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Organisationseinheit der BAM
- 8 Zerstörungsfreie Prüfung (4) (entfernen)
The understanding of dynamic processes in Li-metal batteries is an important consideration to enable the full capacity of cells to be utilised. These processes, however, are generally not directly observable using X-ray techniques due to the low attenuation of Li; and are challenging to visualise using neutron imaging due to the low temporal resolution of the technique. In this work, complementary X-ray and neutron imaging are combined to track the dynamics of Li within a primary Li/SOCl2 cell. The temporal challenges posed by neutron imaging are overcome using the golden ratio imaging method which enables the identification of Li diffusion in operando. This combination of techniques has enabled an improved understanding of the processes which limit rate performance in Li/SOCl2 cells and may be applied beyond this chemistry to other Li-metal cells.
Spectral neutron tomography
(2021)
Combined three-dimensional (3D) mapping of (micro-)structures with elemental and crystalline phase variations is of significant importance for the characterization of materials. Neutron wavelength selective imaging is a spectral imaging technique that exploits unique contrast differences e.g. for mapping dissimilar elemental, isotope, or phase compositions, and has the particular advantage of being applicable to sample volumes on the meso- and macroscale. While being mostly applied as radiography (2D) so far, we herein report that the extension to tomography allows for the display of the full spectral information for every voxel and in 3D. The development is supported by example data from a continuous as well as a pulsed neutron source. As a practical example, we collected 4D data sets (3D + spectral) of plastically deformed metastable stainless steel and herein demonstrate an improved quantification strategy for crystalline phase fractions. These exemplary results illustrate that localized phase transformations can be quantified even in complex geometries within centimeter-sized samples, and we will discuss the limits and future prospects of the technique that is not limited to crystalline materials.
The ability to track electrode degradation, both spatially and temporally, is fundamental to understand performance loss during operation of lithium batteries. X-ray computed tomography can be used to follow structural and morphological changes in electrodes; however, the direct detection of electrochemical processes related to metallic lithium is difficult due to the low sensitivity to the element. In this work, 4-dimensional neutron computed tomography, which shows high contrast for lithium, is used to directly quantify the lithium diffusion process in spirally wound Li/SOCl2 primary cells. The neutron dataset enables the quantification of the lithium transport from the anode and the accumulation inside the SOCl2 cathode to be locally resolved. Complementarity between the collected neutron and X-ray computed tomographies is shown and by applying both methods in concert we have observed lithium diffusion blocking by the LiCl protection layer and identified all cell components which are difficult to distinguish using one of the methods alone.
In recent years, low-temperature polymer electrolyte fuel cells have become an increasingly important pillar in a zero-carbon strategy for curbing climate change, with their potential to power multiscale stationary and mobile applications. The performance improvement is a particular focus of research and engineering roadmaps, with water management being one of the major areas of interest for development. Appropriate characterisation tools for mapping the evolution, motion and removal of water are of high importance to tackle shortcomings.
This article demonstrates the development of a 4D high-speed neutron imaging technique, which enables a quantitative analysis of the local water evolution. 4D visualisation allows the time-resolved studies of droplet formation in the flow fields and water quantification in various cell parts. Performance parameters for water management are identified that offer a method of cell classification, which will, in turn, support computer modelling and the engineering of next-generation flow field designs.