The CaO Enhanced Defluorination and Air-Jet Separation of Cathode-Active Material Coating for Direct Recycling Li-Ion Battery Electrodes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With the rapid growth of the lithium-ion battery (LIBs) market, recycling and re-using end-of-life LIBs to reclaim the critical Li, Co, Ni, and Mn has become an urgent task. Presently, high temperature, strong acid, and alkali conditions are required to extract blended critical metals (CM) from the typical battery cathode. Hence, there is a need for more effective recycling processes for recycling blended Li, Co, Ni, and their direct regeneration for re-use in LIBs. The goal of the offered paper is the development of recycling technology for degraded battery cathode-active materials based on the thermal decomposition of polyvinylidene fluoride (PVDF) using calcination and air-jet stripping of active materials. The proposed air-jet erosion method of calcined cathode material stripping from Al foil allows for the flexible industry-applicable separation process, which is damage-free for both particles and substrate. The CaO calcination air-jet separation process and equipment can significantly improve the PVDF decomposition and the separation efficiency of the cathode materials. It is demonstrated that low-temperature CaO calcination at 350–450 °C associated with air-jet separation of active material is characterized by low environmental impact, high purity of the recycled material, and low cost as compared to pyro- and hydrometallurgical methods.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it