Kinetics, Mechanism, and Optimization Modeling of a Green LFP Delithiation Process Developed for Direct Recycling of Lithium-Ion Batteries
Bibliographic record
Abstract
Orthorhombic LiFePO 4 (LFP) offers highly reversible redox reactions, making it an attractive cathodic material for lithium-ion batteries. This electrochemical property was exploited to develop an environmentally benign selective lithium extraction process based on CO 2 and hydrogen peroxide that can be applied to direct LFP recycling. The proof of concept of this green delithiation process was demonstrated in a previously published paper, while the process optimization and the establishment of the reaction kinetic mechanism are addressed in the current paper. First, the effects of solid to liquid ratio (S/L), temperature, CO 2 pressure, and initial H 2 O 2 to LFP molar ratio were studied through an orthogonal design of experiments. In the range of conditions studied and considering the objective of maximizing the S/L ratio, the optimal conditions are a temperature of 20 °C, a CO 2 pressure of 2 atm, and a H 2 O 2 to LFP molar ratio of 1.25. In addition, reaction kinetic models were used to determine the reaction mechanism. The activation energies obtained based on rate constants from shrinking core and Avrami models are 15.7 and 13.9 kJ mol –1, respectively. While these values reveal a mixed or diffusion-controlled heterogeneous reaction, the analysis of half-delithiated LFP particles under scanning–transmission electron microscopy revealed the reaction being controlled by nucleation rather than diffusion. In this context, the Avrami model that accounts for nucleation and growth in solid-state reactions proved the most appropriate. Further, the reaction mechanism is concluded to be limited by nucleation of FP phase within the body of LFP during the early reaction stage and to sequentially shift to the one-dimensional diffusion-limited crystallite growth regime. Finally, it is shown that CO 2 acts as a buffering agent by neutralizing the LiOH formed by Fenton-like reactions between H 2 O 2 and ferric iron in LFP.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".