Oblique Mean-Target-rotation

Oblique target rotation in the context of exploratory factor analysis is a relevant method for the investigation of the oblique independent clusters model. It was argued that minimizing single cross-loadings by means of target rotation may lead to effects of sampling error of the inter-correlations of the target rotated factors. It was therefore proposed to compute the mean cross-loadings for each block of salient loadings in the independent clusters model and to perform target rotation in order to minimize the block-wise mean cross-loadings. A simulation study based on correlated independent factor models revealed that mean oblique target rotation resulted in a smaller negative bias of the factor inter-correlations than conventional target rotation. Therefore, this method can be recommended when target rotation is performed in the context of oblique independent factor models. An R-script and an SPSS-script for this form of target rotation are provided in the Appendix

CONRAD-2: Cold Neutron Tomography and Radiography at BER II (V7)

V7 has widely been recognized as a versatile and flexible instrument for innovative neutron imaging and has made decisive contributions to the development of new methods by exploiting different contrast mechanisms for imaging. The reason for the success in method development is the flexibility of the facility which permits very fast change of the instrument’s configuration and allows for performing non-standard experiments. The ability for complementary experiments with the laboratory X-ray tomographic scanner (MicroCT Lab) offers the opportunity to study samples at different contrast levels and spatial resolution scales

An X-ray tomographic study of rechargeable Zn/MnO2 batteries

We present non-destructive and non-invasive in operando X-ray tomographic investigations of the charge and discharge behavior of rechargeable alkaline-manganese (RAM) batteries (Zn-MnO2 batteries). Changes in the three-dimensional structure of the zinc anode and the MnO2 cathode material after several charge/discharge cycles were analyzed. Battery discharge leads to a decrease in the zinc particle sizes, revealing a layer-by-layer dissolving behavior. During charging, the particles grow again to almost their initial size and shape. After several cycles, the particles sizes slowly decrease until most of the particles become smaller than the spatial resolution of the tomography. Furthermore, the number of cracks in the MnO2 bulk continuously increases and the separator changes its shape. The results are compared to the behavior of a conventional primary cell that was also charged and discharged several times.DFG, 325093850, Open Access Publizieren 2017 - 2018 / Technische Universität Berli

Combined Application of X-Ray and Neutron Imaging Techniques to Wood Materials

Conservation of Cultural Heritage is extremely important not only from a cultural point of view, but also from a practical one. It is our duty to pass on to future generations the cultural heritage left tous by our ancestors. Wood is one of the most common materials used to generate works of art which are in a state of constant change and/or deterioration. In order to optimize the knowledge of artworks together with their conservation, it is necessary to use the most advanced scientific and technological tools. In the following paper, we will show the results which can be achieved by application of complementary techniques based on the combined use of X-rays and neutrons as structural probes

Classification of FIB/SEM-tomography images for highly porous multiphase materials using random forest classifiers

FIB/SEM tomography represents an indispensable tool for the characterization of three-dimensional nanostructures in battery research and many other fields. However, contrast and 3D classification/reconstruction problems occur in many cases, which strongly limits the applicability of the technique especially on porous materials, like those used for electrode materials in batteries or fuel cells. Distinguishing the different components like active Li storage particles and carbon/binder materials is difficult and often prevents a reliable quantitative analysis of image data, or may even lead to wrong conclusions about structure-property relationships. In this contribution, we present a novel approach for data classification in three-dimensional image data obtained by FIB/SEM tomography and its applications to NMC battery electrode materials. We use two different image signals, namely the signal of the angled SE2 chamber detector and the Inlens detector signal, combine both signals and train a random forest, i.e. a particular machine learning algorithm. We demonstrate that this approach can overcome current limitations of existing techniques suitable for multi-phase measurements and that it allows for quantitative data reconstruction even where current state-of the art techniques fail, or demand for large training sets. This approach may yield as guideline for future research using FIB/SEM tomography

Hierarchical Structuring of NMC111-Cathode Materials in Lithium-Ion Batteries: An In-Depth Study on the Influence of Primary and Secondary Particle Sizes on Electrochemical Performance

Commercially used LiNi1/3Mn1/3Co1/3O2 (NMC111) in lithium-ion batteries mainly consists of a large-grained nonporous active material powder prepared by coprecipitation. However, nanomaterials are known to have extreme influence on gravimetric energy density and rate performance but are not used at the industrial scale because of their reactivity, low tap density, and diminished volumetric energy density. To overcome these problems, the build-up of hierarchically structured active materials and electrodes consisting of microsized secondary particles with a primary particle scale in the nanometer range is preferable. In this paper, the preparation and detailed characterization of porous hierarchically structured active materials with two different median secondary particle sizes, namely, 9 and 37 mu m, and primary particle sizes in the range 300-1200 nm are presented. Electrochemical investigations by means of rate performance tests show that hierarchically structured electrodes provide higher specific capacities than conventional NMC111, and the cell performance can be tuned by adjustment of processing parameters. In particular, electrodes of coarse granules sintered at 850 degrees C demonstrate more favorable transport parameters because of electrode build-up, that is, the morphology of the system of active material particles in the electrode, and demonstrate superior discharge capacity. Moreover, electrodes of fine granules show an optimal electrochemical performance using NMC powders sintered at 900 degrees C. For a better understanding of these results, that is, of process-structure-property relationships at both granule and electrode levels, 3D imaging is performed with a subsequent statistical image analysis. Doing so, geometrical microstructure characteristics such as constrictivity quantifying the strength of bottleneck effects and descriptors for the lengths of shortest transportation paths are computed, such as the mean number of particles, which have to be passed, when going from a particle through the active material to the aluminum foil. The latter one is at lowest for coarsegrained electrodes and seems to be a crucial quantity