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Record W2313117334 · doi:10.1021/ef2008387

Effect of the Particle Size on Asphaltene Adsorption and Catalytic Oxidation onto Alumina Particles

2011· article· en· W2313117334 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

VenueEnergy & Fuels · 2011
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAsphalteneAdsorptionFreundlich equationCatalysisParticle sizeLangmuirChemical engineeringCatalytic oxidationTolueneParticle (ecology)ChemistryInorganic chemistryMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

In this study, the adsorption and catalytic oxidation of asphaltenes, problematic heavy hydrocarbons present in heavy oil, onto two aluminas with different particle sizes and comparable surface acidity were investigated. Equilibrium batch adsorption experiments were conducted at 25 °C with solutions of asphaltenes in toluene at concentrations ranging from 100 to 3000 mg/L. Adsorption data were fit to the Langmuir and Freundlich isotherm models. Nano-alumina fit better to the Langmuir model, while micro-alumina fit well to the Freundlich model. On a surface area basis, nano-alumina has higher adsorption capacity for asphaltenes than micro-alumina. Interestingly, micro-alumina has higher catalytic activity toward asphaltene oxidation than nano-alumina, at the same asphaltene loading, thus exhibiting the significance of textural properties during catalytic oxidation of asphaltenes that dominated over the effect of the particle size.

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 score0.041
Threshold uncertainty score0.286

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 head0.219
Teacher spread0.209 · 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