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Record W2902054251 · doi:10.1021/acs.jpcc.8b09712

Understanding Adsorption of Violanthrone-79 as a Model Asphaltene Compound on Quartz Surface Using Molecular Dynamics Simulations

2018· article· en· W2902054251 on OpenAlexafffund
Tu Lan, Hongbo Zeng, Tian Tang

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2018
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Alberta
FundersCanada First Research Excellence FundNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsAdsorptionHeptaneToluenevan der Waals forceAsphalteneMolecular dynamicsMonomerStackingChemistrySolvationHydrogen bondChemical engineeringChemical physicsSolventPhysical chemistryMoleculeOrganic chemistryPolymerComputational chemistry

Abstract

fetched live from OpenAlex

A series of molecular dynamics simulations were performed to investigate the adsorption of violanthrone-79 (VO-79) as a model asphaltene compound on quartz surface in different organic solvents (n-heptane, toluene, and heptol with three different n-heptane/toluene volume ratios). Our simulations demonstrated that the type of solvent had a great impact on the kinetics of adsorption, such as the adsorption rate and final adsorption amount. However, the equilibrium modes of adsorption were similar: both monomer and aggregate adsorptions were observed regardless of the n-heptane and toluene contents. With monomer adsorption, the polyaromatic core (PAC) of VO-79 was merely parallel to the surface, whereas the PACs showed two types of orientations in aggregate adsorption—parallel and slant—with the majority of them slant to the surface, maintaining π–π stacking between neighboring PACs. Energetic analyses showed that the adsorption was driven primarily by van der Waals forces, accompanied by electrostatic interactions, hydrogen bonding, and free energy of solvation. The results reported here provide valuable insights at the molecular level into the mechanistic understanding of asphaltene adsorption on mineral surfaces in organic media.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.486

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 head0.051
GPT teacher head0.310
Teacher spread0.259 · 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

Citations36
Published2018
Admission routes2
Has abstractyes

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