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Record W2942620238 · doi:10.1002/pen.25118

Study oil/water separation property of PE foam and its improvement by <i>in situ</i> synthesis of zeolitic–imidazolate framework (ZIF‐8)

2019· article· en· W2942620238 on OpenAlexaff
Long Wang, Shinsuke Nagamine, Masahiro Ohshima

Bibliographic record

VenuePolymer Engineering and Science · 2019
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversité Laval
FundersAdvanced Low Carbon Technology Research and Development Program
KeywordsMaterials scienceAcetoneChloroformChemical engineeringImidazolatePorositySolventComposite numberAbsorption of waterZeolitic imidazolate frameworkTolueneAbsorption (acoustics)SelectivityPolyethyleneComposite materialMetal-organic frameworkOrganic chemistryChemistryCatalysisAdsorption

Abstract

fetched live from OpenAlex

Herein, the oil/water separation property of four polyethylene (PE) foams with two different volume expansion ratios including 15 and 30 times was studied. We found that the PE‐30‐1 foam was the best absorbent materials among these four samples, which was also superior to the commercially available products. It demonstrated high oil absorption capacities, as well as high oil/water selectivity, which was due to its small average pore size and high porosity. In addition, this work also reports two rapid and straightforward methods to fabricate PE‐30‐1‐ZIF‐8 composite with enhanced compressive property, an encouraging absorption capacity for different organic solvents, reaching 59 times of its own weight for chloroform, as well as increased oil–water selectivity of the system. Comparing with the PE foam, the organic solvent absorption capacities for PE‐ZIF‐8‐sono composite foams were improved by 6.4%, 29%, 9.1%, and 12% for chloroform, acetone, toluene and oleic acid, respectively, while the corresponding improvement for PE‐ZIF‐8‐Me(OH) was about 7.5%, 28%, 14%, and 15%, respectively. These PE‐ZIF‐8 foams could reach the requirement for oil spill cleanup, suggesting its great potential for this type of application. POLYM. ENG. SCI., 59:1354–1361 2019. © 2019 Society of Plastics Engineers

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)0.001
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 score0.280

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.009
GPT teacher head0.232
Teacher spread0.222 · 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
Published2019
Admission routes1
Has abstractyes

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