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Record W1964561407 · doi:10.1021/jp906607s

Water Structure at Superhydrophobic Quartz/Water Interfaces: A Vibrational Sum Frequency Generation Spectroscopy Study

2009· article· en· W1964561407 on OpenAlexaff
Hidehiko Asanuma, Hidenori Noguchi, Kohei Uosaki, Hua‐Zhong Yu

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsWettingSum-frequency generationContact angleQuartzHydrogen bondMoleculeInfrared spectroscopySpectroscopyMaterials scienceHydrogenChemical engineeringChemistryOrganic chemistryComposite materialOptics

Abstract

fetched live from OpenAlex

The water structure at superhydrophobic solid/bulk water interfaces has been investigated by vibrational sum frequency generation (SFG) spectroscopy. We have adapted a simple and facile chemical modification procedure (methyltrichlorosilane/toluene treatment followed by extraction with ethanol) to prepare transparent quartz crystal surfaces with varied wetting properties, from hydrophilic to hydrophobic and superhydrophobic. In comparison with those obtained on bare quartz, the SFG spectra on polymethylsiloxane-modified surfaces showed significant changes of the relative intensities of the two broad OH stretching modes of hydrogen-bonded water at ∼3200 and ∼3450 cm −1, which can be correlated with surface morphology and molecular variations. Intriguingly, on superhydrophobic quartz these bands are very weak and replaced by a characteristic “free OH” (not hydrogen-bonded) stretching (>3600 cm −1 ) band that is typically observed at water/air interfaces. These results suggest that hydrogen bonding between water molecules weakens as hydrophobicity increases on rough heterogeneous solid surfaces. More importantly, this study provides direct evidence for the existence of stable solid/air/water three-phase interfaces when a superhydrophobic solid is in contact with bulk water.

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 categoriesInsufficient payload (model declined to judge)
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 score0.007
Threshold uncertainty score1.000

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)0.0010.000

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 head0.009
GPT teacher head0.250
Teacher spread0.242 · 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.

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

Citations30
Published2009
Admission routes1
Has abstractyes

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