New Research From Our Sister Projects
Progress towards a circular battery value chain depends on more than one technology. From recovering valuable materials from increasingly complex battery waste to reliably assessing the environmental performance of emerging recycling solutions, research across the battery community is addressing different pieces of the same challenge. Two ReUse sister projects, Revitalise and STREAMS, have recently contributed to this effort with new scientific publications.
The Revitalise project published Towards a direct recycling approach for complex Li/Na ion cathode mixtures: a selective leaching approach to separate components in ChemRxiv.
The study addresses a growing recycling challenge: mixtures of different lithium-ion and sodium-ion cathode materials can arise through blended electrodes or cross-contamination during shredding, making direct recycling more difficult. The researchers demonstrate a selective leaching approach using ascorbic acid to separate a commercial sodium-ion NFM cathode material from Ni-rich NMC, enabling the NMC to be directly regenerated while the NFM is recovered from the leachate through a short-loop route. Importantly, the regenerated NMC retained the morphology of the original material and achieved comparable performance, while the NFM was also successfully regenerated, although further optimisation is needed to match its pristine performance.
The STREAMS project published Machine learning and large language models for life cycle inventory compilation: Current situation and future developmentsin Renewable and Sustainable Energy Reviews.
The study investigates how machine learning, natural language processing and large language models could address gaps in Life Cycle Inventory (LCI) data, which are particularly common for emerging low-carbon technologies. Through a literature review and case studies, the researchers show that ML can improve the estimation of missing inventory data, while generative LLMs can help identify and extract relevant LCI information from scientific literature. At the same time, the paper stresses that these technologies should complement rather than replace traditional LCI methods and human expertise. More work is needed to develop robust, transparent and reproducible AI-assisted approaches suitable for large-scale use in Life Cycle Assessment.
At first glance, the two publications address very different topics. Yet both connect closely with the ambitions of ReUse. ReUse is developing processes for recycling LFP battery production waste and end-of-life batteries, including sorting, separation, purification and regeneration of valuable materials for their return to battery production. The Revitalise research highlights why flexible separation strategies will become increasingly important as battery chemistries and waste streams diversify, while the STREAMS publication underscores the importance of high-quality, representative data for assessing whether emerging recycling technologies deliver the intended environmental benefits.
The studies highlight that a circular battery value chain needs effective material recovery and reliable knowledge of environmental impacts. Both projects, like ReUse, are linked through Battery 2030+ and Batt-Bridge to even more amazing research groups. We encourage you to explore both publications and follow the latest results emerging from our sister projects and the wider European battery research community.