spacings as jump sizes using one of our methods, but the average striation spacing does not correlate with the crack growth rate. We conclude that we observe avalanchelike crack propagation, reflected in both the macroscale crack tip tracking as well as the analysis of the fracture surfaces. Our results show that the fracture surfaces can be used to study the intermittency of fatigue crack propagation and in development of crack-resistant materials. The advantages and disadvantages of the two methods introduced are discussed.

Funding Information: Open Access funding provided by Technical Research Centre of Finland (VTT). This work is part of the Academy of Finland’s Flagship Programme under Project numbers 318890 and 318891 (Competence Center for Materials Bioeconomy, FinnCERES), and grant number 278367. Publisher Copyright: © 2023, The Author(s). Significant importance in the stiffness of materials, such as filaments and films, made of elongated components, has been attributed to orientation. Thus, the control of orientation during the manufacturing of materials has been the target of process optimization for long time. Measuring orientation during the process allows to better grasp the means to control it. In fact, such online tools would enable on-fly process control and optimization improving the flexibility with regards to the raw materials used, and the application requirements. In this article, we will discuss a method based on polarization-sensitive optical coherence tomography utilized as a light-weight online measurement tool of particle (here cellulose nanocrystals) orientation for the purposes of manufacturing next generation products by providing the appropriate interpretation of the retardation images with the help of modelling.

Funding Information: M.J.A. acknowledges support from the Academy of Finland (Center of Excellence program, 278367 and 317464): The authors gratefully acknowledge the support from the European Union Horizon 2020 research and innovation programme under Grant Agreement No. 857470 and from European Regional Development Fund via Foundation for Polish Science International Research Agenda PLUS programme Grant No. MAB PLUS/2018/8. The authors acknowledge the computational resources provided by the Aalto University School of Science “Science-IT” project. | openaire: EC/H2020/857470/EU//NOMATEN There are a multitude of applications in which structural materials would be desired to be nondestructively evaluated, while in a component, for plasticity and failure characteristics. In this way, safety and resilience features can be significantly improved. Nevertheless, while failure can be visible through cracks, plasticity is commonly invisible and highly microstructure-dependent. Here, we show that an equation-free method based on principal component analysis is capable of detecting yielding and tertiary creep onset, directly from strain fields that are obtained by digital image correlation, applicable on components, continuously and nondestructively. We demonstrate the applicability of the method to yielding of Ni-based Haynes 230 metal alloy polycrystalline samples, which are also characterized through electron microscopy and benchmarked using continuum polycrystalline plasticity modeling. Also, we successfully apply this method to yielding during uniaxial tension of Hastelloy X polycrystalline samples, and also to the onset of tertiary creep in quasibrittle fiber composites under uniaxial tension. We conclude that there are key features in the spatiotemporal fluctuations of local strain fields that can be used to infer mechanical properties.

Funding Information: M.Z. and S.A.H. acknowledge funding of this work by DFG through Grant No. 1Za 171-7/1, and P.M. acknowledges DFG funding under MO 3049/3-1. S.A.H and M.P. also acknowledge participation as associate researchers in the training programme of DFG GRK 2423 FRASCAL. J.K. acknowledges funding from Academy of Finland (308235). M.J.A. acknowledges support from the European Union Horizon 2020 research and innovation programme under Grant Agreement No. 857470, from European Regional Development Fund via Foundation for Polish Science International Research Agenda PLUS programme Grant No. MAB PLUS/2018/8, and from the Academy of Finland (No. 278367 and No. 317464). T.M. acknowledges funding from The Finnish Foundation for Technology Promotion. | openaire: EC/H2020/857470/EU//NOMATEN By introducing hierarchical patterns of load-parallel cuts into axially loaded brittle sheets, the resistance to propagation of mode-I cracks is very significantly enhanced. We demonstrate this effect by simulation of two-dimensional beam network models and experimentally by testing paper and polystyrene (PS) sheets that are sliced with a laser cutter to induce load-perpendicular hierarchical cut patterns. Samples endowed with nonhierarchical reference patterns of the same cut density and nonsliced sheets are considered for comparison. We demonstrate that hierarchical slicing can increase failure load, apparent fracture toughness, and work of fracture of notched paper and PS sheets by factors between 2 and 10.

