Battery Materials investigated by Atomic-scale Cryogenic Microscopy Characterisation

Improving the lifetime and performance of energy storage devices is key to a green-energy society. The interface of the electrolyte and electrode plays the most crucial role in batteries and capacitors. However due to the liquid phase of the electrolyte and the volatile nature of Li, characterising this region is challenging. Cryogenic sample preparation and microscopy analysis exploited for biological research has more recently been used for battery characterisation. The cryogenic vacuum conditions allows one to have an undistorted view of the resulting electrochemical reactions at these very complex interfaces. In this project we will investigate new compositions of nanomaterials and deposition methods for the next generation energy storage. There is a vast field of unexplored fundamental questions to be addressed for these energy materials that is only possible now with the development for cryogenic microscopy instrumentation and direct electron detectors for damage free imaging and spectroscopy. This project will aim to investigate:
The relationship between the electrode-electrolyte interface and the performance of lithium-ion batteries.
The complex structure of the solid-liquid interface at the atomic-scale, with an emphasis on probing the light and volatile element such as Li and H.
Changes in chemical bonding within the interfaces.
The student will be integrated into the new EPSRC UK national centre for cryogenic microscopy facility at Imperial College London (https://www.imperial.ac.uk/centre-for-cryomicroscopy/). The unique facility allows for sample transfer, under controlled atmosphere and at cryogenic temperature, between a high-end aberration-corrected transmission electron microscope and an atom probe, allowing for structural and compositional imaging of materials with an unprecedented precision. The student will also have access and support for data processing and simulations from the Imperial-X, the new centre for artificial intelligence, data science and digital technologies