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Record W2888475675 · doi:10.1002/chem.201803628

Interconnected Porous Monolith Prepared via UiO‐66 Stabilized Pickering High Internal Phase Emulsion Template

2018· article· en· W2888475675 on OpenAlexaff
Jierui Wang, He Zhu, Bo‐Geng Li, Shiping Zhu

Bibliographic record

VenueChemistry - A European Journal · 2018
Typearticle
Languageen
FieldMaterials Science
TopicPickering emulsions and particle stabilization
Canadian institutionsMcMaster University
FundersChina Postdoctoral Science FoundationState Key Laboratory of Chemical EngineeringNational Natural Science Foundation of China
KeywordsMonolithPickering emulsionMaterials scienceChemical engineeringPorosityAdsorptionScanning electron microscopeEmulsionTemplatePorous mediumNanotechnologyComposite materialChemistryCatalysisOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract High internal phase emulsion (HIPE) templating offers an efficient approach to prepare 3D hierarchical porous metal–organic framework (MOF)‐based monoliths. However, conventional poly‐Pickering HIPEs synthesized from MOF‐stabilized HIPEs have low permeability due to closed‐cell structures, thus limiting their applications. Herein, interconnected porous MOF monoliths, prepared by adding a small amount of polyvinyl alcohol (PVA) as co‐stabilizer into UiO‐66 stabilized Pickering HIPE templates are reported. The morphology of the porous monoliths was studied by scanning electron microscopy (SEM). The pore size could be well controlled by varying the PVA concentration. A unique morphology, formed by an ice template, was clearly seen on the cell wall. The pores were thus interconnected. The mass transfer performance of the monoliths having different cell structures was investigated by CO 2 adsorption. The interconnected porous structure significantly accelerated the CO 2 adsorption process, as well as enhancing the saturated adsorption capacity.

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 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 score0.018
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.265
Teacher spread0.249 · 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.

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

Citations35
Published2018
Admission routes1
Has abstractyes

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