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Record W2139837229 · doi:10.1080/02786826.2012.741273

Coating Mass Dependence of Soot Aggregate Restructuring due to Coatings of Oleic Acid and Dioctyl Sebacate

2012· article· en· W2139837229 on OpenAlex

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

VenueAerosol Science and Technology · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCoatingSootMaterials scienceParticle sizeParticle (ecology)Oleic acidAerosolMass concentration (chemistry)Aggregate (composite)Chemical engineeringComposite materialChemistryCombustionOrganic chemistry

Abstract

fetched live from OpenAlex

Soot particles in the atmosphere can be coated with organic or nonorganic material, which may affect particle morphology and optical properties. The effect of the mass of coating on the morphology of soot particles was studied using oleic acid and dioctyl sebacate (DOS) coatings. A wide range of coatings were used, with up to 10 times as much coating as the mass of the soot. It is shown that as the coating mass increases the degree of collapsing increases until the coating is so large that the soot particle becomes completely contained within a spherical droplet of the coating material. Higher amounts of coating will not cause further collapse of the particle. The degree of collapse is also a function of the initial size of the soot particle but was independent of the coating materials tested, which have similar surface tensions. A model is presented to predict the change in mobility diameter as a function of coating mass ratio. The effect of coating mass on effective density, shape factor, and fractal dimension is also reported. Copyright 2013 American Association for Aerosol Research

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)0.001
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 score0.230
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.216
Teacher spread0.206 · 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