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For research data to be reusable by scientists or machines, the data and associated meta-data should comply with the so-called "FAIR principles", i.e. it should be findable, accessible, interoperable, and reusable [1]. To realize this, is not a straightforward task, as researchers do not know how FAIR or un-fair their data actually is and how to improve their FAIRness. A quantitative measure, which is easy to apply could help. The Helmholtz Metadata Collaboration (HMC) works on improving tools to automate the assessment of the FAIRness of publications. The F-UJI framework [2] originating from the FAIRsFAIR project is a powerful tool that provides a score for the FAIRness for machine findable and readible metadata of a given publication with respect to the FAIRsFAIR metric [3]. We co-develop F-UJI to explore and evaluate ways to apply it in user-sided tools. On this poster we present a FAIR assessment through F-UJI of Helmholtz data repositories. With our work, we want to identify gaps in the Helmholtz data infrastructure with respect to the FAIRness of (meta)data and how these gaps can be closed effectively. We also provide an outlook on possible research into the development of FAIRness over time within communities. [1] Wilkinson, M.D.et al. Sci Data 3, 160018 (2016) [2] Devaraju, A., Huber, R. (2020). F-UJI, Zenodo. https://doi.org/10.5281/zenodo.4063720 [3] Devaraju, A., et al. (2020). FAIRsFAIR Metrics. Zenodo. https://doi.org/10.5281/zenodo.6461229

Widely used to quantify material wear, the Archard wear law was derived from the asperity flattening model. However, the flattening model is so idealized that it cannot properly represent the real situation with general interlocked asperities, where asperity plowing dominates the wear instead of shearing flattened asperity. Using molecular dynamics simulations, we discussed if Archard law can hold during plowing wear of interlocked interface. Our results indicated Archard law breaks down when fracture dominates the wear. Furthermore, increasing interfacial adhesion or decreasing material ductility changes the dominant wear factor from plasticity to fracture. Finally, we proposed a criterion to determine when Archard wear law will break down and discussed the proposed criterion for real materials.

The review on bulk growth of SiC includes a basic overview on the widely used physical vapor transport method for processing of 4H-SiC boules as well as the discussion of three current research topics: (a) Sublimation bulk growth of large area, freestanding cubic SiC, (b) in-situ Visualization of the PVT Process using 2D and 3D X-ray based imaging and (c) prediction of dislocation formation and motion in SiC using a continuum model of dislocation dynamics (CDD).

Screw-type dislocations like micropipes (MP) and threading screw dislocations (TSD) are prohibiting the function or at least diminishing the efficiency of electronic devices based on silicon carbide (SiC). Therefore, it is essential to characterize wafers in an efficient and fast manner. Molten potassium hydroxide (KOH) etching or white-beam X-ray topography (SWXRT) are either destructive or not economically viable for an in-depth characterization of every wafer of one SiC crystal. Birefringence microscopy is being utilized as a fast and non-destructive characterization method. Instead of microscopic setups, commercially available flat-bed scanners equipped with crossed polarizer foils can be used for fast large-area scans. This work investigates the feasibility of such a setup regarding the detection rate of MPs and TSDs. The results of a full-wafer mapping are compared with birefringence microscopy and KOH etching. In the investigated sample clusters of MPs caused by a polytype switch in the beginning of the growth could be identified by both birefringence microscopy and the flat-bed scanner setup, as well as small angle grain boundaries and TED arrays. However, the resolution of the scanner was not sufficient to identify TSDs. Nevertheless the setup proves to be an easy-to-setup and cheap characterization method, able to quickly identify defect clusters in 4H-SiC wafers.

The lifetime and performance of any engineering component, from nanoscale sensors to macroscopic structures, are strongly influenced by fracture processes. Fracture itself is a highly localized event; originating at the atomic scale by bond breaking between individual atoms close to the crack tip. These processes, however, interact with defects such as dislocations or grain boundaries and influence phenomena on much larger length scales, ultimately giving rise to macroscopic behavior and engineering-scale fracture properties. This complex interplay is the fundamental reason why identifying the atomistic structural and energetic processes occurring at a crack tip remains a longstanding and still unsolved challenge. We develop a new analysis approach for combining quantitative in-situ observations of nanoscale deformation processes at a crack tip with three-dimensional reconstruction of the dislocation structure and advanced computational analysis to address plasticity and fracture initiation in a ductile metal. Our combinatorial approach reveals details of dislocation nucleation, their interaction process, and the local internal stress state, all of which were previously inaccessible to experiments. This enables us to describe fracture processes based on local crack driving forces on a dislocation level with a high fidelity that paves the way towards a better understanding and control of local failure processes in materials.

