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Superhydrophobic and Highly Oleophilic Polystyrene Fibers (PS) with Delayed Freezing Time and Effective Oil Adsorption

2018· article· en· W2906058514 on OpenAlexaff
Reza Jafari, Marc Chameau, M. Farzaneh, Gelareh Momen

Bibliographic record

VenueMaterials science forum · 2018
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsMaterials scienceContact angleWettingPolystyreneComposite materialAdsorptionHysteresisElectrospinningPorosityFiberOil dropletChemical engineeringPolymerEmulsion

Abstract

fetched live from OpenAlex

We present an efficient and simple approach for preparing superhydrophobic-superoleophilic polystyrene (PS) fibers via electrospinning. Bead-on-string fibers from a 5% PS solution and micro-sized fibers from a 20% PS solution were combined to achieve a surface having very high contact angle (about 160°) and low contact angle hysteresis. The presence of bead-on-string fibers increases the superhydrophobicity of the sorbent. The micro-sized PS fibers improve the mechanical properties of the electrospun mat through their elastic and flexible behavior. An evaluation of wettability at a low temperature (-10 oC) showed a delayed freezing time for water droplets on the superhydrophobic surface. Water droplets on a polished aluminum surface froze more quickly (about 6 seconds) than droplets on the fabricated superhydrophobic surface (about 500 seconds). Finally, the oil adsorption capacity of the developed superhydrophobic PS fibers, which have a porous surface structure, showed values of 69.1, 69.3 and 61.2 g/g for canola oil, olive oil and motor oil, respectively.

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 score0.005
Threshold uncertainty score0.920

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 studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.006
GPT teacher head0.215
Teacher spread0.209 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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