MétaCan
Menu
Back to cohort
Record W4405531595 · doi:10.1016/j.sciaf.2024.e02510

A comprehensive review of recent advances in membrane innovations for efficient heavy metal removal from mine effluents

2024· review· en· W4405531595 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueScientific African · 2024
Typereview
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsnot available
FundersNational Research FoundationNational Science and Technology CouncilInternational Development Research Centre
KeywordsEffluentHeavy metalsEnvironmental scienceEngineeringWaste managementEnvironmental chemistryChemistry

Abstract

fetched live from OpenAlex

The growing global challenge of water scarcity, intensified by industrialization and population growth has heightened the need for effective wastewater management in industries, including the mining sector. Mining operations discharge substantial volumes of wastewater laden with toxic metal such as copper, iron, cobalt, lead and mercury which poses significant environmental as well as human health risk. Efficient wastewater treatment is crucial to mitigate these effects. While technological advancements have improved mine effluents treatment, there remains a need for advanced methods that enable not only removal of the toxic metals but also recovery of resources such as valuable metals and water. Due to its high efficiency, selectivity and low environmental footprint, membrane technology has gained attention especially in the treatment of various mine effluent. Though fouling is a major challenge in its implementation. The review gives an updated overview on the membrane technology in mining effluent treatment, examining the performance of various membranes (pressure driven membrane, thermal and concentration) in removal of metals and recycle of valuable resources from mine effluents such Acid Mine Drainage (AMD) and other mine effluents. It also examines innovative approaches such as pre-treatment processes, hybrid membrane system as well as the use nanocomposites polymeric membrane . Furthermore, the recent advances in membrane modification techniques such as chemical vapour deposition , sol-gel process, lithography, Atomic layer deposition , layer by layer and electrospinning have been discussed. Studies show that >95 % separation efficiency,> 85 % water recovery and >90 % metal recovery for hybrid membrane processes and chemical precipitation . The recovered metals show high purity of >99 %. Studies indicate that standalone membrane system have limitations in recovery of metals but hybrid systems (membrane coupled with other complementary methods) can achieve better results. This review identifies future direction for advancing membrane technology in sustainable mine wastewater management for improved environmental as well as mine operations.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.971
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.006
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.062
GPT teacher head0.349
Teacher spread0.287 · 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