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Record W2317367551 · doi:10.1021/la503968v

Determination of Charge on Asphaltene Nanoaggregates in Air Using Electrostatic Force Microscopy

2014· article· en· W2317367551 on OpenAlexafffund
Ravi Gaikwad, Aharnish Hande, Siddhartha Das, Sushanta K. Mitra, Thomas Thundat

Bibliographic record

VenueLangmuir · 2014
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Alberta
FundersCanada Excellence Research Chairs, Government of Canada
KeywordsAsphalteneAtomic force microscopyMicroscopyNanotechnologyChemistryChemical engineeringMaterials scienceElectrostatic force microscopeElectrostaticsAnalytical Chemistry (journal)ChromatographyOrganic chemistryPhysical chemistryOpticsPhysics

Abstract

fetched live from OpenAlex

In this paper, we provide measurement of charge of asphaltene nanoaggregates in air using electrostatic force microscopy. We obtain the average surface charge density of the nanoaggregates as 43.7 nC/cm(2). Among the different aspects of asphaltene, one of the least known is its charge and the effect of solvent and compositional variability (of asphaltene) in dictating this charge. For aqueous systems, asphaltene charge demonstrates a strong dependence on the pH and the salt concentration, indicating that a possible ionization of the surface groups leads to this charging. On the contrary, for asphaltene in nonpolar media (e.g., toluene and heptane), it is believed that asphaltene native charge is central in dictating this charging. This native charge is the solvent-independent charge or the asphaltene charge in air. Our measurements, therefore, provide the first direct quantification (i.e., a quantification of charge not from the measurement of the asphaltene mobilities, which in turn requires specification of the nonuniform asphaltene size distribution) of this asphaltene native charge by conducting the measurements in air. Similar measurements in a solvent may introduce a solvent-dependent value, thereby forbidding not only the exact quantification of this native charge but also the understanding of the specific role of the solvent. This measurement, therefore, will provide a useful starting point to quantify the mechanism of asphaltene charging in nonpolar solvents with important ramifications in deciphering the role of asphaltene in transport and handling of crude and heavy oils.

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 score0.028
Threshold uncertainty score0.346

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 head0.008
GPT teacher head0.265
Teacher spread0.256 · 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

Citations25
Published2014
Admission routes2
Has abstractyes

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