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Record W2789889969 · doi:10.1021/acs.jpcc.8b00481

Effects of Thickness and Adsorption of Airborne Hydrocarbons on Wetting Properties of MoS<sub>2</sub>: An Atomistic Simulation Study

2018· article· en· W2789889969 on OpenAlexafffund
Mohammad Khalkhali, Hao Zhang, Qingxia Liu

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2018
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsUniversity of Alberta
FundersCanadian Centre for Clean Coal/Carbon and Mineral Processing Technologies
KeywordsWettingMolybdenum disulfideContact angleMonolayerAdsorptionMaterials sciencevan der Waals forceChemical engineeringSurface energyMolybdenumNanotechnologyChemical physicsChemistryComposite materialOrganic chemistryMoleculeMetallurgy

Abstract

fetched live from OpenAlex

Molybdenum disulfide (MoS 2 ) has attracted great attention due to its distinctive electronic, optical, chemical, and mechanical properties. In almost all of these applications, having a clear understanding about the wetting properties of MoS 2 is essential. The basal plane of MoS 2 has been generally believed to be hydrophobic with water contact angle (WCA) around 90°. Kozbial et al. have recently suggested that the freshly exfoliated MoS 2 was intrinsically relative hydrophilic (WCA = 69.0 ± 3.8°); however, it could become fairly hydrophobic after 1 day exposure to the ambient air (WCA = 89.0 ± 3.1°) (Kozbial et al. Understanding the Intrinsic Water Wettability of Molybdenum Disulfide (MoS 2 ). Langmuir 2015, 31, 8429–8435). They contributed this change in wetting properties to the adsorption of airborne hydrocarbons. The number of layers is another important factor that is believed to affect the wetting properties in ultrathin MoS 2 films. For highly crystalline samples grown at high temperature (900°C), Gaur et al. showed that the WCA was a function of number of layers and changed from 98° in monolayer sample to 88° in a sample with 11 layers (Gaur et al. Surface Energy Engineering for Tunable Wettability through controlled synthesis of MoS 2 . Nano Lett. 2014, 14, 4314–4321). In this work, we study the effects of these two parameters, namely, adsorption of airborne hydrocarbon contaminants and the number of layers, on MoS 2 wetting properties using atomistic simulations. Results of our simulations confirm that both of these factors can affect the wetting properties of MoS 2 through altering van der Waals interactions between MoS 2 and water. We also show that the contributions of both energy and entropy of adhesion should be considered to understand the wetting properties of MoS 2 . Results of this work improve our understanding about the wetting properties of MoS 2 and other transition metal dichalcogenides.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.254
Teacher spread0.241 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations22
Published2018
Admission routes2
Has abstractyes

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