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Record W3177967042 · doi:10.1002/pen.25741

Open‐cell polyvinylidene fluoride foams as carriers to promote biofilm growth for biological wastewater treatment

2021· article· en· W3177967042 on OpenAlexafffund
Pardis Ghahramani, Ahmed Eldyasti, Siu N. Leung

Bibliographic record

VenuePolymer Engineering and Science · 2021
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials sciencePolyvinylidene fluorideBiofilmBiofoulingPorosityChemical engineeringComposite materialCloggingMembranePolymerChemistry

Abstract

fetched live from OpenAlex

Abstract This article reports the design and fabrication of open‐cell polyvinylidene fluoride (PVDF) foams as carriers that can promote biofilm growth and organic removal efficiency for biological wastewater treatment in attached growth bioreactors. Open‐cell PVDF foams were fabricated by a manufacturing approach that integrated compression molding and particulate leaching. PVDF carriers were structured with two governing factors of leaching agent types (e.g., sodium chloride [NaCl] and sodium acetate [NaOAc]) and contents (e.g., 80 and 90 wt%). Open‐cell PVDF foams possessed high porosity and high protected surface area (i.e., more than ×10 to ×20 of the areas of commercialized carriers), which promoted biofilm growth in these carriers. As a successful advantage, PVDF carriers used in the moving bed biofilm reactors (MBBR) were entirely covered by biofilm in both interior and exterior parts without clogging. This provides strong evidence of the bacterial compatibility of the fabricated open‐cell PVDF foam carriers. Moreover, the specific morphology of the PVDF carriers in this article provided superior biofilm protection from the detachment in MBBR. Experimental results revealed that PVDF open‐cell foams fabricated by 80 wt% of NaCl demonstrated higher mechanical strength with an organic removal efficiency of 77% ± 7% in the corresponding bioreactor containing them.

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 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 categoriesnone
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 score0.011
Threshold uncertainty score0.655

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 studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.240
Teacher spread0.214 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2021
Admission routes2
Has abstractyes

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