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Record W4307030595 · doi:10.1002/adfm.202207723

Metal‐Organic Frameworks and Electrospinning: A Happy Marriage for Wastewater Treatment

2022· article· en· W4307030595 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvanced Functional Materials · 2022
Typearticle
Languageen
FieldChemistry
TopicMetal-Organic Frameworks: Synthesis and Applications
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersUniversity of British ColumbiaCanada Research Chairs
KeywordsMaterials scienceElectrospinningMetal-organic frameworkNanofiberWastewaterAdsorptionPhotodegradationMetal ions in aqueous solutionNanotechnologySewage treatmentAqueous solutionWater treatmentPortable water purificationPhotocatalysisWaste managementChemical engineeringMetalPolymerComposite materialOrganic chemistryCatalysisMetallurgyChemistry

Abstract

fetched live from OpenAlex

Abstract Metal‐organic frameworks (MOFs), an emerging class of porous organic‐inorganic hybrid materials, have shown great potential for water and wastewater treatment applications. However, pure MOF powders have limited practical applications in water treatment due to their insolubility, poor processability, brittleness, safety hazard from dust formation, and difficult separation from aqueous solutions. Thus, exploring potential MOFs composites with improved separation performance is of great importance. The marriage of MOFs with electrospun nanofiber with forethought into the final product's morphology, structure, and chemistry has opened up new opportunities for efficient wastewater treatment. The present review exhaustively summarizes the strategies to integrate MOFs into nanofibers via electrospinning to remove various pollutants (i.e., organic dyes, heavy metal ions, pharmaceuticals, personal care products, oily compounds, organic solvents, etc.) via adsorption, photodegradation, and membrane filtration. Besides, the most recent advances of electrospun MOF nanofibers for wastewater treatment and their current challenges and future outlook are delineated.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0260.000

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 head0.014
GPT teacher head0.237
Teacher spread0.223 · 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