Funding Information: This research was funded by the European Union Horizon 2020 research and innovation program under grant agreement no. 857470 and from the European Regional Development Fund via Foundation for Polish Science International Research Agenda PLUS program grant no. MAB PLUS/2018/8 . We wish to acknowledge fruitful discussions with Daniel Cieslinski. | openaire: EC/H2020/857470/EU//NOMATEN Nanoscale hardness in polycrystalline metals is strongly dependent on microstructural features that are believed to be influenced from polycrystallinity — namely, grain orientations and neighboring grain properties. We train a graph neural networks (GNN) model, with grain centers as graph nodes, to assess the predictability of micromechanical responses of nano-indented 310S steel surfaces, based on surface polycrystallinity, captured by electron backscatter diffraction maps. The grain size distribution ranges between 1–100 μm, with mean size at 18μm. The GNN model is trained on nanomechanical load-displacement curves to make predictions of nano-hardness, with sole input being the grain locations and orientations. We explore model performance and its dependence on various structural/topological grain-level descriptors (e.g. grain size and number of neighbors). Analogous GNN-based frameworks may be utilized for quick, inexpensive hardness estimates, for guidance to detailed nanoindentation experiments, akin to cartography tool developments in the world exploration era.

openaire: EC/H2020/857470/EU//NOMATEN Funding Information: Acknowledgments. We acknowledge the European Synchrotron Radiation Facility for the provision of synchrotron radiation facilities and we would like to thank Marco di Michiel for assistance in using beam line ID15A. We thank Simo Huotari and Heikki Suhonen for their help in the application and data analysis process. M.J.A. acknowledges support from the Academy of Finland (Center of Excellence program, Grants No. 278367 and No. 317464). M.J.A. and T.M. acknowledge funding from the European Union Horizon 2020 research and innovation programme under Grant Agreement No. 857470 and from European Regional Development Fund via the Foundation for Polish Science International Research Agenda PLUS programme Grant No. MAB PLUS/2018/8. T.M. also acknowledges funding from The Finnish Foundation for Technology Promotion. J.K. acknowledges the funding from the Academy of Finland (Grant No. 308235) and Business Finland (Grant No. 211715). The Aalto Science IT project is acknowledged for providing computational resources. Publisher Copyright: © 2022 American Physical Society. Wood deformation, in particular when subject to compression, exhibits scale-free avalanche-like behavior as well as structure-dependent localization of deformation. We have taken three-dimensional (3D) x-ray tomographs during compression with constant stress rate loading. Using digital volume correlation, we obtain the local total strain during the experiment and compare it to the global strain and acoustic emission. The wood cells collapse layer by layer throughout the sample starting from the softest parts, i.e., the spring wood. As the damage progresses, more and more of the softwood layers throughout the sample collapse, which indicates damage spreading instead of localization. In 3D, one can see a fat-tailed local strain rate distribution, indicating that inside the softwood layers, the damage occurs in localized spots. The observed log-normal strain distribution is in agreement with this view of the development of independent local collapses or irreversible deformation events. A key feature in the mechanical behavior of wood is then in the complex interaction of localized deformation between or among the annual rings.

Significant importance in the stiffness of materials, such as filaments and films, made of elongated components, has been attributed to orientation. Thus, the control of orientation during the manufacturing of materials has been the target of process optimization for long time. Measuring orientation during the process allows to better grasp the means to control it. In fact, such on-line tools would enable on-fly process control and optimization improving the flexibility with regards to the raw materials used, and the application requirements. In this article, we will discuss a method based on Polarization Sensitive Optical Coherence Tomography utilized as a light-weight on-line measurement tool of particle (here cellulose nanocrystals) orientation for the purposes of manufacturing next generation products by providing the appropriate interpretation of the retardation images with the help of modelling.

Unicellular Chlamydomonas reinhardtii micro-algae cells were inserted into a quasi-2D Hele-Shaw chamber filled with saponin foam. The movement of the algae along the bubble borders was then manipulated and tracked. These self-propelled particles generate flow and stresses in their surrounding matter. In addition, the algae possess the capability of exerting forces that alter bubble boundaries while maintaining an imminent phototactic movement. We find that by controlling the gas fraction of the foam we can change the interaction of the algae and bubbles. Specifically, our data expose three distinct swimming regimes for the algae with respect to the level of confinement due to the Plateau border cross-section: unlimited bulk, transition, and overdamped regimes. At the transition regime we find the speed of the algae to be modeled by a simple force balance equation emerging from the shear inside the Plateau border. Thus, we have shown that it is possible to create an algae-friendly foam while controlling the algae motion. This opens doors to multiple applications where the flow of nutrients, oxygen and recirculation of living organisms is essential.

