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Register a new userControlling Strain Bursts and Avalanches at the Nano-to-Micro Scale
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We demonstrate, through 3-dimensional discrete dislocation dynamics simulations, that the com- plex dynamical response of nano and micro crystals to external constraints can be tuned. Under load rate control, strain bursts are shown to exhibit scale-free avalanche statistics, similar to critical phenomena in many physical systems. For the other extreme of displacement rate control, strain burst response transitions to quasi-periodic oscillations, similar to stick-slip earthquakes. External load mode control is shown to enable a qualitative transition in the complex collective dynamics of dislocations from self-organized criticality to quasi-periodic oscillations.
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Plastic deformation of micron and sub-micron scale specimens is characterized by intermittent sequences of large strain bursts (dislocation avalanches) which are separated by regions of near-elastic loading. In the present investigation we perform a statistical characterization of strain bursts observed in stress-controlled compressive deformation of monocrystalline Molybdenum micropillars. We characterize the bursts in terms of the associated elongation increments and peak deformation rates, and demonstrate that these quantities follow power-law distributions that do not depend on specimen orientation or stress rate. We also investigate the statistics of stress increments in between the bursts, which are found to be Weibull distributed and exhibit a characteristic size effect. We discuss our findings in view of observations of deformation bursts in other materials, such as face-centered cubic and hexagonal metals.
Oligothiophenes are pi-conjugated semiconducting and fluorescent molecules whose self-assembly properties are widely investigated for application in organic electronics, optoelectronics, biophotonics and sensing. We report here an approach to the preparation of crystalline oli-gothiophene nano/micro-fibers based on the use of a sulfur overrich quaterthiophene building block, -T4S4-, containing in its covalent network all the information needed to promote the di-rectional, pi-pi stacking driven, self-assembly of Ar-T4S4-Ar oligomers into fibers with hierar-chical supramolecular arrangement from nano- to microscale. We show that when Ar varies from unsubstituted thiophene to thiophene substituted with electron withdrawing groups, a wide redistribution of the molecular electronic charge takes place without substantially affecting the aggregation modalities of the oligomer. In this way a structurally comparable series of fibers is obtained having progressively varying optical properties, redox potentials, photoconductivity and type of prevailing charge carriers (from p- to n-type). A thorough characterization of the fi-bers based on SEM, CD, CV, X-ray diffraction, UV-vis and PL spectroscopies, photoconductivi-ty and KPFM measurements is reported. With the aid of DFT calculations, combined with X-ray data, a model accounting for the growth of the fibers from molecular to nano- and microscale is proposed. We believe that the simple strategy outlined in this study allows to establish a straightforward correlation between the molecular structure of the components and the function-al properties of the corresponding self-assembled nano/micro-fibers.
X-ray Computed Tomography (X-ray CT) is a well-known non-destructive imaging technique where contrast originates from the materials absorption coefficients. Novel battery characterization studies on increasingly challenging samples have been enabled by the rapid development of both synchrotron and laboratory-scale imaging systems as well as innovative analysis techniques. Furthermore, the recent development of laboratory nano-scale CT (NanoCT) systems has pushed the limits of battery material imaging towards voxel sizes previously achievable only using synchrotron facilities. Such systems are now able to reach spatial resolutions down to 50 nm. Given the non-destructive nature of CT, in-situ and operando studies have emerged as powerful methods to quantify morphological parameters, such as tortuosity factor, porosity, surface area, and volume expansion during battery operation or cycling. Combined with powerful Artificial Intelligence (AI)/Machine Learning (ML) analysis techniques, extracted 3D tomograms and battery-specific morphological parameters enable the development of predictive physics-based models that can provide valuable insights for battery engineering. These models can predict the impact of the electrode microstructure on cell performances or analyze the influence of material heterogeneities on electrochemical responses. In this work, we review the increasing role of X-ray CT experimentation in the battery field, discuss the incorporation of AI/ML in analysis, and provide a perspective on how the combination of multi-scale CT imaging techniques can expand the development of predictive multiscale battery behavioral models.
Lattice defects play a key role in determining the properties of crystalline materials. Probing the 3D lattice strains that govern their interactions remains a challenge. Bragg Coherent Diffraction Imaging (BCDI) allows strain to be measured with nano-scale 3D resolution. However, it is currently limited to materials that form micro-crystals. Here we introduce a new technique that allows the manufacture of BCDI samples from bulk materials. Using tungsten as an example, we show that focussed ion beam (FIB) machining can be used to extract, from macroscopic crystals, micron-sized BCDI samples containing specific pre-selected defects. To interpret the experimental data, we develop a new displacement-gradient-based analysis for multi-reflection BCDI. This allows accurate recovery of the full lattice strain tensor from samples containing multiple dislocations. These new capabilities open the door to BCDI as a microscopy tool for studying complex real-world materials.
We investigate native nitrogen (NV) and silicon vacancy (SiV) color centers in commercially available, heteroepitaxial, wafer-sized, mm thick, single-crystal diamond. We observe single, native NV centers with a density of roughly 1 NV per $mu m^3$ and moderate coherence time ($T_2 = 5 mu s$) embedded in an ensemble of SiV centers. Low-temperature spectroscopy of the SiV zero phonon line fine structure witnesses high crystalline quality of the diamond especially close to the growth surface, consistent with a reduced dislocation density. Using ion implantation and plasma etching, we verify the possibility to fabricate nanostructures with shallow color centers rendering our diamond material promising for fabrication of nanoscale sensing devices. As this diamond is available in wafer-sizes up to $100 mm$ it offers the opportunity to up-scale diamond-based device fabrication.
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