MétaCan
Menu
Back to cohort
Record W2884143898 · doi:10.11159/ijtan.2015.003

Colloidosomes from Peroxidized Pickering Emulsions

2015· article· en· W2884143898 on OpenAlexvenueno aff
Andriy Popadyuk, Nadiya Popadyuk, Ihor Tarnavchyk, Stanislav Voronov, Andriy Voronov

Bibliographic record

VenueInternational Journal of Theoretical and Applied Nanotechnology · 2015
Typearticle
Languageen
FieldMaterials Science
TopicPickering emulsions and particle stabilization
Canadian institutionsnot available
Fundersnot available
KeywordsPickering emulsionPolymer scienceNanotechnologyChemical engineeringMaterials scienceEngineeringEmulsion

Abstract

fetched live from OpenAlex

A new approach to synthesis of cross-linked colloidosomes (microcapsules with a shell from colloidal particles) was developed on the basis of a peroxidized Pickering emulsion (an emulsion stabilized exclusively by peroxidized colloidal particles).Peroxidized latex particles were employed to ensure formation of Pickering emulsion.Free radical polymerization was used to convert droplets of a peroxidized Pickering emulsion into colloidosomes (soft template technique).The peroxidized latex particles were synthesized with the use of amphiphilic polyperoxide copolymer poly [N-(t-butylperoxymethyl) acrylamide]-co-maleic anhydride (PM-MA)applied as both initiator and surfactant (inisurf) in the emulsion polymerization process.The polymerization results in latexes with a controllable amount of peroxide and carboxyl groups (both derived from PM-MA macromolecules) at the particle surface.It was demonstrated that the structure of the synthesized (using peroxidized latex particles) colloidosomes depends on the amount of functional groups and pH during the synthesis.Thus, the size and morphology of colloidosomes can be controlled by latex particle surface properties.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.012
GPT teacher head0.257
Teacher spread0.245 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Theoretical and Applied NanotechnologySame topicPickering emulsions and particle stabilizationFrench-language works237,207