Plastic yielding in solids strongly depends on various conditions, such as temperature and loading rate and indeed, sample-dependent knowledge of yield points in structural materials promotes reliability in mechanical behavior. Commonly, yielding is measured through controlled mechanical testing at small or large scales, in ways that either distinguish elastic (stress) from total deformation measurements, or by identifying plastic slip contributions. In this paper we argue that instead of separate elastic/plastic measurements, yielding can be unraveled through statistical analysis of total strain fluctuations during the evolution sequence of profiles measured in-situ, through digital image correlation. We demonstrate two distinct ways of precisely quantifying yield locations in widely applicable crystal plasticity models, that apply in polycrystalline solids, either by using principal component analysis or discrete wavelet transforms. We test and compare these approaches in synthetic data of polycrystal simulations and a variety of yielding responses, through changes of the applied loading rates and the strain-rate sensitivity exponents., Comment: 9 pages, 6 figures

Machine learning techniques have been recently applied in predicting deformation in amorphous materials. In this study, we extract structural features around liquid film vertices from images of flowing 2D foam and apply a multilayer perceptron to predict local yielding. We evaluate their importance in the description of the T1 events and show that a high level of predictability may be achieved using well-chosen combinations of features as the prediction data. The most relevant features are extracted by performing the predictions separately for isolated sets of features, and these findings are verified using principal component analysis. Using this approach, we determine which properties of the images are most important with regard to the physics of the processes. Our findings indicate that film lengths and angles between the liquid films joining at the vertex are the most important features that predict the local yield events. These two features describe 83% of the yield events. As an application, we extract the statistics of event waiting times from the experiment.

Complex fluids made of liquid crystals (LCs) and small molecules, surfactants, nanoparticles or 1D/2D nanomaterials show novel and interesting features, making them suitable materials for various applications starting from optoelectronics to biosensing. While these additives (impurities) introduce new features in the complex fluids, they may also alter the phase transition behaviour of LCs depending on the physiochemical properties of the added impurity. This article reports on the phase transition of 4-cyano-4'-alkylbiphenyl (nCB) LCs in the presence of an associative impurity,i.e., water and a non-associative impurity,i.e., hexane employing computational methods and experiments. In particular, all-atom (AA) simulations and coarse-grained (CG) models were designed for two complex systems,i.e., 6CB + water and 6CB + hexane and corresponding spectrophotometry experiments were performed using a homologous LC,i.e., 5CB. Results from the simulations and experiments elucidate that the phase transition of LCs depends on the mixing/demixing phenomenon of the impurity in the LC. While associative liquids like water which do not mix with LCs do not influence the nematic-to-isotropic phase transition of LCs, hexane, being a non-associative liquid, mixes well with LCs and induces a sharp impurity-induced nematic-to-isotropic phase transition. Upon application of both AA and CG simulations, we could reach the conclusion that the mixing/demixing phenomenon in an LC + impurity system influences the entropy of the system and hence the observed phase transitions are entropy-driven. acceptedVersion

We study a liquid-gas front propagation in a modulated Hele-Shaw cell by means of multiphase computational fluid mechanics based on the three-dimensional Navier-Stokes equations. In the simulations an obstacle that partially fills the gap is placed at the center of the cell, and the liquid-gas interface is driven at a constant velocity. We study the morphological differences between imbibition and drainage for a wide range of capillary numbers, and explore how the wetting properties of the constriction affect the amount of liquid that remains trapped in the draining process. We observe increasing remaining volumes with increasing capillary number and decreasing contact angle. The present CFD implementation for a single mesa defect provides insight into a wide number of practical applications.

Portevin–Le Chatelier deformation bands obey predictions of a simple mean-field model of critical avalanche dynamics., The plastic deformation of metal alloys localizes in the Portevin–Le Chatelier effect in bands of different types, including propagating, or type “A” bands, usually characterized by their width and a typical propagation velocity. This plastic instability arises from collective dynamics of dislocations interacting with mobile solute atoms, but the resulting sensitivity to the strain rate lacks fundamental understanding. Here, we show, by using high-resolution imaging in tensile deformation experiments of an aluminum alloy, that the band velocities exhibit large fluctuations. Each band produces a velocity signal reminiscent of crackling noise bursts observed in numerous driven avalanching systems from propagating cracks in fracture to the Barkhausen effect in ferromagnets. The statistical features of these velocity bursts including their average shapes and size distributions obey predictions of a simple mean-field model of critical avalanche dynamics. Our results thus reveal a previously unknown paradigm of criticality in the localization of deformation.

openaire: EC/H2020/857470/EU//NOMATEN The last stage of material failure often shows a regime with power-law acceleration as the material lifetime is approached. We study this experimentally in tensile creep with paper samples using digital image correlation. The last, tertiary creep stage exhibits scale-free features in the sample response (strain rate) and its fluctuations. It is accompanied by an increasing localization of strain at the location of final failure. The main features are reproduced by a material model built on a viscoelastic fiber bundle model.