Acta materialia 241, 118394 (2022). doi:10.1016/j.actamat.2022.118394, Published by Elsevier Science, Amsterdam [u.a.]

International audience; In situ straining experiments were performed in a TEM on an equimolar CoCrFeMnNi (Cantor) high entropy alloy at room and cryogenic temperature. Perfect and partial dislocation activity were recorded in both cases. Twinning directly follows the development of partial dislocation shearing that has various origins (perfect dislocation splitting, anchoring). It is shown that, although twinning is more frequently observed at liquid nitrogen temperature, its prevalence depends mainly on crystal orientation. As a result, twinning and perfect dislocation plasticity are likely to occur jointly in random oriented polycrystals, even at early stages of deformation.

Polycrystal microstructures, with their distinct physical, chemical, structural and topological entities, play an important role in determining the effective properties of materials. Particularly for computational studies, the well-known Voronoi tessellation technique is regularly used for obtaining microstructures. Standard Voronoi tessellations, however, exhibit statistics that are generally far removed from those in real microstructures. Nevertheless, such tessellations can be optimized to obtain certain key features and statistics seen in real microstructures. In this work, we develop the open-source software package OptiMic that enables the generation of optimized microstructures for both finite element as well as atomistic simulations. OptiMic allows for both monodispersive grains as well as irregular grains obtained currently via Voronoi tessellations. These initial microstructures can then be optimized to reflect desired statistical features. A key feature of the tool is that it gives the user extensive control on the optimization process via customizable cost functions. The software currently performs tessellations with the Voronoi method and can be easily extended to include other methods like grain-growth, phase-field etc., Comment: 19 pages, 6 figures, Manuscript submitted to SoftwareX

A macroscopically nominal flat surface is rough at the nanoscale level and consists of nanoasperities. Therefore, the frictional properties of the macroscale-level rough surface are determined by the mechanical behaviors of nanoasperity contact pairs under shear. In this work, we first used molecular dynamics simulations to study the non-adhesive shear between single contact pairs. Subsequently, to estimate the friction coefficient of rough surfaces, we implemented the frictional behavior of a single contact pair into a Greenwood-Williamson-type statistical model. By employing the present multiscale approach, we used the size, rate, and orientation effects, which originated from nanoscale dislocation plasticity, to determine the dependence of the macroscale friction coefficient on system parameters, such as the surface roughness and separation, loading velocity, and direction. Our model predicts an unconventional dependence of the friction coefficient on the normal contact load, which has been observed in nanoscale frictional tests. Therefore, this model represents one step toward understanding some of the relevant macroscopic phenomena of surface friction at the nanoscale level., 29 pages, 16 figures

Transmission electron microscopy and finite element-based dislocation simulations were combined to study the development of dislocation microstructures after cyclic deformation of single crystal and bicrystal Ni micropillars oriented for multi-slip. A direct correlation between large accumulation of plastic strain and the presence of dislocation cell walls in the single crystal micropillars was observed, while the presence of the grain boundary hampered the formation of wall-like structures in agreement with a smaller accumulated plastic strain. Automated crystallographic orientation and nanostrain mapping using transmission electron microscopy revealed the presence of lattice heterogeneities associated to the cell walls including long range elastic strain fields. By combining the nanostrain mapping with an inverse modelling approach, information about dislocation density, line orientation and Burgers vector direction was derived, which is not accessible otherwise in such dense dislocation structures. Simulations showed that the image forces associated with the grain boundary in this specific bicrystal configuration have only a minor influence on dislocation behavior. Thus, the reduced occurrence of “mature” cell walls in the bicrystal can be attributed to the available volume, which is too small to accommodate cell structures.

Transformation Induced Plasticity (TRIP) steels undergo a diffusionless phase transformation from austenite to martensite, resulting in a material exhibiting desireable material properties such as exceptional balance of strength and ductility as well as good fatigue behavior. Computational modeling at the mesoscale is potentially a suitable tool for studying how plastic deformation interacts with phase transformations and ultimately affects the bulk properties of these steels. We introduce models that represent the phase microstructure in a continuum approach and couple a time-dependent Ginzburg-Landau equation with discrete dislocation via their elastic strain energy densities. With this, the influence of several dislocation configurations are examined, namely a single dislocation, a “penny-shaped crack”, and a “dislocation cascade”. It is shown that the strain due to the presence of dislocations has a significant influence on the resultant martensitic microstructure. Furthermore, the importance of using a non-local elasticity approach for the dislocation stress fields is demonstrated.

