Multi-Scale Diagnosis of Lithium-Ion Batteries Using Correlative Dilatometric, Acoustic and X-ray Imaging Techniques
There are growing concerns over the environmental, climate and health impacts associated with the use of non-renewable fossil fuels. Therefore, affordable, renewable energy storage devices are becoming increasingly critical as a necessary route to transition to a clean energy ecosystem. In particular, lithium-ion batteries (LiBs) as a storage solution would enable renewable energy generation to be stored until required. To overcome the limitations of LiBs in performance, capacity, power and lifetime, it is important to understand the degradation mechanism of LiB electrodes. For example, during battery operation, electrodes undergo bulk volume changes that can exacerbate electrode strain and particle cracking, which in turn contribute to the electrode’s cumulative degradation. Hence, understanding how electrodes dilate can be of critical value in improving the durability of these energy storage devices.
In this thesis, in-situ electrochemical dilatometry (ECD) will be carried out in combination with microscopy techniques, such as scanning emission microscopy (SEM) and X-ray computed tomography (X-ray CT), to investigate bulk volume changes of LiB electrodes. X-ray CT will be carried out across multiple length-scales to allow visual interpretation of the entire cell architecture and electrode morphology. Image-based modelling and quantification of X-ray images will be carried out to reveal physical parameters of electrodes such as porosity and surface area. Finally, acoustic measurements will reveal the physical changes undergone by LiBs during operation.
The experiments reported in this work successfully demonstrate a multi-scale approach to assessing the degradation mechanisms undergone by LiBs during operation, from an electrode to whole cell assemblies. Insights from ECD and acoustic measurements can be used to inform electrode design in future generation LiBs.
https://discovery.ucl.ac.uk/id/eprint/10168667/8/Michael_10168667_Thesis_sigs_removed.pdf