We present an experimental study of a two-dimensional liquid foam, composed of a confined monolayer of bubbles, forced to flow within a model porous medium that mimics an inhomogeneous open fracture. It consists of a Hele-Shaw cell with a single localized constriction-like defect that reduces locally its gap and thus its permeability. Taking advantage of the possibility to directly visualize and follow the bubbles, we compute the bubble velocity field by image correlation analysis, as well as the bubble deformation field, through eccentricity measurements obtained by fitting each bubble with an ellipse. The defect acting as a permeable obstacle can strongly disturb the foam flow; we investigate here the influence of its geometry (height, size, and shape) on the average steady-state flow of foams of various liquid content, and specifically the motion and deformation of their elementary components, the bubbles. In the frame of the flowing foam, we can observe a recirculation around the obstacle, characterized by a multipolar velocity field. Its complex structure displays a strong fore-aft asymmetry, with an extended region downstream the constriction, where the foam velocity can be much larger than the imposed driving one. This overshoot was already revealed for nonpermeable obstacles, but here we show that its extent and intensity are associated to the bubble deformation and depend strongly and nontrivially on both the geometry of the constriction as well as the liquid fraction of the foam.

In rheological terms, foams are time independent yield stress fluids, displaying properties of both solid and liquid materials. Here we measure the propagation of a 2D dry foam in a radially symmetric Hele-Shaw cell forcing local yielding. The yield rate is manipulated by mechanical vibration with frequencies from 0 to 150 Hz. The flow speed is then extracted from the video stream and analyzed using digital image correlation software. The data are modeled analytically by a Guzman–Arrhenius type of energy landscape where the local yielding of foam correlates with the number of oscillations, i.e. attempts to cross the energy barrier. The model is confirmed in an auxiliary experiment where the vibrated foam stays in its flowing state at the same small driving pressures, where the flow of the unvibrated foam ceases. We conclude that the yield stress behaviour of foams under an external perturbation can be summarized using a simple energy landscape model. The vibration affects the films causing the stress to occasionally and locally exceed the yield threshold. This, thus, prevents the foam from jamming as in a static configuration even when the global driving is below the yield point of the foam.

openaire: EC/H2020/857470/EU//NOMATEN We study the compression of low-weight foam-formed materials made out of wood fibers. Initially the stress-strain behavior follows mean-field like response, related to the buckling of fiber segments as dictated by the random three-dimensional geometry. Our Acoustic Emission (AE) measurements correlate with the predicted number of segment bucklings for increasing strain. However, the experiments reveal a transition to collective phenomena as the strain increases sufficiently. This is also seen in the gradual failure of the theory to account for the stress-strain curves. The collective avalanches exhibit scale-free features both as regards the AE energy distribution and the AE waiting time distributions with both exponents having values close to 2. In cyclic compression tests, significant increases in the accumulated acoustic energy are found only when the compression exceeds the displacement of the previous cycle, which further confirms other sources of acoustic events than fiber bending.

The yielding of dry foams is enabled by small elementary yield events on the bubble scale, “T1”s. We study the large-scale detection of these in an expanding two-dimensional (2D) flow geometry using artificial intelligence (AI) and nearest neighbor analysis. A good level of accuracy is reached by the AI approach using only a single frame, with the maximum score for vertex centered images highlighting the important role the vertices play in the local yielding of foams. We study the predictability of T1s ahead of time and show that this is possible on a timescale related to the waiting time statistics of T1s in local neighborhoods. The local T1 event predictability development is asymmetric in time, and measures the variation of the local property to yielding and similarly the existence of a relaxation timescale after local yielding.

