讲座主题：Machine learning for the characterisation and design of battery electrode microstructure
主讲人： Samuel J Cooper Associate Professor of Imperial College London
邀请人： Jiayu Wan
时间： 2025.08.11 10:00 ~ 2025.08.11 11:00
地点： Room 200, Yue-Kong Pao Library’s Annex
摘要： Battery companies want to know the relationship between their manufacturing parameters and the performance of the resulting cells, so that they can optimise their products for particular applications, reduce costs, and improve yield. The literature contains many examples of physics-based models of the various manufacturing processes (including mixing, coating, drying and calendaring), but these systems are hugely complex, and as a result they are expensive to simulate and hard to validate. Recent advances in generative machine learning (ML) methods have allowed the relationship from manufacturing parameters to microstructure to be directly learned from data. In this talk I will present a modular approach to the cell optimisation cycle that makes use of these ML methods, in combination with GPU accelerated metric extraction (TauFactor 2), electrochemical cell simulation (PyBaMM), and Bayesian optimisation. In addition, I will be introducing ML methods for generating 3D data from 2D images, as well as, inpainting artefacts in image data; and a data fusion method for combining multi-modal datasets using GANs. Most recently, our group has also been exploring the use of LLMs and vision transformers to accelerate scientific workflows. We are always looking for new collaborations and new data so please get in touch! If you’d like to use any of our suite of open-source tools, then head to our website: https://tldr-group.github.io.
主讲人简介 ：
Dr Sam Cooper is an Associate Professor of Artificial Intelligence for Materials Design in the Dyson School of Design Engineering at Imperial. His group develop simulation and machine learning tools for the characterisation and design of advanced materials, such as battery electrodes. Sam is also the Chief Scientist of Polaron, a company he co-founded in 2023 along with two of his former PhD students. Polaron’s generative AI models are already being used by major manufacturers to optimise their R&D workflows and in 2025 they were the winners of the inaugural Manchester Prize in “AI for the Public Good”. www.polaron.ai.
