Designing New Production Processes for Lithium-Ion Batteries for a Sustainable Future

制造更好、更可持续、更便宜的锂离子电池是减少气候变化影响和实现净零碳生产战略的关键组成部分。这对电动汽车的未来尤为重要。在这个研究项目中，学生将应用尖端的粒子处理技术来制造锂离子电池电极。电极传统上使用浆液铸造工艺制造，这涉及到大量的溶剂。溶剂的使用在制造过程中引起了许多挑战，例如溶剂毒性，高能量使用增加了制造成本（和碳足迹），以及电极微观结构中的缺陷。由于这些问题，迫切需要新的电极制造技术，以减少或完全消除溶剂。在本研究项目中，学生将应用现代粒子加工技术来解决低溶剂电极制造的挑战。特别是，他们将使用计算模型，如离散元方法（DEM）来检查，理解和预测新的干电极制造工艺的性能。DEM已广泛应用于电极制造行业之外。DEM在电池制造中的应用是非常新颖的，在改变储能设备制造方面具有很大的潜力。学生将在多个长度尺度上进行研究，对混合和去团聚产生机理理解，并将这些知识应用于锂离子电池制造的新型干法加工技术的开发。他们将有机会在电极制造、计算建模、实验技术和表征方面发展技能。

The manufacture of better, more sustainable and cheaper lithium-ion batteries is a crucial part of the strategy to reduce the impact of climate change and reach net zero carbon production. This is particularly important for the future of electric vehicles. In this research project, the student will apply cutting edge particle processing techniques to the manufacture of lithium-ion battery electrodes. Electrodes are traditionally manufactured using the slurry casting process, which involves large volumes of solvents. Use of solvents cause a number of challenges during manufacture, such as solvent toxicity, high energy usage which increases the cost of manufacture (and carbon footprint), and defects in the electrode microstructural. Because of these problems, there is a strong need for new electrode manufacturing techniques which reduce or completely eliminate solvents. In this research project, the student will apply modern particle processing techniques to the challenge of low solvent electrode manufacture. In particular, they will use computational modelling such as Discrete Element Method (DEM) to examine, understand and predict the performance of new dry electrode manufacturing processes. DEM has been used widely outside of the electrode manufacturing industry. The application of DEM to battery manufacture is highly novel and has great potential to transform energy storage device manufacture. The student will perform research at multiple length scales, generate mechanistic understanding of mixing and de-agglomeration, and apply this knowledge to the development of novel dry processing technologies for lithium ion battery manufacture. They will have the opportunity to develop skills across the breadth of electrode manufacture, in computational modelling, experimental techniques and characterisation.