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Record W2586600030 · doi:10.1021/acs.jpcc.6b11763

Adsorption of a Polyaromatic Compound on Silica Surfaces from Organic Solvents Studied by Molecular Dynamics Simulation and AFM Imaging

2017· article· en· W2586600030 on OpenAlexafffund
Yong Xiong, Tiantian Cao, Qian Chen, Zhen Li, Yue Yang, Shengming Xu, Shiling Yuan, Johan Sjöblom, Zhenghe Xu

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2017
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of Alberta
FundersNorges ForskningsrådNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsHeptaneAdsorptionToluenevan der Waals forceMoleculeChemical engineeringChemistryPhase (matter)Molecular dynamicsSolventMaterials scienceOrganic chemistryComputational chemistry

Abstract

fetched live from OpenAlex

Molecular dynamics simulation was used to investigate the adsorption of a polyaromatic compound (C5Pe) on silica surfaces from organic solvents. Heptane and toluene were used as oil phase to probe the effect of solvent properties on C5Pe adsorption. The results showed that C5Pe molecules tend to adsorb rapidly on silica surface in heptane and assemble to form long strip shaped aggregates, while in toluene C5Pe prefers to form aggregates which remain mostly in bulk oil phase. The van der Waals interactions were found to provide the largest contribution for driving the adsorption of C5Pe from heptane solutions due to the protonated state of C5Pe molecules. The calculated lower system free energy of C5Pe adsorption from heptane than from toluene corresponded well with the observed stronger adsorption of C5Pe from heptane than from toluene. AFM imaging confirmed the observed trend of C5Pe adsorption on silica from heptane and toluene.

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 score0.581
Threshold uncertainty score0.259

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 head0.244
Teacher spread0.236 · 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

Citations83
Published2017
Admission routes2
Has abstractyes

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