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 $\rho_p = 10^{21}\,\text{m}^{-3}$ 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., Comment: 7 pages, 5 figures. Submitted to Physical Review Materials

Here, we follow the stable propagation of a roughening crack using simultaneously Digital Image Correlation and Infra-Red imaging. In a quasi-two-dimensional paper sample, the crack tip and ahead of that the fracture process zone follow the slowly, diffusively moving “hot spot” ahead of the tip. This also holds when the crack starts to roughen during propagation. The well-established intermittency of the crack advancement and the roughening of the crack in paper are thus subject to the dissipation and decohesion in the hot spot zone. They are therefore not only a result of the depinning of the crack in a heterogeneous material.

We investigate the coupling between the interstitial medium and granular particles by studying the hopper flow of dry and submerged systems 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 by fitting the particle–particle contact friction for each system separately. Submerging the hopper changes the particle–particle contact friction from µvacuum = 0.15 to µsub = 0.13, while all the other simulation parameters remain the same.

A dynamic elastoplastic compression model of Norway spruce for virtual computer optimization of mechanical pulping processes was developed. The empirical wood behaviour was fitted to a Voigt-Kelvin material model, which is based on quasi static compression and high strain rate compression tests (QSCT and HSRT, respectively) of wood at room temperature and at high temperature (80–100°C). The effect of wood fatigue was also included in the model. Wood compression stress-strain curves have an initial linear elastic region, a plateau region and a densification region. The latter was not reached in the HSRT. Earlywood (EW) and latewood (LW) contributions were considered separately. In the radial direction, the wood structure is layered and can well be modelled by serially loaded layers. The EW model was a two part linear model and the LW was modelled by a linear model, both with a strain rate dependent term. The model corresponds well to the measured values and this is the first compression model for EW and LW that is based on experiments under conditions close to those used in mechanical pulping.

Finding out when cracks become unstable is at the heart of fracture mechanics. Cracks often grow by avalanches and when a sample fails depends on its past avalanche history. We study the prediction of sample failure in creep fracture under a constant applied stress and induced by initial flaws. Individual samples exhibit fluctuations around a typical rheological response or creep curve. Predictions using the acoustic emission from the intermittent crack growth are not feasible until well beyond the sample-dependent minimum strain rate. Using an optical speckle analysis technique, we show that predictability is possible later because of the growth of the fracture process zone.

Aqueous foams are viscoelastic yield stress fluids. Due to their complex rheology, foam flow around an obstacle embedded in a 2D Hele-Shaw cell has been widely studied. Typically, in such geometry in the moving flow reference frame the flow field of viscoelastic fluids exhibit a quadrupolar structure characterized by a negative wake. Here, we introduce a measuring geometry, new in this context, whereby instead of flowing the foam around the obstacle, we move the obstacle as an intruder inside the foam. The proposed setup makes it possible to independently control the driving velocity and the liquid foam properties, such as the gas fraction and polydispersity. We show that the liquid foam velocity field around the intruder is similar to the one observed in viscoelastic fluids, in particular the emergence of a negative wake, e.g. a velocity overshoot downstream side of the obstacle. However, surprisingly, the intensity of this velocity overshoot decreases with the number of intruder passes, probably related to the evolution of the local disordered structure of the liquid foam.

Correction for ‘Chlamydomonas reinhardtii swimming in the Plateau borders of 2D foams’ by Oskar Tainio et al., Soft Matter, 2021, 17, 145–152, DOI: 10.1039/D0SM01206H.

Materials flow - under creep or constant loads - and, finally, fail. The prediction of sample lifetimes is an important and highly challenging problem because of the inherently heterogeneous nature of most materials that results in large sample-to-sample lifetime fluctuations, even under the same conditions. We study creep deformation of paper sheets as one heterogeneous material and thus show how to predict lifetimes of individual samples by exploiting the "universal" features in the sample-inherent creep curves, particularly the passage to an accelerating creep rate. Using simulations of a viscoelastic fiber bundle model, we illustrate how deformation localization controls the shape of the creep curve and thus the degree of lifetime predictability.

Dewatering processes are invariably encountered in the chemical manufacturing and processing of various bioproducts. In this study, Computational Fluid Mechanics (CFD) simulations and theory are utilized to model and optimize the dewatering of commercial nanofiber suspensions. The CFD simulations are based on the volume-averaged Navier-Stokes equations, while the analytical model is deduced from the empirical Darcy’s law for dewatering flows. The results are successfully compared to experimental data on commercial cellulose suspensions obtained with a Dynamic Drainage Analyzer (DDA). Both the CFD simulations and the analytical model capture the dewatering flow profiles of the commercial suspensions in an experiment using a constant pressure profile. However, a temporally varying pressure profile offers a superior dewatering performance, as indicated by both the simulations and the analytical model. Finally, the analytical model also predicts an optimized number of pressure pulses, minimizing the time required to completely dewater the suspension.

