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Record W2318588795 · doi:10.1021/la4045896

Effect of Temperature on Morphologies of Evaporation-Triggered Asphaltene Nanoaggregates

2014· article· en· W2318588795 on OpenAlexaff
Mahsa Mehranfar, Ravi Gaikwad, Siddhartha Das, Sushanta K. Mitra, Thomas Thundat

Bibliographic record

VenueLangmuir · 2014
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAsphalteneEvaporationChemical engineeringMaterials scienceChemistryNanotechnologyOrganic chemistryThermodynamics

Abstract

fetched live from OpenAlex

We use atomic force microscopy to observe the structural changes in petroleum-asphaltene aggregates in air as a function of temperature. The aggregates are obtained by evaporating a toluene solution containing asphaltene. Increase in temperature leads to transition from self-assembled fractal structures to substantially larger mobile "liquid-like" domains that show distinct tendencies of substrate repulsion and self-coalescence. This new aggregation dynamics of asphaltene can be explained by temperature-induced transition of asphaltene from pure amorphous to liquid crystalline phase. Observation of this new phenomenon for asphaltene will have wide implications for asphaltene handling and separation.

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 score0.016
Threshold uncertainty score0.312

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 head0.005
GPT teacher head0.240
Teacher spread0.235 · 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

Citations30
Published2014
Admission routes1
Has abstractyes

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