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Record W3134446505 · doi:10.1126/sciadv.abc7926

Wax-wetting sponges for oil droplets recovery from frigid waters

2021· article· en· W3134446505 on OpenAlex
Pavani Cherukupally, Wei Sun, Daryl R. Williams, Geoffrey A. Ozin, Amy M. Bilton

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

VenueScience Advances · 2021
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationNational Natural Science Foundation of ChinaImperial College LondonFisheries and Oceans CanadaEnvironment and Climate Change CanadaUniversity of Toronto
KeywordsWettingWaxArcticSpongeEnvironmental scienceChemical engineeringMaterials scienceGeologyOceanographyComposite materialEngineeringPaleontology

Abstract

fetched live from OpenAlex

Energy-efficient recovery of oil droplets from ice-cold water, such as oil sands tailings, marine, and arctic oil spills, is challenging. In particular, due to paraffin wax crystallization at low temperatures, the crude oil exhibits high viscosity, making it difficult to collect using simple solutions like sponges. Here, we report a wax-wetting sponge designed by conforming to the thermoresponsive microstructure of crude oil droplets. To address paraffin wax crystallization, we designed the sponge by coating a polyester polyurethane substrate with nanosilicon functionalized with paraffin-like octadecyl ligands. The wax-wetting sponge can adsorb oil droplets from wastewater between 5° and 40°C with 90 to 99% removal efficacy for 10 cycles. Also, upon rinsing with heptol, the adsorbed oil is released within seconds. The proposed approach of sponges designed to conform with the temperature-dependent microstructure of the crude oils could enable cold water technologies and improve circular economy metrics in the oil industry.

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 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 score0.041
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.021
GPT teacher head0.278
Teacher spread0.257 · 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