Cellular solids usually possess random microstructures that may contain a characteristic length scale, such as the cell size. This gives rise to size dependent mechanical properties where large systems behave differently from small systems. Furthermore, these structures are often irregular, which not only affects the size dependent behavior but also leads to significant property variations among different microstructure realizations. The computational model for cellular microstructures is based on networks of Timoshenko beams. It is a computationally efficient approach allowing to obtain statistically representative averages from computing large numbers of realizations. For detailed analysis of the underlying deformation mechanisms an energetically consistent continuization method was developed which links the forces and displacements of discrete beam networks to equivalent spatially continuous stress and strain fields. This method is not only useful for evaluation and visualization purposes but also allows to perform ensemble averages of, e.g., continuous stress patterns – an analysis approach which is highly beneficial for comparisons and statistical analysis of microstructures with respect to different degrees of structural disorder.

Data science and informatics have emerged as the fourth paradigm of scientific research over the past decade. Although the impact of this new paradigm is very apparent in many scientific fields and has seen many success stories, the field of materials informatics – data science and informatics for materials science and engineering – is still in its infancy. Based on the availability of data, the field of materials science would be ideal for data analytics and informatics, particularly if such data is shared with the larger materials science community. In this work, we discuss the advantages of digitalization and data science, current challenges for experiments and simulations involving data management, acquisition and sharing, and look at possible solutions.

Parallel computational results for problems in dislocation mechanics are presented using the deal.II adaptive finite element software and the Fast and Robust Overlapping Schwarz Preconditioner (FROSch).

In this work we study shock-induced plasticity in Mo single crystals, impacted along the 〈1 1 0〉 crystal orientation. In particular, the shear relaxation behind the shock front is quantitatively inspected. Molecular dynamics (MD) simulations are employed to simulate the deformation during shock, followed by post-processing to identify and quantify the dislocation lines nucleated behind the shock front. The information on the dislocation lines is ensemble averaged inside slabs of the simulation box and over different realizations of the MD simulations, from which continuous dislocation fields are extracted using the Discrete-to-Continuous method. The continuous dislocation fields are correlated with the stress and strain fields obtained from the MD simulations. Based on this analysis, we show that the elastic precursor overshoots the shear stress, after which dislocations on a specific group of slip planes are nucleated, slightly lagging behind the elastic front. Consequently, the resolved shear stress is relaxed, but the principal lateral stress increases. The latter leads to an increase in the resolved shear stress on a plane parallel to the shock wave, resulting in an additional retarded front of dislocation nucleation on planes parallel to the shock front. Finally, the two-stage process of plasticity results in an isotropic stress state in the plane parallel to the shock wave. The MD simulation results are employed to calculate the dislocation densities on specific slip planes and the plastic deformation behind the shock, bridging the gap between the information on the atomic scale and the continuum level.

In single crystal Nickel-based superalloys subject to creep loading, the γ / γ ′ phase microstructure co-evolves with the system of dislocations under load. Computational modeling thus requires multiphysics approaches capable of describing and simulating both phase and defect microstructures within a common conceptual framework. To do so, we formulate a coupled continuum model of the evolution of phase and dislocation microstructures. The simulated γ / γ ′ phase microstructure accounts for concentration as well as crystallographic order parameters. Dislocation microstructure evolution is described in terms of dislocation densities and associated stress-driven dislocation fluxes. The creep strain curve is obtained as a natural by-product of the microstructure evolution equations. We perform simulations of γ / γ ′ evolution for different dislocation densities and establish the driving forces for microstructure evolution by analyzing in detail the changes in different contributions to the elastic energy and chemical free energy density, as well as the evolution of stress concentrations that may trigger the transition from dislocation flow in the γ channels towards shearing of the γ ′ precipitates. Our investigation reveals the mechanisms controlling the process of directional coarsening (rafting) and demonstrates that the kinetics of rafting significantly depends on characteristics of the dislocation microstructure. In addition to rafting under constant load, we investigate the effect of changes in loading conditions and explore the possibility of improving creep properties by pre-rafting along a different loading path.

A new approach for characterizing the dislocation microstructure obtained from atomistic simulations is introduced, which relies on converting properties of discrete lines to continuous data. This data is represented by a number of density and density-like field variables containing detailed information about properties of the dislocation microstructure. Applying this methodology to atomistic simulations of nanoscratching in iron reveals a pronounced “length scale effect”: With increasing scratching length the number of dislocations increases but the density of geometrically necessary dislocations remains constant resulting in decreasing shear stress. During scratching dislocations are mostly generated at the scratch front. The nucleation rate versus scratching length has an approximately antisymmetric shape with respect to the scratch front leading to an almost constant curvature.

