This review analyzes direct recycling methods for lithium-ion batteries, highlighting AI contributions to process optimization.
The surging demand for electric vehicles and energy storage technologies drives an unprecedented accumulation of spent batteries, which leads to severe environmental burdens and critical resource wastage. Traditional recycling technologies rely on high‐temperature calcination or acid/base leaching, and the final products in the form of alloys or salts can only be used as precursors. In contrast, advanced direct recycling regenerates spent cathode and anode into materials that can be directly used in battery production, simplifying the recycling process and improving economic benefits, which is expected to become a shortcut for lithium‐ion battery recycling in the future. This review analyzes the state‐of‐the‐art direct recycling methods based on the failure mechanisms for anodes and cathodes, divides them into solid‐state recycling, hydrothermal repair, and others according to different recycling conditions, and summarizes separately the advancements and limitations of each method, to guide the scale‐up and sustainability of recycling. Furthermore, this review systematically introduces artificial intelligence (AI) assisted direct recycling strategies, emphasizing the role of AI in optimizing the pretreatment and recycling processes. Finally, the practical challenges and future opportunities for direct recycling are discussed, providing important reference for further development.
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Liang et al. (2025) studied this question.
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