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Record W2003499315 · doi:10.1039/c4cp03117b

Interaction of H<sub>2</sub>O and H<sub>2</sub>S with Cu(111) and the impact of the electric field: the rotating &amp; translating adsorbate, and the rippled surface

2014· article· en· W2003499315 on OpenAlexafffund
Jin Hyun Chang, Ahmed Huzayyin, Keryn Lian, F.P. Dawson

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicnanoparticles nucleation surface interactions
Canadian institutionsUniversity of TorontoToronto Public Health
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectric fieldAdsorptionDipoleField (mathematics)ChemistryRotation (mathematics)Surface (topology)Molecular physicsMoleculeElectronChemical physicsCondensed matter physicsPhysicsPhysical chemistryGeometry

Abstract

fetched live from OpenAlex

The interactions of H2O and H2S monomers with Cu(111) in the absence and presence of an external electric field are studied using density functional theory. It is found that the adsorption is accompanied by a rippled pattern of the surface Cu atoms and electron accumulation on the surface Cu atoms surrounding the adsorption site. The response of the H2O/Cu(111) and H2S/Cu(111) interfaces to the external electric field is computed up to the field magnitude of 10(10) V m(-1). The results show that H2O rotates and translates much more with an electric field than H2S does. The extent of the surface deformation changes considerably with the applied electric field, which influences the translation pattern of the adsorbates. On the other hand, the rotation of the adsorbates is correlated to the dipole moment of the molecules and their adsorption energies.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.007
GPT teacher head0.223
Teacher spread0.216 · 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

Citations13
Published2014
Admission routes2
Has abstractyes

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