Characterisation of battery electrodes using microscopy and AI
Explore battery electrode microstructures with cutting-edge microscopy and AI. Collaborate with industry and develop tools that improve battery performance analysis.
AI-generated overview
Project Description
Project Overview
This project focuses on characterising battery electrode materials to better understand their structure and behavior using microscopy combined with AI methods. It is part of a collaboration with Polaron and sponsored by The Faraday Institution.
What You Will Do
You will apply state-of-the-art microscopy techniques to collect detailed images of battery electrodes, and develop AI algorithms to analyze and interpret the complex data. The project includes a 3-month industry internship at Polaron, providing practical experience and collaboration opportunities.
Expected Outcomes
The research aims to deliver new insights into microstructural factors affecting battery performance and longevity. You will develop computational tools to enhance the predictive modelling of battery materials, supporting improved design and manufacturing processes.
Why This Matters
Understanding battery electrode microstructures is critical for advancing battery technologies, which are essential for renewable energy storage and electric vehicles. This project helps address the global challenges of energy sustainability and safety.
How to Apply
Eligibility
Supervisor Profile
Dr. Samuel J Cooper is an Associate Professor at Imperial College London's Dyson School of Design Engineering and leads the TLDR group. His research focuses on lithium-ion batteries, machine learning, generative AI, tomography, and tortuosity, with significant contributions to understanding transport phenomena in electrochemical systems and battery safety. He combines computational modeling and experimental methods to enhance battery design and analysis.