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Record W2139880552 · doi:10.1002/aic.12000

Understanding weathering of oil sands ores by atomic force microscopy

2009· article· en· W2139880552 on OpenAlexafffund
Sili Ren, Hongying Zhao, Jun Long, Zhenghe Xu, Jacob H. Masliyah

Bibliographic record

VenueAIChE Journal · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAsphaltWeatheringDLVO theoryOil sandsAtomic force microscopyAdhesionColloidChemistryMineralogyChemical engineeringMaterials scienceComposite materialNanotechnologyGeologyOrganic chemistryGeochemistry

Abstract

fetched live from OpenAlex

Abstract Effect of weathering on colloidal interactions between bitumen and oil sands solids was studied by atomic force microscopy (AFM). The change in bitumen chemistry due to weathering was found to have a negligible effect on the interactions of bitumen with solid particles. However, the increase in solid surface hydrophobicity due to ore weathering reversed the long‐range interaction forces between bitumen and solids from repulsive to attractive with a corresponding increase in adhesion force. The measured force profiles between bitumen and various solids can be well fitted with the extended DLVO theory by considering an additional attractive force. The attractive long‐range force and increased adhesion force make the separation of bitumen from solids more difficult and the attachment of fine solids on liberated bitumen easier, thereby leading to poor bitumen liberation and lower aeration efficiency. Such changes account for the observed poor processability of the weathered ores. © 2009 American Institute of Chemical Engineers AIChE J, 2009

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 score0.327
Threshold uncertainty score0.388

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 head0.022
GPT teacher head0.290
Teacher spread0.268 · 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

Citations31
Published2009
Admission routes2
Has abstractyes

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