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Record W2332164150 · doi:10.1021/la504829j

Oxygen and Carbon Dioxide Dual Gas-Responsive and Switchable Microgels Prepared from Emulsion Copolymerization of Fluoro- and Amino-Containing Monomers

2015· article· en· W2332164150 on OpenAlexafffund
Lei Lei, Qi Zhang, Shuxian Shi, Shiping Zhu

Bibliographic record

VenueLangmuir · 2015
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsCopolymerMonomerMethacrylateChemical engineeringPolymer chemistryEmulsionMaterials scienceAqueous solutionOxygenPhase (matter)AcrylamideCarbon dioxideChemistryPolymerOrganic chemistry

Abstract

fetched live from OpenAlex

We report herein the design and preparation of microgels that are responsive to both O2 and CO2 gases. The microgels were synthesized through soap-free emulsion copolymerization of O2-responsive monomer 2,3,4,5,6-pentafluorostyrene (FS) and CO2-responsive monomer 2-(diethylamino)ethyl methacrylate (DEA) with N,N'-methylenebis(acrylamide) (BisAM) as the cross-linker. The P(DEA-co-FS) microgels dispersed in aqueous solution could undergo volume phase transitions triggered by O2 and/or CO2 aeration. The particles were very responsive to CO2, while their responsivity to O2 was moderate. Microgels having different levels of the responsivity could be designed and prepared by varying the FS content in the copolymer. The phase transitions were also highly reversible, and the initial states of microgels could be easily recovered by "washing off" the trigger gases with N2. Multicycle O2, CO2, and N2 aerations were applied, and no loss in the dual gas responsivity and switchability was observed.

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)0.000
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 score0.030
Threshold uncertainty score0.630

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)0.0000.000

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 head0.010
GPT teacher head0.195
Teacher spread0.185 · 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

Citations48
Published2015
Admission routes2
Has abstractyes

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