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Record W2329804815 · doi:10.1021/la1020498

Pickering Emulsion Templated Layer-by-Layer Assembly for Making Microcapsules

2010· article· en· W2329804815 on OpenAlex
Jian Li, Harald D. H. Stöver

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.

Bibliographic record

VenueLangmuir · 2010
Typearticle
Languageen
FieldMaterials Science
TopicPickering emulsions and particle stabilization
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPickering emulsionPolyelectrolyteCoatingNanoparticleLayer by layerChemical engineeringMaterials scienceEmulsionComposite numberCopolymerLayer (electronics)PorosityNanotechnologyPolymer chemistryChemistryComposite materialPolymer

Abstract

fetched live from OpenAlex

Pickering emulsions stabilized by poly(sodium styrenesulfonate) (PSS) surface-modified LUDOX CL particles were used as templates for the layer-by-layer (LbL) deposition of polyelectrolytes and charged nanoparticles to form composite shells. The microcapsules resulting from repeated LbL coating with poly(diallyldimethylammonium chloride) (PDADMAC) and PSS had porous walls due to the loose arrangement of the original nanoparticle aggregates at the oil-water interface, leading to significant microcapsule rupture and low encapsulation efficiency. Microcapsules formed by coating with PDADMAC and anionic LUDOX HS nanoparticles led to dense walls and stronger microcapsules, suitable for microencapsulation of hydrophobic materials with a wide range of polarities.

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 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 score0.044
Threshold uncertainty score0.455

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 head0.028
GPT teacher head0.305
Teacher spread0.276 · 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