An international team of scientists from ESRF, SLAC, Virginia Tech and Purdue University wanted to understand and quantitatively define what leads to the failure of lithium-ion batteries. Previously, studies have either focussed on individual areas or particles in the cathode during failure or examined behaviour at the cellular level without offering sufficient microscopic details. This current study provides the first global view with unprecedented amount of microscopic structural details.
If you have a perfect electrode, every single particle should behave in the same fashion. However, electrodes are very heterogeneous and contain millions of particles. There is no way to ensure that every particle behaves the same way at the same time.
To overcome this challenge, the research team relied heavily on the synchrotron X-ray methods and used two synchrotron facilities to study electrodes in batteries. “The ESRF allowed us to study larger quantities of battery particles at higher resolution” says Feng Lin, assistant professor at Virginia Tech. Complementary experiments, in particular nano-resolution X-ray spectro-microscopy and soft Soft X-ray absorption spectroscopy, took place at Stanford’s SLAC National Accelerator Laboratory in the US.
“Hard X-ray phase contrast nano-tomography showed us each particle at remarkable resolution across the full electrode thickness. This allowed us to track the level of damage in each after using the battery. Around half of the data from the paper came from the ESRF”, explains ESRF scientist Yang Yang.
“Before the experiments we didn’t know we could study these many particles all at once. Imaging individual active battery particles has been the focus of this field. To make a better battery, you need to maximize the contribution from each individual particle”, says Yijin Liu, a scientist at SLAC.
Virginia Tech lab manufactured the materials and batteries, which were then tested for their charging and degradation behaviours at ESRF and SLAC. Kejie Zhao, assistant professor at Purdue University, led the computational modelling effort in this project.
The team’s findings offer a diagnostic method for particle utilization and how to improve fading in batteries. “This could improve how industry designs electrodes for fast-charging batteries”, concludes Yang.