Cyclic loading on granular packings and amorphous media leads to a transition from reversible elastic behavior to an irreversible plasticity. In the present study, we investigate the effect of oscillatory shear on polycrystalline and amorphous colloidal solids by performing molecular dynamics simulations. Our results show that close to the transition, both systems exhibit enhanced particle mobility, hysteresis, and rheological loss of rigidity. However, the rheological response shows a sharper transition in the case of the polycrystalline sample as compared to the amorphous solid. In the polycrystalline system, we see the disappearance of disclinations, which leads to the formation of a monocrystalline system, whereas the amorphous system hardly shows any ordering. After the threshold strain amplitude, as we increase the strain amplitude both systems get fluid. In addition to that, particle displacements are more homogeneous in the case of polycrystalline systems as compared to the amorphous solid, mainly when the strain amplitude is larger than the threshold value. We do not see any effect of oscillation frequency on the reversible-irreversible transition.

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., Comment: Published version from https://www.nature.com/articles/s41467-018-07737-2. Supplementary material can also be found from the link

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., 5 pages, 5 figures

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. acceptedVersion

The curling motion of the curling stone on ice is well-known: if a small clockwise rotational velocity is imposed to the stone when it is released, in addition to the linear propagation velocity, the stone will curl to the right. A similar curl to the left is obtained by counter-clockwise rotation. This effect is widely used in the game to reach spots behind the already thrown stones, and the rotation also causes the stone to propagate in a more predictable fashion. Here, we report on novel experimental results which support one of the proposed theories to account for the curling motion of the stone, known as the “scratch-guiding theory”. By directly scanning the ice surface with a white light interferometer before and after each slide, we observed cross-scratches caused by the leading and trailing parts of the circular contact band of the linearly moving and rotating stone. By analyzing these scratches and a typical curling stone trajectory, we show that during most of the slide, the transverse force responsible for the sideways displacement of the stone is linearly proportional to the angle between these cross-scratches.

Plastic deformation of crystalline materials is governed by the features of stress-driven motion of dislocations. In the case of irradiated steels subject to applied stresses, small dislocation loops as well as precipitates are known to interfere with the dislocation motion, leading to an increased yield stress as compared to pure crystals. We study the combined effect of precipitates and interstitial glissile $$\frac{{\bf{1}}}{{\bf{2}}}\langle {\bf{111}}\rangle $$ 1 2 〈 111 〉 dislocation loops on the yield stress of iron, using large-scale three-dimensional discrete dislocation dynamics simulations. Precipitates are included in the simulations using our recent multi-scale implementation [A. Lehtinen et al., Phys. Rev. E 93 (2016) 013309], where the strengths and pinning mechanisms of the precipitates are determined from molecular dynamics simulations. In the simulations we observe dislocations overcoming precipitates with an atypical Orowan mechanism which results from pencil-glide of screw segments in iron. Even if the interaction mechanisms with dislocations are quite different, our results suggest that in relative terms, precipitates and loops of similar sizes contribute equally to the yield stress in multi-slip conditions.

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.

Nuclear fuel material is an example of a sintered, porous ceramic material. We formulate a two-dimensional model which couples three physical mechanisms in the material: (scalar) damage accumulation by thermal creep and radiation effects, porosity changes due to the damage, and the time-dependent diffusion of (radiation-induced) gases in the pore system thus created. The most important effect in the dynamics arises from the process where the pore system is swept through the percolation transition. The main conclusions that can be drawn concern the fractional gas release and its dependence on the three effects present in the damage dynamics: creep, radiation-induced bubble formation, and recovery due to bubble closure. In the main, the model reproduces the experimentally observed quick gas release phenomenon qualitatively.

The effect of fatigue treatment on the thermal conductivity of wood was studied. Fresh Norway spruce samples both with and without fatigue were analyzed in a temperature rise experiment by means of an infrared camera. The experimental temperature profiles were compared to finite-element simulations of heat conduction. The temporal features of temperature profiles indicate an increase in the conductivity of fatigued wood, which points to changes in the cellular structure of wood. The importance of fatigue for thermal conductivity and consequently for mechanical pulp-making is discussed.