DrMohammad Javad Shojaei

In my current role, I am conducting experiments using X-ray tomography with the Xradia Versa 510 and performing synchrotron tomography at the Diamond Light Source beamtime (I13) to investigate how charging and discharging processes influence structural changes in battery electrodes. These experiments generate large datasets that capture the dynamic behavior of electrode materials during battery operation. To analyse this data, I am leveraging advanced image processing techniques, including the development of Super-Resolution Convolutional Neural Networks (SRCNNs) in Python. These SRCNNs are integrated with multi-scale imaging data from Scanning Electron Microscopy (SEM) to enhance the resolution and interpretability of the X-ray Computed Tomography (XCT) data. This combined approach allows me to uncover critical insights into the interactions between micro- and macro-scale phenomena within batteries. The findings from this work are guiding the design and optimization of next-generation electrode materials, contributing to the development of more efficient and durable battery technologies.