A Universal Solution for Direct Regeneration of Spent Lithium Iron Phosphate

Abstract Lithiation reactions driven by chemical potential offer a promising avenue for directly regenerating degraded lithium iron phosphate (LFP). However, the choice of solution system significantly influences the lithium supplementation where improper selection may result in poor lithium recovery or extremely slow kinetics. Herein, it is identified that the most critical factor affecting solution repair effectiveness is the redox potential of the anions in the solution, which determines whether spent LFP (SLFP) can undergo spontaneous lithiation under ambient conditions. Then, machine learning (ML) is used for prediction and screening of huge potential solution systems, and finally a general strategy is…

• GI
  Guangdong Innovative and Entrepreneurial Research Team Program

  Award: 2021ZT09L197
• NN
  National Natural Science Foundation of China

  Award: U21A20174
• SS
  Shenzhen Science and Technology Innovation Program

  Award: KQTD20210811090112002