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A Review on Recycling of Waste Lead-Acid Batteries

2024· review· en· W4394999324 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Physics Conference Series · 2024
Typereview
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsQueen's University
Fundersnot available
KeywordsLead–acid batteryLead (geology)Waste managementEnvironmental scienceBusinessEngineeringBattery (electricity)GeologyPhysics

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.827
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.090
GPT teacher head0.351
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it