ManyLands: A Journey Across 4D Phase Space of Trajectories

Mathematical models of ordinary differential equations are used to describe and understand biological phenomena. These models are dynamical systems that often describe the time evolution of more than three variables, i.e., their dynamics take place in a multi‐dimensional space, called the phase space. Currently, mathematical domain scientists use plots of typical trajectories in the phase space to analyze the qualitative behavior of dynamical systems. These plots are called phase portraits and they perform well for 2D and 3D dynamical systems. However, for 4D, the visual exploration of trajectories becomes challenging, as simple subspace juxtaposition is not sufficient. We propose ManyLands to support mathematical domain scientists in analyzing 4D models of biological systems. By describing the subspaces as Lands, we accompany domain scientists along a continuous journey through 4D HyperLand, 3D SpaceLand, and 2D FlatLand, using seamless transitions. The Lands are also linked to 1D TimeLines. We offer an additional dissected view of trajectories that relies on small‐multiple compass‐alike pictograms for easy navigation across subspaces and trajectory segments of interest. We show three use cases of 4D dynamical systems from cell biology and biochemistry. An informal evaluation with mathematical experts confirmed that ManyLands helps them to visualize and analyze complex 4D dynamics, while facilitating mathematical experiments and simulations.     

Electron Mobility of 24 cm2 V−1 s−1 in PbSe Colloidal‐Quantum‐Dot Superlattices

Colloidal quantum dots (CQDs) are nanoscale building blocks for bottom‐up fabrication of semiconducting solids with tailorable properties beyond the possibilities of bulk materials. Achieving ordered, macroscopic crystal‐like assemblies has been in the focus of researchers for years, since it would allow exploitation of the quantum‐confinement‐based electronic properties with tunable dimensionality. Lead‐chalcogenide CQDs show especially strong tendencies to self‐organize into 2D superlattices with micrometer‐scale order, making the array fabrication fairly simple. However, most studies concentrate on the fundamentals of the assembly process, and none have investigated the electronic properties and their dependence on the nanoscale structure induced by different ligands. Here, it is discussed how different chemical treatments on the initial superlattices affect the nanostructure, the optical, and the electronic‐transport properties. Transistors with average two‐terminal electron mobilities of 13 cm² V^?1 s^?1 and contactless mobility of 24 cm² V^?1 s^?1 are obtained for small‐area superlattice field‐effect transistors. Such mobility values are the highest reported for CQD devices wherein the quantum confinement is substantially present and are comparable to those reported for heavy sintering. The considerable mobility with the simultaneous preservation of the optical bandgap displays the vast potential of colloidal QD superlattices for optoelectronic applications.     

Visual Analysis of Defects in Glass Fiber Reinforced Polymers for 4DCT Interrupted In situ Tests

Material engineers use interrupted in situ tensile testing to investigate the damage mechanisms in composite materials. For each subsequent scan, the load is incrementally increased until the specimen is completely fractured. During the interrupted in situ testing of glass fiber reinforced polymers (GFRPs) defects of four types are expected to appear: matrix fracture, fiber/matrix debonding, fiber pull‐out, and fiber fracture. There is a growing demand for the detection and analysis of these defects among the material engineers. In this paper, we present a novel workflow for the detection, classification, and visual analysis of defects in GFRPs using interrupted in situ tensile tests in combination with X‐ray Computed Tomography. The workflow is based on the automatic extraction of defects and fibers. We introduce the automatic Defect Classifier assigning the most suitable type to each defect based on its geometrical features. We present a visual analysis system that integrates four visualization methods: 1) the Defect Viewer highlights defects with visually encoded type in the context of the original CT image, 2) the Defect Density Maps provide an overview of the defect distributions according to type in 2D and 3D, 3) the Final Fracture Surface estimates the material fracture's location and displays it as a 3D surface, 4) the 3D Magic Lens enables interactive exploration by combining detailed visualizations in the region of interest with overview visualizations as context. In collaboration with material engineers, we evaluate our solution and demonstrate its practical applicability.     

Testing loaded samples using X-ray computed tomography

Methods for studying polymer composites by X-ray computed tomography are presented. A test bench for generating static loads and investigating materials is considered.     

Balancing the Load

We have developed a stack of semantics for a high-level C-like language and low-level assembly code, which has been carefully crafted to support the pervasive verification of system software. It can handle mixed-language implementations and concurrently operating devices, and permits the transferral of properties to the target architecture while obeying its resource restrictions. We demonstrate the applicability of our framework by proving the correct virtualization of user memory in our microkernel, which implements demand paging. This verification target is of particular interest because it has a relatively simple top-level specification and it exercises all parts of our semantics stack. At the bottom level a disk driver written in assembly implements page transfers via a swap disk. A page-fault handler written in C uses the driver to implement the paging algorithm. It guarantees that a step of the currently executing user can be simulated at the architecture level. Besides the mere theoretical and technical difficulties the project also bore the social challenge to manage the large verification effort, spread over many sites and people, concurrently contributing to and maintaining a common theory corpus. We share our experiences and elaborate on lessons learned.     

Dynamic Networks of Cellulose Nanofibrils Enable Highly Conductive and Strong Polymer Gel Electrolytes for Lithium-Ion Batteries

Tunable dynamic networks of cellulose nanofibrils (CNFs) are utilized to prepare high-performance polymer gel electrolytes. By swelling an anisotropically dewatered, but never dried, CNF gel in acidic salt solutions, a highly sparse network is constructed with a fraction of CNFs as low as 0.9%, taking advantage of the very high aspect ratio and the ultra-thin thickness of the CNFs (micrometers long and 2–4 nm thick). These CNF networks expose high interfacial areas and can accommodate massive amounts of the ionic conductive liquid polyethylene glycol-based electrolyte into strong homogeneous gel electrolytes. In addition to the reinforced mechanical properties, the presence of the CNFs simultaneously enhances the ionic conductivity due to their excellent strong water-binding capacity according to computational simulations. This strategy renders the electrolyte a room-temperature ionic conductivity of 0.61 ± 0.12 mS cm⁻¹ which is one of the highest among polymer gel electrolytes. The electrolyte shows superior performances as a separator for lithium iron phosphate half-cells in high specific capacity (161 mAh g⁻¹ at 0.1C), excellent rate capability (5C), and cycling stability (94% capacity retention after 300 cycles at 1C) at 60 °C, as well as stable room temperature cycling performance and considerably improved safety compared with commercial liquid electrolyte systems.     

Visual optimality and stability analysis of 3DCT scan positions

Industrial cone-beam X-Ray computed tomography (CT) systems often face problems due to artifacts caused by a bad placement of the specimen on the rotary plate. This paper presents a visual-analysis tool for CT systems, which provides a simulation-based preview and estimates artifacts and deviations of a specimen's placement using the corresponding 3D geometrical surface model as input. The presented tool identifies potentially good or bad placements of a specimen and regions of a specimen, which cause the major portion of artefacts. The tool can be used for a preliminary analysis of the specimen before CT scanning, in order to determine the optimal way of placing the object. The analysis includes: penetration lengths, placement stability and an investigation in Radon space. Novel visualization techniques are applied to the simulation data. A stability widget is presented for determining the placement parameters' robustness. The performance and the comparison of results provided by the tool compared with real world data is demonstrated using two specimens.