Designing and developing sustainable battery materials with artificial intelligence

The PhD student will develop and design an eco-friendly rechargeable battery. Artificial Intelligence will be used to design the system based on existing scientific and industrial data. It is highly desirable to use rechargeable batteries to store energy from renewable sources and in consumer electronics and automobiles. This market is dominated by lithium-ion batteries (LIB) which have high efficiency and long life cycles. LIBs are expensive, scarce, and recycling them has a large environmental impact. Using inverse engineering and deep learning, we aim to design next-generation batteries with minimal environmental impact. The successful candidate will combine data analyses with Deep Learning methods and experiment with the state-of-the-art fabrication facilities available at Durham. The candidate will have the opportunity to develop a novel model that correlates the properties of batteries to the composition of materials. This model will also consider the environmental impact of all processes in detail. Because the project has industrial support, the candidate will work closely with the company (WeLoop) to assess the life cycle assessment of existing batteries as a tool to design the next generation batteries. To be successful, a broad skill set is essential, as well as an enthusiasm for experimentation, coding/simulation, and practical engineering.