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Record W2737391574 · doi:10.1002/admi.201700560

Engineering Elastic ZIF‐8‐Sponges for Oil–Water Separation

2017· article· en· W2737391574 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 Materials Interfaces · 2017
Typearticle
Languageen
FieldChemistry
TopicMetal-Organic Frameworks: Synthesis and Applications
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaCanada Research Chairs
KeywordsMaterials scienceSpongeMelamineComposite numberComposite materialPolymerLayer (electronics)Chemical engineeringNanotechnology

Abstract

fetched live from OpenAlex

Abstract This work reports a rapid and straightforward method to fabricate ZIF‐8‐melamine sponge composite with good mechanical properties, which overcomes the outstanding challenge of fabricating mechanically stable metal–organic framework (MOF)‐based 3D structures. A continuous ZIF‐8 thin layer is grown onto sponge skeleton by simple immersion of pristine sponge in ZIF‐8 precursor solution. This method is rapid, cost‐effective, easily scaled‐up, and it does not require any premodification. The obtained ZIF‐8 sponge shows an excellent compressive behavior and ZIF‐8 thin layer remained intact after over ten cycles of compression tests. In addition, the MOF/polymer shows an outstanding absorption performance of organic solvents, good recoverability, and good recyclability, demonstrating its potential in cleaning up oil spills.

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 score0.015
Threshold uncertainty score0.999

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.287
Teacher spread0.271 · 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