The effect of initial dislocation density and external stress on primary creep of Nickel-based superalloys are studied by a combined continuum dislocation dynamics/phase-field model. This model can simultaneously predict the dislocation motion as well as the γ / γ ' evolution and yields macroscopic creep properties as a natural outcome – all of which are supported by experimental data. The rafting simulation results show that the initial dislocation density as well as the external stress can dramatically influence the aspect ratio of the γ ' precipitates and the interface dislocation density at the γ / γ ' interfaces. In contrast, the plastic strain towards the end of primary creep is not sensitive to the initial dislocation density due to a seeming strain rate inversion during creep, and it is dependent on the applied external stress.

Plastic yielding of amorphous solids occurs by power-law distributed deformation avalanches whose universality is still debated. Experiments and molecular dynamics simulations are hampered by limited statistical samples, and although existing stochastic models give precise exponents, they require strong assumptions about fixed deformation directions, at odds with the statistical isotropy of amorphous materials. Here, we introduce a fully tensorial, stochastic mesoscale model for amorphous plasticity that links the statistical physics of plastic yielding to engineering mechanics. It captures the complex shear patterning observed for a wide variety of deformation modes, as well as the avalanche dynamics of plastic flow. Avalanches are described by universal size exponents and scaling functions, avalanche shapes, and local stability distributions, independent of system dimensionality, boundary and loading conditions, and stress state. Our predictions consistently differ from those of mean-field depinning models, providing evidence that plastic yielding is a distinct type of critical phenomenon., The universality class for plastic yield in amorphous materials remains controversial. Here authors present a tensorial mesoscale model that captures both complex shear patterns and avalanche scaling behaviour, which differs from mean-field models and suggests a distinct type of critical phenomenon.

Some materials are strong in response to a slowly applied deformation, yet weak when subject to rapid deformations—a materials property known as strain-rate softening1. Snow exhibits such behaviour: it is comparatively strong at low deformation rates, where it is quasi-plastic, but weak at high rates, where it deforms in a quasi-brittle manner2. During deformation, strain-rate-softening materials ranging from metals3, 4 to micellar systems5 exhibit complex spatio-temporal deformation patterns, including regular or chaotic deformation-rate oscillations and travelling deformation waves6. Here we report a systematic investigation of such phenomena in snow and show that snow can deform with the formation and propagation of localized deformation bands accompanied by oscillations of the driving force. We propose a model that accounts for these observations. Our findings demonstrate that in snow, strain localization can occur even in initially homogeneous samples deforming under homogeneous loads.

The Greenwood–Williamson (GW) model has been one of the commonly used contact models to study rough surface contact problems during the past decades. While this has been a successful model, it still has a number of restrictions: (i) surface asperities are spheres; (ii) the overall deformation must be assumed to be small enough, such that there is no interaction between asperities, i.e., they are independent of each other; and (iii) asperity deformation remains elastic. This renders the GW model unrealistic in many situations. In the present work, we resolve above restrictions in a discrete version of the GW model: instead of spherical asperities, we assumed that the surface consists of three-dimensional sinusoidal asperities which appear more similar to asperities on a rough surface. For single asperity mechanical response, we propose a Hertz-like analytical solution for purely elastic deformation and a semi-analytical solution based on finite element method (FEM) for elastic–plastic deformation. The asperity interaction is accounted for by discretely utilizing a modified Boussinesq solution without consideration of asperity merger. It is seen that the asperity interaction effect is more than just the delay of contact as shown in the statistical model, it also contributes to the loss of linearity between the contact force and the contact area. Our model also shows that: for elastic contact, using spherical asperities results in a larger average contact pressure than using sinusoids; when plasticity is taken into account, using a sphere to represent asperities results in a softer response as compared with using sinusoids. It is also confirmed that sinusoidal asperities are a much better description than spheres, by comparison with fully resolved FEM simulation results for computer-generated rough surfaces.

Plasticity is governed by the evolution of, in general anisotropic, systems of dislocations. We seek to faithfully represent this evolution in terms of density-like variables which average over the discrete dislocation microstructure. Starting from T. Hochrainer's continuum theory of dislocations (CDD) ( Hochrainer, 2015 ), we introduce a methodology based on the ‘Maximum Information Entropy Principle’ (MIEP) for deriving closed-form evolution equations for dislocation density measures of different order. These equations provide an optimum representation of the kinematic properties of systems of curved and connected dislocation lines with the information contained in a given set of density measures. The performance of the derived equations is benchmarked against other models proposed in the literature, using discrete dislocation dynamics simulations as a reference. As a benchmark problem we study dislocations moving in a highly heterogeneous, persistent-slip-band like geometry. We demonstrate that excellent agreement with discrete simulations can be obtained in terms of a very small number of averaged dislocation fields containing information about the edge and screw components of the total and excess (geometrically necessary) dislocation densities. From these the full dislocation orientation distribution which emerges as dislocations move through a channel-wall structure can be faithfully reconstructed.