Datasets for the analysis of dislocations at grain boundaries and during vein formation in cyclically deformed Ni micropillars.

The dataset together with the corresponding Python scripts and Jupyter notebooks presented in this article are supplementary data for the work presented in Samaee et al., 2019 [1]. The data itself consists of two parts: the simulation data that was used in [1] to analyze the effect of a particular grain boundary on curved dislocations and the precession electron diffraction (PED) strain maps together with post-processed data for analyzing details of the observed dislocation vein structures. Additionally, the complete stress tensor components, which are not shown in [1], have also been included. The data sets are accompanied by Python code explaining the file formats and showing how to post-process the data.

Analysis of the Basal Plane Dislocation Density and Thermomechanical Stress during 100 mm PVT Growth of 4H-SiC.

Basal plane dislocations (BPDs) in 4H silicon carbide (SiC) crystals grown using the physical vapor transport (PVT) method are diminishing the performance of SiC-based power electronic devices such as pn-junction diodes or MOSFETs. Therefore, understanding the generation and movement of BPDs is crucial to grow SiC suitable for device manufacturing. In this paper, the impact of the cooldown step in PVT-growth on the defect distribution is investigated utilizing two similar SiC seeds and identical growth parameters except for a cooldown duration of 40 h and 70 h, respectively. The two resulting crystals were cut into wafers, which were characterized by birefringence imaging and KOH etching. The initial defect distribution of the seed wafer was characterized by synchrotron white beam X-ray topography (SWXRT) mapping. It was found that the BPD density increases with a prolonged cooldown time. Furthermore, small angle grain boundaries based on threading edge dislocation (TED) arrays, which are normally only inherited by the seed, were also generated in the case of the crystal cooled down in 70 h. The role of temperature gradients inside the crystal during growth and post-growth concerning the generation of shear stress is discussed and supported by numerical calculations.

Predicting the flow stress and dominant yielding mechanisms: analytical models based on discrete dislocation plasticity.

Dislocations are the carriers of plasticity in crystalline materials. Their collective interaction behavior is dependent on the strain rate and sample size. In small specimens, details of the nucleation process are of particular importance. In the present work, discrete dislocation dynamics (DDD) simulations are performed to investigate the dominant yielding mechanisms in single crystalline copper pillars with diameters ranging from 100 to 800 nm. Based on our simulations with different strain rates and sample size, we observe a transition of the relevant nucleation mechanism from "dislocation multiplication" to "surface nucleation". Two physics-based analytical models are established to quantitatively predict this transition, showing a good agreement for different strain rates with our DDD simulation data and with available experimental data. Therefore, the proposed analytical models help to understand the interplay between different physical parameters and nucleation mechanisms and are well suitable to estimate the material strength for different material properties and under given loading conditions.

Universal features of amorphous plasticity.

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.

Scalar model for frictional precursors dynamics.

Recent experiments indicate that frictional sliding occurs by nucleation of detachment fronts at the contact interface that may appear well before the onset of global sliding. This intriguing precursory activity is not accounted for by traditional friction theories but is extremely important for friction dominated geophysical phenomena as earthquakes, landslides or avalanches. Here we simulate the onset of slip of a three dimensional elastic body resting on a surface and show that experimentally observed frictional precursors depend in a complex non-universal way on the sample geometry and loading conditions. Our model satisfies Archard's law and Amontons' first and second laws, reproducing with remarkable precision the real contact area dynamics, the precursors' envelope dynamics prior to sliding, and the normal and shear internal stress distributions close to the interfacial surface. Moreover, it allows to assess which features can be attributed to the elastic equilibrium, and which are attributed to the out-of-equilibrium dynamics, suggesting that precursory activity is an intrinsically quasi-static physical process. A direct calculation of the evolution of the Coulomb stress before and during precursors nucleation shows large variations across the sample, explaining why earthquake forecasting methods based only on accumulated slip and Coulomb stress monitoring are often ineffective.