Abstract
The new global decarbonization and energy transition guidelines have caused the industrial sector to undergo a metamorphosis towards more sustainable alternatives. To this end, phenomena such as digital transformation and the implementation of new solutions at the forefront of technological advances are helping to accelerate these changes. Key sectors for the future of society and industry, such as batteries, are already employing different tools based on big data, machine learning and artificial intelligence solutions to optimize both their design and production phases, with the aim of boosting a sector that is expected to reach a demand of almost 4.9 TWh by the end of this decade.
However, these prospects also pose a major long-term challenge: the recycling of all these devices. Considering that this is an industry with increasingly stringent standards in terms of sustainability and circularity, this is where, once again, digital solutions such as those mentioned above can play a key role, both in terms of optimizing current recycling processes and developing new proposals and approaches.
This paper aims to identify precisely that set of opportunities that artificial intelligence-based solutions can present to the battery recycling industry in its activities. Especially, in terms of development, evolution and optimization of the most promising technological routes (such as hydrometallurgy, pyrometallurgy or direct recycling), in order to respond to the challenges and needs of a strategic activity for the future of the battery value chain.
Keywords: Batteries, Recycling, Recovery, Waste, Artificial Intelligence, Automation, Hydrometallurgy, Pyrometallurgy, Direct Recycling.