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Record W2332931334 · doi:10.1021/ef5010682

Cluster of Asphaltene Nanoaggregates by DC Conductivity and Centrifugation

2014· article· en· W2332931334 on OpenAlexaff
Lamia Goual, Mohammad Sedghi, Farshid Mostowfi, Richard A. McFarlane, Andrew E. Pomerantz, Soheil Saraji, Oliver C. Mullins

Bibliographic record

VenueEnergy & Fuels · 2014
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsAlberta InnovatesSchlumberger (Canada)
Fundersnot available
KeywordsAsphalteneChemistryTolueneCluster (spacecraft)CentrifugationColloidConductivityChromatographyAnalytical Chemistry (journal)Chemical engineeringThermodynamicsOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

A model of the dominant molecular and stable colloidal structures of asphaltenes has been proposed, the Yen–Mullins model. The formation of clusters of asphaltene nanoaggregates in toluene was reported elsewhere to occur at a concentration of a few grams per liter with a cluster aggregation number of approximately 8 (Mullins, O. C. Energy Fuels 2010, 24, 2179−2207). Here, we measure the DC-conductivity signal of toluene as a function of asphaltene concentration obtaining support for the critical clustering concentration (CCC) of a roughly 1.7 g/L in toluene. In addition, the small change in the Stokes drag at the CCC indicates that the cluster aggregation number is small, less than 10. The temperature variation of the CCC is measured to be small and within error, suggesting that cluster formation is entropically driven. Centrifugation experiments were also performed on asphaltene–toluene solutions at different concentrations. These experiments confirmed that a significant change in asphaltene aggregation occurs in the concentration range of the CCC. The CCC values from centrifugation and DC-conductivity measurements are roughly the same. The centrifugation experiments confirm a cluster size of ∼5 nm corroborating the small aggregation number found in the DC-conductivity experiments. These results add to the growing body of literature validating the Yen–Mullins model.

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)0.000
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 score0.045
Threshold uncertainty score0.366

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 head0.006
GPT teacher head0.209
Teacher spread0.203 · 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

Citations50
Published2014
Admission routes1
Has abstractyes

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