Publications

The creation of a circular economy is seen as one of the key challenges in recycling spent Li-ion batteries and would vastly diminish pressures faced in the initial extraction stage of the life cycle. Molten salts (MS) possess a set of excellent electrochemical properties and have been used to recycle metals and non-metals in the...

The transition to widespread adoption of electric vehicles (EVs) is leading to a steep increase in lithium ion battery production around the world. With this increase it is predicted there will not only be a large increase in end of life batteries needing to be recycled, but also a substantial amount of production scrap, particularly...

In recent years, the demand for lithium-ion batteries (LIBs) has been increasing rapidly. Conventional recycling strategies (based on pyro- and hydrometallurgy) are damaging for the environment and more sustainable methods need to be developed. Bioleaching is a promising environmentally friendly approach that uses microorganisms to solubilize metals. However, a bioleaching-based technology has not yet been...

A critical component of the drive to deliver net zero economies is the introduction of electric vehicles (EVs), which necessitates a need for the development of efficient ways to recycle EV Li-ion batteries at the end of their usable life. The need for recycling is highlighted by recent EU regulations on recovery targets for key...

An acetone-based process to recover polyvinylidene fluoride (PVDF) from Li-ion battery electrodes has been developed. The PVDF binder was first dissolved away using acetone and the electrode material was subsequently subject to stirring in acetone for delamination from the current collector. The electrode became separated into electrode materials, PVDF binder, and current collector. The solubility...

This paper fuses ideas from reinforcement learning (RL), Learning from Demonstration (LfD), and Ensemble Learning into a single paradigm. Knowledge from a mixture of control algorithms (experts) are used to constrain the action space of the agent, enabling faster RL refining of a control policy, by avoiding unnecessary explorative actions. Domain-specific knowledge of each expert...