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The neutron imaging instrument CONRAD was operated as a part of the user program of the research reactor BER‐II at Helmholtz‐Zentrum Berlin (HZB) from 2005 to 2020. The Instrument was designed to use the neutron flux from the cold source of the reactor, transported by a curved neutron guide. The pure cold neutron spectrum provided a great advantage in the use of different neutron optical components such as focusing lenses and guides, solid‐state polarizers, Monochromators and phase gratings. The flexible setup of the instrument allowed for implementation of new methods including wavelength‐selective, dark‐field, phase‐contrast and imaging with polarized neutrons. In summary, these developments helped to attract a large number of scientists and industrial customers, who were introduced to neutron imaging and subsequently contributed to the Expansion of the neutron imaging community.
Understanding the complicated interplay of the continuously evolving electrode materials in their inherent 3D states during the battery operating condition is of great importance for advancing rechargeable battery research.
In this regard, the synchrotron X-ray tomography technique, which enables non-destructive, multi-scale, and 3D imaging of a variety of electrode components before/during/after battery operation, becomes an essential tool to deepen this understanding. The past few years have witnessed an increasingly growing interest in applying this technique in battery research. Hence, it is time to not only summarize the already obtained battery-related Knowledge by using this technique, but also to present a fundamental elucidation of this technique to boost future studies in battery research. To this end, this review firstly introduces the fundamental principles and experimental Setups of the synchrotron X-ray tomography technique. After that, a user guide to ist application in battery research and examples of its applications in Research of various types of batteries are presented. The current review ends with a discussion of the future opportunities of this technique for next-generation rechargeable batteries research. It is expected that this review can enhance the reader’s understanding of the synchrotron X-ray tomography technique and stimulate new ideas and opportunities in battery research.
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.
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.