A Review on Recycling of Waste Lead-Acid Batteries
Bibliographic record
Abstract
Abstract Lead-acid batteries (LABs) have become an integral part of modern society due to their advantages of low cost, simple production, excellent stability, and high safety performance, which have found widespread application in various fields, including the automotive industry, power storage systems, uninterruptible power supply, electric bicycles, and backup power supplies. Hence, the use of LABs has greatly benefited human society and contributed to advancements in science and technology. However, the extensive use of LABs unavoidably leads to the generation of a significant amount of LABs waste. On one hand, if these waste LABs are not handled properly, any leakage can cause devastating damage to the natural environment and human health. On the other hand, waste LABs represent an important secondary resource for lead, with approximately 64.57% of global lead resources derived from recycled lead, making them a major source of lead worldwide. Moreover, approximately 85% of global lead resources are currently utilized for manufacturing LABs, and the recycling of waste LABs brings favourable prospects for the sustainable development of the energy storage industry. Therefore, the recycling of waste LABs is necessary and inevitable. In this paper, we have comprehensively reviewed the methods of recycling waste LABs. Particularly, we focused on the valuable component of waste lead paste and critically evaluated the pyrometallurgical and hydrometallurgical techniques associated with it. By categorizing and summarizing the characteristics of different methods, we have conducted a detailed comparison of these technologies, aiming to provide a comprehensive assessment of the advantages, disadvantages, status, and trends in LABs recycling technology. Additionally, the paper explores the necessity and impacts of recycling waste LABs from the perspectives of resource, energy, economy, environment, and society. It discusses the challenges faced by waste LABs recycling and presents the development prospects from both technical and non-technical point of views.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".