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Record W4213053347 · doi:10.1016/j.jcis.2022.02.053

An approach for the scalable production of macroporous polymer beads

2022· article· en· W4213053347 on OpenAlexaff
Juan Carlos Ferrer, Qixiang Jiang, Angelika Menner, Alexander Bismarck

Bibliographic record

VenueJournal of Colloid and Interface Science · 2022
Typearticle
Languageen
FieldMaterials Science
TopicPickering emulsions and particle stabilization
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsEmulsionChemical engineeringPolymerPolymerizationMaterials scienceMethyl methacrylateSuspension polymerizationMonomerEthylene glycol dimethacrylateEmulsion polymerizationBeadPolymer chemistryComposite material

Abstract

fetched live from OpenAlex

A tubular co-flow reactor to produce macroporous polymer beads by polymerization of medium and high internal phase emulsion (M/HIPE) templates was developed. This reactor allows for improved production rates compared to tubing based microfluidic devices. Water-in-oil (W/O) M/HIPEs, containing methyl methacrylate (MMA) and ethylene glycol dimethacrylate (EGDMA) monomers in the continuous phase, were injected into a re-circulating carrier phase. The continuous phase of the emulsion droplets was UV polymerized in situ, resulting in polyM/HIPE beads. The emulsion composition was adjusted to produce poly(MMA-co-EGDMA) porous polymer beads with a protective crust and an interconnected internal pore structure. HCl loaded beads were produced by adding the active ingredient into the dispersed emulsion phase, leading to HCl encapsulation in the porous structure of the beads after polymerization. Even after exposure to ambient conditions for 24 h, 60% of the HCl remained in the beads, indicating good encapsulation efficiencies. Thus, it is possible to use such macroporous beads as delivery vehicles.

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)0.002
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 score0.009
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.015
GPT teacher head0.284
Teacher spread0.268 · 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

Citations18
Published2022
Admission routes1
Has abstractyes

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