A Review on Sustainable Recycling of NdFeB Waste: Methodologies, Challenges, and the Integration of Machine Learning (ML).

The increasing demand and production of neodymium-iron-boron-based permanent magnets (NdFeB-PMs) for the electronics, energy sector, and automobile industries led to disposal consequences. The NdFeB-PMs contain a substantial amount of rare earth elements (REEs). Although China is the largest exporter of REEs to the world, it has applied some restrictive policies in terms of supply chain and taxes. To address such issues, this review systematically examines current recycling techniques, including short-loop, hydrometallurgy, pyrometallurgy, and hybrid processes, and the integration of Machine Learning (ML) to the leaching process, with a particular focus on their impact on industrial capability, economic viability, and environmental concerns. However, a comparative study highlights ongoing challenges to large-scale implementation, including fragmented waste sources, gaps between efficient processes and environmental sustainability, and a lack of regulatory and infrastructure support. To address these challenges, technical innovation in automated disassembly systems and selective REE recovery via ML was discussed, along with legislative initiatives such as Extended Producer Responsibility (EPR) and waste monitoring procedures. Furthermore, ecologically and economically feasible solutions were optimized through ML-based recycling procedures to increase the leaching efficiency and the recovery of the REEs. This analysis emphasizes the importance of collective technological, environmental, and policy initiatives to achieve sustainable NdFeB recycling and long-term resource availability. These findings offer important perspectives into developing effective and environmentally friendly NdFeB waste recycling solutions via the integration of ML.