A new method to recycle Li-ion batteries with laser materials processing technology
Bibliographic record
Abstract
Efficient and cost-effective recycling of spent lithium-ion batteries is essential for the sustainable growth of the clean energy sector, conserves critical mineral resources, and contribute to environmental sustainability. The pyrometallurgy process, involving high-temperature smelting and solid-state reduction, plays a key role in the industrial-scale recycling of these batteries. Traditional smelting methods, however, face criticism for their substantial energy requirements and the loss of lithium in slag. In this study, an innovative laser-based in-situ pyrometallurgical process, hereinafter referred to as laser recycling, was developed to recycle Li-ion batterie materials without using slag, enabling the simultaneous recovery of Co, Ni, Mn, and Li. Lab-scale experiments were carried out to investigate the influences of laser power density and duration on the carbothermic reduction behavior of battery materials. The results showed that the maximum temperature reached approximately 1850 °C with a laser power between 1500 and 2000 W focused to an area of 20 mm in diameter within a few seconds. The laser recycling facilitates concurrent smelting and solid-state reduction, with carbothermic reduction completed in just 30 s due to rapid reaction kinetics, ultra-high temperatures, and the enhanced contact area resulting from surface tension-driven molten material flow under intense laser beam exposure. This laser recycling process reduced LiCoO 2 and LiNi 0.33 Mn 0.33 Co 0.33 O 2 to metallic Co or Co-Ni-Mn alloy, respectively, while Li was recovered as Li 2 CO 3 . The new process allowed for the near-total recovery of Co, Ni, and Mn in the alloy and virtually 100% Li recovery in the form of Li 2 CO 3 by a vapor phase capture system. Additionally, continuous laser recycling in the battery material powder bed showed potentials to scale up for industry battery recycling. A mechanism for the laser recycling process was proposed. A preliminary discussion on the techno-economic implications of laser recycling was also provided. • A novel laser-based in-situ battery recycling process is developed. • Laser recycling facilitates concurrent smelting and solid-state reduction. • Laser recycling via carbothermic reduction completes in just 30 s. • The products obtained by laser recycling are metallic alloy and nano Li 2 CO 3 particles. • Continuous laser recycling in battery material powder bed with a high recycling efficiency shows potential to scale up.
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.
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) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".